The development of the Internet of Things (IoT) has led to the widespread use of WiFi-enabled consumer electronic devices, which are now common in everyday life. These advancements in IoT have greatly improved data collection and analysis capabilities, especially for health monitoring applications. However, traditional centralized machine learning methods often fall short, raising significant privacy concerns and requiring extensive data collection, which is inefficient. To address these limitations within the distributed IoT environment, this article presents a federated learning (FL)-based WiFi sensing system specifically designed for health monitoring. By enabling local model training, our system prevents the sharing of sensitive data, thus reducing the risk of privacy breaches. We further enhance our system with a secret sharing mechanism coupled with model sparsification to significantly improve privacy. Additionally, our improved top-k model sparsification algorithm, equipped with adaptive residuals, reduces communication overhead while ensuring high accuracy. Extensive testing across various datasets and models confirms that our system outperforms existing benchmarks in terms of privacy protection and communication efficiency, marking a substantial advancement in health monitoring within the IoT.

A prominent countermeasure against side-channel attacks, the hiding countermeasure , typically involves shuffling operations using a permutation algorithm. This is especially crucial in the era of Post-quantum Cryptography, where computational characteristics of lattice and code-based cryptography heighten the need for robust defenses. In this context, securely and efficiently generating permutations is critical for an algorithm’s overall security and performance. Among the various approaches, the Fisher-Yates shuffle is widely adopted due to its security and ease of implementation. However, it is limited by a complexity of \(\mathcal {O}(N)\) due to its sequential nature. In response, we propose a time-area tradeoff swap algorithm, \(\mathsf {FSS}\) , that leverages a Butterfly Network structure, achieving only \(\log (N)\) depth, \(\log (N)\) work, and \(\mathcal {O}(1)\) operation time in parallel. Our analysis calculates the maximum gain an attacker can achieve through butterfly operations with \(\log (N)\) depth from a side-channel analysis perspective. Notably, we derive a generalized formula for the attack complexity of higher-order side-channel attacks for arbitrary input sizes, utilizing the fractal structure of the butterfly network. Moreover, our research demonstrates the efficiency and security of this permutation approach across different platforms. We include practical implementation results on ASIC as well as on CPU and GPU architectures, which underscore the algorithm’s performance advantages and robustness across diverse hardware environments. Through this exploration, we show that efficient and secure permutations can indeed be achieved with minimal randomness requirements.

Summary This article presents a tracing mechanism for group signatures answering the security threats of malicious authorities and users' forgeries. The proposal weakens the high trust placed on the centralized tracing party in previous group signatures by decentralizing tracing power using a multiple tracer setting and limiting the tracers' access using attribute‐based encryption and the requirement of the group manager's agreement. We allow the group manager to control tracers identifying his group users. Instead of a centralized tracer, our setting has multiple tracers possessing attribute sets. Thus, after getting the group manager's permission, a tracer should satisfy the access policy in a given signature to identify the signer. On the other hand, our group signature scheme decentralizes the tracing key generation and removes the group manager's tracing ability. Thus, it ensures that only the attribute‐satisfying and permitted tracers can identify the signer. Moreover, this article delivers security against malicious users. It presents a verification process of access policy of the signatures to prevent users from utilizing invalid attributes for signing. In addition, the article delivers a collaborative tracing mechanism to satisfy attribute sets that a tracer fails to fulfill alone for identifying a signer. Thus, our tracing mechanism ensures security against malicious authorities and group users in group signatures. The article gives the general construction of the scheme and discusses the security.

In recent years, growing research interest from both industry and academia has been aroused to the vehicular networks, which is regarded as the fundamental component of the modern intelligent transportation system (ITS). Lots of remarkable research outputs with respect to secure vehicular data interactions and user privacy preservation has been witnessed. However, the existing schemes all focus on the common vehicular communication scenarios where facilities are deployed, whereas the secure data exchange in the abnormal infrastructure-less vehicular environment has not been properly investigated. To deal with unpredictable abnormal situations caused by artificial or natural disasters such as earthquakes and floods, a distinctive vehicle-assisted aggregate authentication mechanism for infrastructure-less vehicular networks is presented in this paper. With assistance from the neighboring vehicles, the homomorphic signature involving all requesting vehicles is generated and forwarded to the remaining functional RSUs. Meanwhile, vehicular group communication among the validated entities is enabled. Additionally, the fault-tolerant verification method is adopted such that the ineffective entities can be easily distinguished and removed without interfering with other requesting vehicles. The security proofs and discussions regarding vital security properties are presented, while the performance analysis follows. Compared with the state-of-the-art, advantages in terms of security and performance properties can be proved.

Blockchain is an important supporting technology for various sustainable systems. It relies on a number of distributed nodes running blockchain client software, which is responsible for some critical tasks, such as communicating with other nodes and generating new blocks. However, the quick evolution of blockchain technology brings crucial challenges to blockchain client design. After carefully examining existing blockchain client software, we have identified a critical weakness: Blockchain clients are weak in supporting live upgrades, resulting in a blockchain fork that incurs security concerns and risks. In this article, we propose Phoenix, a novel blockchain client design that is live upgradable. Phoenix uses blockchain service encapsulation to decouple blockchain services. Based on service encapsulation, we propose a live upgrade scheme that packs upgrade codes into blockchain transactions and uses a Just-In-Time engine to avoid service interruption. A parallel execution engine is developed to increase service efficiency. We evaluated Phoenix on a 51-node blockchain, and experimental results show that Phoenix outperforms existing solutions in overhead and upgrade latency.

We propose a decentralized but collaborative attribute-based tracing mechanism (a signer-identifying mechanism) for group signatures. Instead of a central tracing party in our scheme, a set of tracers satisfying the attribute set used for generating the group signature can identify the signer. Thus our proposal limits the parties who can identify the signer. On the other hand, it decentralized the tracing authority.

Any person can post arbitrary strings on the bulletin board. Following publication on bulletin board, a party receives a "evidence" that the intended data were posted. The bulletin board is open to the public, which means that anyone can view its contents. The fundamental security criteria for a BB are that its contents cannot be deleted, and that no evidence of publication can be falsified. BB was commonly perceived as a trusted and publicly verifiable channel. It formed the backbone of many important protocols such as e-voting, secure multi-party computation etc. and quite often it was assumed to exist to support the execution of the main protocol. After the advent of blockchain technology, BB systems has found a strong footing regarding its implementation in a distributed manner. In this paper, we aim to provide a concise summary of the evolution of bulletin board, its implementation issues and security analysis with an emphasis on its impact to e-voting systems.

Modern Internet of Things (IoT) systems are highly complex due to its mobile, ad-hoc and geographically distributed nature. Very often, an edge-cloud infrastructure is established to offer intelligent services in modern IoT systems. However, IoT edge devices are typically resource-constrained and can not perform sophisticated machine learning algorithm on board. Data sharing with a central server is a common approach of crowdsourcing, but also brings privacy and security concerns. The emerging federated learning offers a promising pathway to achieve an accurate model through distributed machine learning while ensuring data privacy. The existing federated learning process is not tailored to the mobile and adhoc nature of IoT systems where devices are of varying data and system qualities and may not be able to participate the entire training process. Therefore, in this paper, a new federated learning framework is proposed to support asynchronous model fusion with clustering-based participant selection. The proposed framework aims to accommodate the ad-hoc nature of IoT devices, and at the same time avoiding low quality or even malicious data from its participants to ensure model convergence and performance.

All-or-nothing transforms (AONT) were proposed by Rivest as a message preprocessing technique for encrypting data to protect against brute-force attacks, and have many applications in cryptography and information security. Later the unconditionally secure AONT and their combinatorial characterization were introduced by Stinson. Informally, a combinatorial AONT is an array with the unbiased requirements and its security properties in general depend on the prior probability distribution on the inputs s-tuples. Recently, it was shown by Esfahani and Stinson that a combinatorial AONT has perfect security provided that all the inputs s-tuples are equiprobable, and has weak security provided that all the inputs s-tuples are with non-zero probability. This paper aims to explore on the gap between perfect security and weak security for combinatorial (t, s, v)-AONTs. Concretely, we consider the typical scenario that all the s inputs take values independently (but not necessarily identically) and quantify the amount of information $H(\mathcal{X}\mid \mathcal{Y})$ about any t inputs $\mathcal{X}$ that is not revealed by any s−t outputs $\mathcal{Y}$. In particular, we establish the general lower and upper bounds on $H(\mathcal{X}\mid \mathcal{Y})$ for combinatorial AONTs using information-theoretic techniques, and also show that the derived bounds can be attained in certain cases.

All-or-nothing transforms (AONTs) were proposed by Rivest as a message preprocessing technique for encrypting data to protect against brute-force attacks, and have numerous applications in cryptography and information security. Later the unconditionally secure AONTs and their combinatorial characterization were introduced by Stinson. Informally, a combinatorial AONT is an array with the unbiased requirements and its security properties in general depend on the prior probability distribution on the inputs$s$-tuples. Recently, it was shown by Esfahani and Stinson that a combinatorial AONT has perfect security provided that all the inputs$s$-tuples are equiprobable, and has weak security provided that all the inputs$s$-tuples are with non-zero probability. This paper aims to explore on the gap between perfect security and weak security for combinatorial$(t,s,v)$-AONTs. Concretely, we consider the typical scenario that all the$s$inputs take values independently (but not necessarily identically) and quantify the amount of information$H(\mathcal {X}|\mathcal {Y})$about any$t$inputs$\mathcal {X}$that is not revealed by any$s-t$outputs$\mathcal {Y}$. In particular, we establish the general lower and upper bounds on$H(\mathcal {X}|\mathcal {Y})$for combinatorial AONTs using information-theoretic techniques, and also show that the derived bounds can be attained in certain cases. Furthermore, the discussions are extended for the security properties of combinatorial asymmetric AONTs.

Technology advances—such as improving processing power, battery life, and communication functionalities—contribute to making mobile devices an attractive research area. In 2008, in order to manage mobility, the Internet Engineering Task Force (IETF) developed Proxy Mobile IPv6, which is a network-based mobility management protocol to support seamless connectivity of mobile devices. This protocol can play a key role in volunteer computing paradigms as a user can seamlessly access computing resources. The procedure of user authentication is not defined in this standard; thus, many studies have been carried out to propose suitable authentication schemes. However, in the current authentication methods, with reduced latency and packet loss, some security and privacy considerations are neglected. In this study, we propose a secure and anonymous ticket-based authentication (SATA) method to protect mobile nodes against existing security and privacy issues. The proposed method reduces the overhead of handover authentication procedures using the ticket-based concept. We evaluated security and privacy strengths of the proposed method using security theorems and BAN logic.

Recently, deep learning based natural language processing techniques are being extensively used to deal with spam mail, censorship evaluation in social networks, among others. However, there is only a couple of works evaluating the vulnerabilities of such deep neural networks. Here, we go beyond attacks to investigate, for the first time, universal rules, i.e., rules that are sample agnostic and therefore could turn any text sample in an adversarial one. In fact, the universal rules do not use any information from the method itself (no information from the method, gradient information or training dataset information is used), making them black-box universal attacks. In other words, the universal rules are sample and method agnostic. By proposing a coevolutionary optimization algorithm we show that it is possible to create universal rules that can automatically craft imperceptible adversarial samples (only less than five perturbations which are close to misspelling are inserted in the text sample). A comparison with a random search algorithm further justifies the strength of the method. Thus, universal rules for fooling networks are here shown to exist. Hopefully, the results from this work will impact the development of yet more sample and model agnostic attacks as well as their defenses.

This paper analyses the problem of efficiently routing XML documents on a network whose nodes are capable of distributed XML processing. The goal of our study is to find network paths for which XML documents’ transmission will result in high likelihood that a large portion of the documents be processed within the network, decreasing the amount of XML processing at documents arrival at the destination site. We propose several routing algorithms for single route and multipath routing and evaluate them on a distributed XML network simulation environment. We show the benefits of the proposed XML routing algorithms as compared with widespread minimum hop routing strategy of the Internet.

Summary In this paper, we explore the problem of providing selective read/write access to the outsourced data for clients using mobile devices in an environment that supports users from multiple domains and where attributes are generated by multiple authorities. We consider Ciphertext‐Policy Attribute‐based Encryption (CP‐ABE) scheme as it can provide access control on encrypted outsourced data. One limitation of CP‐ABE is that the users can modify the access policy specified by the data owner if write operations are introduced in the scheme. We propose a protocol for providing different levels of access to outsourced data that permits the authorized users to perform write operation without altering the access policy specified by the data owner. Our scheme provides fine‐grained read/write access to the users, accompanied with a light weight signature scheme and computationally inexpensive user revocation mechanism suitable for resource‐constrained mobile devices. We provide a theoretical analysis of the security of the proposed protocol and the experimental results measured from a real‐world testbed.

Recent research has revealed that the output of deep neural networks (DNNs) can be easily altered by adding relatively small perturbations to the input vector. In this paper, we analyze an attack in an extremely limited scenario where only one pixel can be modified. For that we propose a novel method for generating one-pixel adversarial perturbations based on differential evolution (DE). It requires less adversarial information (a black-box attack) and can fool more types of networks due to the inherent features of DE. The results show that 67.97% of the natural images in Kaggle CIFAR-10 test dataset and 16.04% of the ImageNet (ILSVRC 2012) test images can be perturbed to at least one target class by modifying just one pixel with 74.03% and 22.91% confidence on average. We also show the same vulnerability on the original CIFAR-10 dataset. Thus, the proposed attack explores a different take on adversarial machine learning in an extreme limited scenario, showing that current DNNs are also vulnerable to such low dimension attacks. Besides, we also illustrate an important application of DE (or broadly speaking, evolutionary computation) in the domain of adversarial machine learning: creating tools that can effectively generate low-cost adversarial attacks against neural networks for evaluating robustness.

When a user consumes an encrypted digital content (for example video and music files), the player application accesses the secret key to decrypt the content. If the user is malicious, he can analyse the access pattern of the player application to extract the secret key efficiently. Oblivious RAMs (ORAMs) are effective solution for such threats. However, ORAMs are only effective for `passive' attackers who can observe the RAM access done by the application, but cannot alter data stored on RAM. The attacker with ability to alter data on RAM can be called `active' attackers. In this paper, we evaluate the security of ORAM schemes against active adversaries where they alter data on RAM and try to efficiently extract the secret information. We also propose countermeasures against active adversaries.

The Internet of Things (IoT) is an extension of the traditional Internet, which allows a very large number of smart devices, such as home appliances, network cameras, sensors and controllers to connect to one another to share information and improve user experiences. IoT devices are micro-computers for domain-specific computations rather than traditional function-specific embedded devices. This opens the possibility of seeing many kinds of existing attacks, traditionally targeted at the Internet, also directed at IoT devices. As shown by recent events, such as the Mirai and Brickerbot botnets, DDoS attacks have become very common in IoT environments as these lack basic security monitoring and protection mechanisms. In this paper, we propose a novel light-weight approach for detecting DDos malware in IoT environments. We extract the malware images (i.e., a one-channel gray-scale image converted from a malware binary) and utilize a light-weight convolutional neural network for classifying their families. The experimental results show that the proposed system can achieve 94:0% accuracy for the classification of goodware and DDoS malware and 81:8% accuracy for the classification of goodware and two main malware families.

Outsourcing data to the cloud for computation and storage has been on the rise in recent years. In this paper we investigate the problem of supporting write operation on the outsourced data for clients using mobile devices. We consider the Ciphertext-Policy Attribute-based Encryption (CP-ABE) scheme as it is well suited to support access control in outsourced cloud environments. One shortcoming of CP-ABE is that users can modify the access policy specified by the data owner if write operations are incorporated in the scheme. We propose a protocol for collaborative processing of outsourced data that enables the authorized users to perform write operation without being able to alter the access policy specified by the data owner. Our scheme is accompanied with a light weight signature scheme and simple, inexpensive user revocation mechanism to make it suitable for processing on resource-constrained mobile devices. The implementation and detailed performance analysis of the scheme indicate the suitability of the proposed scheme for real mobile applications. Moreover, the security analysis demonstrates that the security properties of the system are not compromised.

Summary Low cost, decentralized architecture and ad hoc nature are a few desirable properties of wireless sensor networks that make them well suited for gathering sensitive information in hazardous deployment grounds. Existing security protocols exploit various cryptographic tools to strengthen their security. Not many works focus on constraints faced by an adversary. One such constraint being practical difficulties to trace a particular frequency band from a large range of unknown frequencies, specially in unharmonious geographical locations. Our research capitalizes on this weakness encountered by an adversary and preassigns nodes with multiple frequency bands from a wide range of frequencies allocated to the network. Deployed nodes can discover these bands during set network setup phase by a simple trick. Nodes are to internally switch their frequency bands depending on parametric variation that are caused by an (external) impulse. Experiments conducted using magneto optic sensors confirm that any variation of their parameter affects frequencies of emergent waves. Similar behavior is expected from application specific sensors. Frequency regulation (FR) concept is applied to combinatorial key predistribution schemes (KPS) having (regular) degreer. Depending onrand each node's capability to switch internal frequencies, nodes are preallocated withnfrequency bands. This naturally partitions the (distributed) network and results in improved resilience. Combining our FR concept to a KPS where the number of shared key between a pair of nodes is at most one (γ≤ 1) may yield best case scenario of an ideally resilient key predistribution. Our analysis of systems that combines FR idea with KPS whereγ > 1 leads to an optimized key‐band distribution argument and drastic resilience improvements. Results of simulations conducted assuming real‐life scenario ascertain our analysis and establishes superior performance of our protocols as compared to prominent ones.

We address two problems: first, we study a variant of block withholding (BWH) attack in Bitcoins and second, we propose solutions to prevent all existing types of BWH attacks in Bitcoins. We analyze the strategies of a selfish Bitcoin miner who in connivance with one pool attacks another pool and receives reward from the former mining pool for attacking the latter. We name this attack as “sponsored block withholding attack.” We present detailed quantitative analysis of the monetary incentive that a selfish miner can earn by adopting this strategy under different scenarios. We prove that under certain conditions, the attacker can maximize her revenue by adopting some strategies and by utilizing her computing power wisely. We also show that an attacker may use this strategy for attacking both the pools for earning higher amount of incentives. More importantly, we present a strategy that can effectively counter block withholding attack in any mining pool. First, we propose a generic scheme that uses cryptographic commitment schemes to counter BWH attack. Then, we suggest an alternative implementation of the same scheme using hash function. Our scheme protects a pool from rogue miners as well as rogue pool administrators. The scheme and its variant defend against BWH attack by making it impossible for the miners to distinguish between a partial proof of work and a complete proof of work. The scheme is so designed that the administrator cannot cheat on the entire pool. The scheme can be implemented by making minor changes to existing Bitcoin protocol. We also analyze the security of the scheme.

Recently, biometric authentication protocols are developed. Security of these protocols originates in compromising no privacy information by wiretapping, malicious access and etc. in the authentication processes. With regard to this, the authors pointed out the risk of excessive collection of privacy information caused by remaining data related to biometric authentication data such as logs and intermediate processing data on the authentication servers. As a requirement against this risk, the authors introduced receipt-freeness of biometric authentication protocols. In this research, the authors develop the above research by investigating so-called coercion-resistance which means resistance against coercing user into executing biometric authentication. This paper describes definition of coercion-resistance against wiretapping coercer, relevance to receipt-freeness, and analysis of coercion-resistance in two IC card based protocols. The results show one of the protocols satisfies receipt-freeness and coercion-resistance, although another one does not satisfy.

Cyberbullying is a underlying problem in social networking service, threatening users' mental and physical health. Previous research on automated cyberbullying detection is mostly textual or social based methods. Cyberbullying content is identified through a set of textual features within the content in the former method and through social information surrounding the content in the latter method. Those methods can not cater different cyberbullying standard for individual SNS user since each content is evaluated using same features. Therefore, in this article we propose a automated cyberbullying detection method that utilises the parent-child relationship between comments to capture the reaction from a third party to detect cyberbullying comments. We were able to improve the effectiveness of cyberbullying detection using only publicly available data.

Abstract Searchable encryption allows us to perform a keyword search over encrypted data. However, we cannot efficiently perform some complex search (e.g., a wildcard search) with traditional searchable encryption schemes because they can deal with only equality matches. Our symmetric searchable encryption can deal with partial matches. This allows us to efficiently perform a wildcard search, partial match search, and so on. We also examine the feasibility of our scheme by experiments on a smartphone and tablet, and confirm our scheme can be used in these environments. Availability on portable devices will offer high convenience. Copyright © 2013 John Wiley & Sons, Ltd.

Online games have become one of the most popular games in recent years. However, fraud such as real money trading and the use of game bot, has also increased accordingly. In order to maintain a balance in the virtual world, the operators of online games have taken a stern response to the players who conduct fraud. In this study, we have sorted out players' behaviors based on players' game playing time in order to support and find potentially illegal players in the MMORPG. In this paper, we added a topic model to the experiment and used k-means as a major tool to classify the players in the World of War craft Avatar History Dataset and find potentially illegal players.

Recently, several ownership protection schemes which combine encryption and secret sharing technology have been proposed. To reveal the original message, however, they exploited XOR operation which is similar to a one-time pad. It is fairly losing the reconstruction simplicity due to the human visual system (HVS). It should be noted that it is completely different from the original concept of visual cryptography proposed by Naor and Shamir. To decrypt the secret message, Naor and Shamir’s concept stacked k transparencies together. The operation solely does a visual OR of the shares rather than XOR, the way HVS does. In this paper, we, consequently, adopt Naor and Shamir’s concept to apply correct theory of visual cryptography. Furthermore, audio copyright protection schemes which exploit chaotic modulation or watermark integration into frequency components have been widely proposed. Nevertheless, security issue against intentional distortions has not been addressed yet. In this paper, we aim to construct a resilient audio ownership protection scheme to enhance the security by integrating the discrete wavelet transform and discrete cosine transform, visual cryptography, and digital timestamps. In the proposed scheme, the watermark does not require to be embedded within the original audio but is used to generate a secret image and a public image. The watermark is then acquired by performing OR between the secret and public image. We can alleviate the trade-off expenses between the capacity of data payload and two other important properties such as imperceptibility and robustness without modifying the original audio signals. The experiments against a variety of audio signals processing provided by StirMark confirm superior robustness of the proposed scheme. We also demonstrate the intentional distortion by modifying the original content via experiments, it reveals comparable reliability. The proposed scheme can be widely applied to the area of audio ownership protection.

ABSTRACT Document clustering is a practical and powerful data mining technique to analyze large amount of documents and large sets of text or hypertext documents. However, it also brings the problem of sensitive information leaking in disregard of privacy, especially when it is executed in distributed environment. In this paper, we propose a cryptography‐based framework to realize privacy‐preserving document clustering among the users under the distributed environment; there are two parties, each having his private document database, want to collaboratively execute agglomerative document clustering without disclosing their private contents. We provide two implementations of such a framework, one is with more precision and stronger security but requires more computational resources. The other is a simplified version with less computational complexity and achieves higher processing speed. Additionally, we provide the security proofs and experimental analysis of precision and scalability of our proposal. Copyright © 2013 John Wiley & Sons, Ltd.

In cognitive radio networks, primary user emulation (PUE) attack is a denial-of-service (DoS) attack on secondary users. It means that a malicious attacker sends primary-user-like signals to jam certain spectrum channels during the spectrum sensing period. Sensing the attacker's signal, the legitimate secondary user will regard these channels are used by the primary users, and give up using these attacked channels. In this paper, the interaction between the PUE attacker and the secondary user is modeled as a constant sum differential game which is called PUE attak game. The secondary user's objective is to find the optimal sensing strategy so as to maximize its overall channel usability, while the attacker's objective is to minimize the secondary user's overall channel usability. The Nash equilibrium solution of this PUE attack game is deprived, and the optimal anti-PUE attack strategy is obtained. Numerical results demonstrate the trajectories of the secondary user's optimal channel sensing strategies over time, and also shows that: by following the differential game solution, the secondary user can always optimize its channel usability when confronting PUE attacks.

Optical information media printed on paper use printing materials to absorb visible light. There is a two-dimensional code, which may be encrypted but also can possibly be copied. Hence, we envisage an information medium that cannot possibly be copied and thereby offers high security. At the surface, the normal two-dimensional code is printed. The inner layers consist of two-dimensional codes printed using a variety of materials, which absorb certain distinct wavelengths, to form a multilayered two-dimensional code. Information can be distributed among the two-dimensional codes forming the inner layers of the multiplex.

Nowadays, data collection and processing becomes ubiquitous in social and business areas, especially in Internet of Things. However, sensitive information leakage is a critical issue. To solve problem, privacy-preserving techniques are strongly needed. Jiang {\em et al.} proposed a protocol of finding frequent item in accountable computing (AC) framework which enables two parties to conduct collaborative computation on their transactional databases to find out the common frequent items without disclosing their private data to the other party. Their scheme was proposed in a secure two-party computation model against malicious adversaries. In this paper, we analyze the implementation details of AC-framework and identify some security weaknesses in their scheme. Furthermore, we clarify the security requirements for the AC-framework and present an augmented solution to enhance security.

The distributed system made the large-scale scientific computing possible in a cost effective way. And the hardware resources in such systems are also getting much cheaper than years before. However, the problem of executing the job using minimum resources is still reasonable and important, especially for the cloud environment, who has to save energy and control cost. Unfortunately, only a few existing scheduling algorithms have taken into account the resource usage issue. In this study, with considering the realistic network topology and communication model, we firstly propose the Deadline, Reliability, Resources-aware (DRR) scheduling algorithm. The theory analysis fully demonstrate that, the output schedule of our algorithm can satisfy the user's requirement on reliability and deadline. Through the experiments, with setting the deadline less than the make span of the MaxRe algorithm's output schedule, we find that our algorithm can complete the job under this deadline. Besides, our algorithm can save almost 50% computation resources and 70% communication resources than FTSA (bl) and FTSA (tl+bl) algorithms.

Sybil Attack means one node counterfeits multiple identities. It poses great threats to the routing of wireless ad hoc networks. Many existing solutions employ local detection method to capture misbehavior and then enhance the detection accuracy by information exchange. However, they ignore the rationality of member nodes. To save resource, rational nodes are reluctant to share information, therefore, how to guarantee reliable information exchange becomes a challenge issue. This paper presents a cooperative detection method against Sybil attack. Our method adopts the reputation mechanism which relies on the observation exchange to differentiate Sybil identities from legitimate ones. To promote the observation exchange, we present a cooperative detection game with initial condition, which helps nodes be aware that with which to share the observations can bring the maximum utilities. The theoretical and numerical analysis indicate that only benign and unselfish nodes can be accepted by their rational neighbors while Sybil nodes are excluded from the information exchange.

Wire-tap channel coding allows information-theoretically secure communication between legitimate sender and receiver in presence of an eavesdropper Eve, whose channel is subject to noise. A secrecy capacity for their communication is equal to capacity of the channel connecting them, minus capacity of Eve's channel, when the channels are assumed independent and affected by additive white Gaussian noise. In order to increase the secrecy capacity, we propose to employ a coding scheme using matched filter. The legitimate parties are assumed to share a pre-shared key of the matched filter, secretly from Eve. Hereby, the legitimate parties can use it to increase the capacity of their channel, while Eve cannot. We propose to apply this scheme to indoor wireless communication over IEEE 802.11 wireless LAN, analyze advantages of our construction and discuss an appropriate selection of coding scheme fitting the IEEE 802.11 protocol specification.

The objective of creating malicious software (i.e., malware), intruding computers and conducting malicious activities is shifted from showing off attacker's computer skills to earning money. Thus, recent attackers take more sophisticated and effective malware infection ways such as malware infection via malicious Web sites as well as the traditional exploitations like worm propagation. The malicious Web sites attempt to compromise machines by drive-by-download attack which redirects users to exploiting sites and install malware compulsorily in their machines by exploiting vulnerabilities of their Web browser or plugins. As a countermeasure for these malicious Web sites, blacklisting URLs or domains of them is significant. However, attackers tend to change the URLs or domains in a short period to avoid the blacklist. Thus, a blacklisting scheme which can filter even unknown malicious Web sites is critical. In this paper, we first analyze characteristics of malicious Web sites by their domain information such as AS (Autonomous System), IP address block, IP address, domain, and registrar. Second, we evaluate reputations of IP address blocks and registrars used by attackers. Then, we propose a blacklisting scheme constructed of the combination of IP address block and registrars with low reputation, that is, intensively used by attackers. From our experimental results, the Web sites with the same combination with low reputation appeared over long period, which indicates that our proposed blacklist has a certain capability of filtering unknown malicious Web sites.

To achieve security in wireless sensor networks (WSNs), key management is one of the most challenging issues in design of WSN due to resource-constrained sensor nodes. Various key management schemes (KMs) have been proposed to enable encryption and authentication in WSN for different application scenarios. According to different equirements, it is important to select the trustworthy KMs in a WSN for setting up a fully appropriate WSN mechanism. An Analytic Hierarchy Process (AHP)-aided method helping with the complex decision has been presented in our previous work. Our purpose in this paper is to do performance analysis of KMs in WSN using our previous AHP-aided method. We analyze the characters of abundance KMs intuitively. The following five performance criteria are considered: scalability, key connectivity, resilience, storage overhead and communication overhead. As all permutations of five performance criteria include 120 types' situations, experimental analyses on 43 KMs for the optimum selection are presented.

Abstract Trust research is a key issue in peer‐to‐peer (P2P) networks. Reputation‐based trust models as one of the good solutions to resolve the trust problems in P2P network are received more and more attention in recent years. One of the fundamental challenges is to capture the evolving nature of a trust relationship between peers and reflect the varied bias or preference of peers in a distributed and open environment. In this paper, we present a fine‐grained trust computation model for P2P networks. Our model defines the service as a fined‐grained quality‐of‐service (QoS) (N‐dimensional vector), and in order to accurate the recommendation trust computing, several concepts are introduced to reflect the recommenders' current status, history behavior, and the gap between these two behaviors. Also, we firstly introduce the Gauss‐bar function to measure the preference similarity between peers. All these will result in a flexible model which represents trust in a manner more close to human intuitions and satisfies the diverse QoS requirements of peers in P2P networks. The extensive simulations have confirmed the efficiency of our model. Copyright © 2009 John Wiley & Sons, Ltd.

With rapid development and increasing complexity of computer and communication systems and networks, traditional security technologies and measures cannot meet the demand for integrated and dynamic security solutions. Therefore, trusted computing and communications, as a significant challenging and innovative research field, is expected to resolve the security problems for traditional distributed services. During the past decades, a large amount of achievements have been published and applied extensively in various environments such as web documents, medical systems, telecommunications, and electronic commerce. The subject of trusted computing and communications has also attracted intensive research interests in academia, industry, military, and government. Trusted computing and communications aims to ensure the availability, security, reliability, controllability, and dependability for the distributed systems and networks. The research issues range from the traditional security (i.e., the identity trust) to the broader field of trusted computing (i.e., behavior trust) of systems and networks. In fact, trusted computing and communications has become one of the essential components of various distributed services, applications, and systems, which include ad hoc networks; peer-to-peer networks, social networks, semantic webs, e-commence, e-government; and pervasive, ubiquitous, and cyber-physical systems. The purpose of this special issue is to present a collection of high quality research papers that report the latest research achievements in wireless network security, trusted computing, data encryption, and key management. In this special issue, we selected 9 papers out of 29 total submissions, which demonstrate some novel works in this field. A detailed overview of the selected works is given below. The first paper, Enhanced Correlation Power Analysis Attack against Trusted Systems, presented a Hamming distance (HD) power analysis model which emulates HD based on probability distribution of Hamming weight. The proposed model reveals that the probability distribution of HD is well correlated with that of Hamming weight under certain rules, and thus the statistical correlation power analysis (CPA) between power and HD can be well mapped to the correlation between power and Hamming weight. Power analysis experiments demonstrated that the proposed models can jointly achieve better feasibility and accuracy. The second paper, Better Security Enforcement in Trusted Computing Enabled Heterogeneous Wireless Sensor Networks, proposed a heterogeneous architecture for wireless sensor networks (WSNs) by applying the high-end cluster heads equipped with trusted platform modules into clusters of the network. The proposed architecture, which enables the cluster heads to act as the online trusted parties with respect to security enforcement, can resolve the scalability problem inherent in the homogeneous WSNs and help to enforce the security in WSNs in a more effective manner. The third paper, A New Biometric Identity Based Encryption Scheme Secure against DoS Attacks, described a novel biometric identity based encryption (IBE) scheme and showed that the proposed scheme is immune from the DoS attacks by applying signature on the public value of the user. The proposed scheme enables the sender to detect whether the public value of the receiver is modified by an active adversary. Therefore, the proposed scheme is secure against DoS attacks and has better efficiency in terms of the key generation and decryption compared with the existing fuzzy IBE schemes. The fourth paper, Hybrid Pattern Matching for Trusted Intrusion Detection, presented a hybrid pattern matching engine: Field-programmable gate array (FPGA)-based and multicore-based pattern matching engine, which is optimized by the multithreading and novel clustered state coding techniques. The hybrid pattern matching engine can increase the reliability and trustworthiness of the intrusion detection system by working in parallel to improve detection accuracy and cross-examine to self-check integrity of the engine. In the fifth paper, TPM-Based Protection for Mobile Agents, the authors analyzed the problems in the agent protection and host protection, and presented a hardware-based mechanism for protecting the agents. The novel solution uses a trusted platform module (TPM) based protocol to realize its security. This paper provides a proof of concept by means of the "secure migration library for agents" to validate the proposed approach and demonstrates that the migration process of mobile agents is protected in the real attacks. In the sixth paper, A Fine-Grained Trust Model for P2P Networks, the authors presented a fine-grained trust computation model for P2P networks. The new model defines the service as a fine-grained quality-of-service (QoS) (N-dimensional vector) in order to ensure the accuracy of the recommendation in trusted computing. The authors first introduced several concepts to reflect the recommenders' current status, history behavior, and the gap between the two kinds of information, and then introduced the Gauss-bar function to measure the service preference similarity between peers, finally proposed a flexible and efficient model, which represents trust in a manner more close to human intuitions and effectively satisfies the diverse QoS requirements of peers in P2P networks. The seventh paper, A Challenge-Based Trust Establishment Protocol for Peer-to-Peer Networks, proposed a concrete challenge-based trust protocol for P2P networks, which uses challenge-response operations in each trust evaluation phase and validates every contacted peer while recording their corresponding trust value. The proposed scheme utilizes random selection of challenges without revealing any additional information, so the malicious peers have little opportunity to tamper with the P2P system. The eighth paper, Enhancing Identity Trust in Cryptographic Key Management Systems for Dynamic Environments, showed that both the key update and collusion avoidance problems are NP-complete, which needs to use the heuristic algorithms to prevent performance degradations encountered in the standard cryptographic key management system (CKM) schemes. Based on the analysis results, the authors presented a collusion detection and resolution algorithm. The time complexity of the algorithm is polynomial in the number of keys. The new algorithm operates by mapping the generated key set onto a key graph whose independent set is computed in polynomial time. The performance evaluation of the proposed algorithm indicates that the collusion prevention can be done dynamically without affecting the performance. The ninth paper, Secure Reputation Monitoring System – A Novel Connected Dominating Set-Based Framework for WSNs, proposed a connected dominating set (CDS) based reputation monitoring system, which is the first to employ a CDS-based monitoring backbone to securely aggregate the reputation of sensors. The proposed system enhances effectively the mobility and robustness for the certificate-less nodes without subjecting them to energy depletion or reputation pollution attacks encountered in the existing reputation monitoring systems. In conclusion, this special issue on trusted computing and communications gives insight into the recent research results in the broader security community. This special issue also provides certain guidelines for academic and industry advances, and these accomplishments are regarded as a basis toward future research directions, and vital commercial applications. This special issue has obtained help and instructions from all participants, so we would like to express our great appreciation to Prof. Hsiao-Hwa Chen, the Editor-in-Chief of this journal, for his suggestions and encouragements all through the stages, and to all anonymous reviewers who spent their precious time in reviewing the papers, and offering good advice or recommendations, which greatly helped us to select the best papers into this special issue. We also thank all authors who submitted their papers to this special issue. Finally, we hope you will find that the papers in this issue are useful.

In the existing studies on fault-tolerant scheduling, the active replication schema makes use of ε + 1 replicas for each task to tolerate E failures. However, in this paper, we show that it does not always lead to a higher reliability with more replicas. Besides, the more replicas implies more resource consumption and higher economic cost. To address this problem, with the target to satisfy the user's reliability requirement with minimum resources, this paper proposes a new fault tolerant scheduling algorithm: MaxRe. In the algorithm, we incorporate the reliability analysis into the active replication schema, and exploit a dynamic number of replicas for different tasks. Both the theoretical analysis and experiments prove that the MaxRe algorithm's schedule can certainly satisfy user's reliability requirements. And the MaxRe scheduling algorithm can achieve the corresponding reliability with at most 70% fewer resources than the FTSA algorithm.

In P2P systems, it is important to guarantee the efficiency and security of message routing between the source and the destination. Unfortunately, malicious attackers can easily insert a lot of nodes they controlled, and disturb the message routing between honest nodes. In order to counter such attacks, secure routing protocols which ensure successful message routing are needed. Furthermore, it is very important to analyze existing routing protocols for the inventions of secure routing protocols. In this paper, we propose a security model for evaluating security level of routing protocol. In this model, we define the concept of Regular Path, and use it as the indicator of security level. Then, we analyze three representative routing protocols based on proposed model to make comparisons from the aspects of security level and implement level.

We address secure secret key distribution in wireless communication systems. There is the secrecy capacity concept that it can distribute information which the third parties can not eavesdrop because of the noise over the distribution channel. Then, we address secure secret key distribution in wireless communication systems using secrecy capacity concept. Wireless channel is noisier compared with wired channel. Specifically, we investigate about wiretap channel coding that it can implement in the existing wireless LAN systems. We have investigated the coding parameters and the conditions that it can implement.

In this paper we compare four risk analysis methods: Mehari, Magerit, NIST800-30 and Microsoft's Security Management Guide. Mehari is a method for risk analysis and risk management developed by CLUSIF (Club de la Securite del' Information Francais). Magerit is a risk analysis and management methodology for information systems developed by CSAE (Consejo Superior de Administracion Electronica). NIST800-30 is a risk management guide for information technology systems recommended by the National Institute of Standard and Technology (NIST) in NIST Special Publication 800-30. Microsoftpsilas Security Management Guide is a security risk management guide developed by Microsoft. In this paper, we compare those methods based on two main criteria: the first criterion is the steps that are used by the methods to conduct the risk assessment, the second one is the contents of the methods and supplementary documents provided with them. We found that all methods follow the first three general steps of risk analysis. However, the Mehari method, the Magerit method and the Microsoft Security Management Guide do not include control recommendations. Control recommendations in these methods are proposed as the next step to security management (i.e. after risk analysis). All methods provide a detailed guide for risk analysis. However, only three methods - Mehari, Magerit and the one proposed in the Microsoft Security Management Guide-provide supplementary documents for risk assessment.

Intrusion detection system records worm's signature, and detects the attack that lurks in traffic based on it. However, to detect the worm that corrects, and changes some oneself, a highly accurate detection technique for distinguishing the code that seems to be the worm included in traffic is requested. In this paper, we pay attention to the Toth et al.'s method to extract the executable code included in the data flows on the network and detect the attack by measuring the length of them. Then, we describe the problem of their method and how to solve it.

Today, with increasing deversity of network technologies, people have been likely to be interested in anonymity. The attacker might threaten anonymity of senders and receivers by confirming linkability between their sessions. Recently, Golle et al. proposed the re-encryption scheme applicable to Mix, called universal re-encryption. In this scheme, a ciphertext is supposed to be re-encrypted without public information corresponding to it. Moreover, only a subject that re-enctypts a ciphertext can know the correspondence of original ciphertext and it, and the computational complexity to break the unlinkability property is equal to the semantic secrecy. In this paper, we consider and improve the universal re-encryption scheme, and propose a scheme that can verify who transmit the message by adding the property of signature.

The sensitive information leakage and security risk is a problem from which both individual and enterprise suffer in massive data collection and the information retrieval by the distrusted parties. In this paper, we focus on the privacy issue of data clustering and point out some security risks in the existing data mining algorithms. Associated with cryptographic techniques, we initiate an application of random data perturbation (RDP) which has been widely used for preserving the privacy of individual records in statistical database for the distributed data clustering scheme. Our scheme applies linear transformation of Gaussian distribution perturbed data and general additional data perturbation (GADP) schemes to preserve the privacy for distributed kernel density estimation with the help of any trusted third party. We also show that our scheme is more secure against the random matrix-based filtering attack which is based on analysis of the distribution of the eigenvalues by using two RDP methods.

Mailing lists are used for information exchange in specific groups. However, in the recent times, the number of spam mails received has increased, and considerable amount of time is wasted in filtering spam mails. Spam filtering techniques are widely used tool, however, they produce false positive and false negative results. We propose a system to block spam mails in a mailing list. In our system, we assign different posting addresses to different mailing list members. A mailing list member sends a mail to the mail address assigned to him for sending a mail to the mailing list. When a spam mail is received, the address that is the cause of the spam mail is identified and invalidated, and a new address is assigned to the member. Thus, we can block spam mails from the invalidated address. Furthermore, our system is highly compatible with current mail systems because our system does not require any particular software to be installed in the client machines.

The main focus of current research in trusted operating systems (TOS) is on the enhanced access control of reference monitors which, in turn, control the individual operations on a given access instance. However, many real-life runtime attacks involve behavioral semantics. We have proposed an extended reference monitor to support both access and behavior controls. This results in a sequence of operations which are also of concern in security enforcement. This paper presents a policy language for the extended reference monitor. Our policy language is based on domain and type enforcement (DTE) and role-based access control (RBAC). Permission is defined as an event and a state of behavior is represented as a fluent to be accorded with the convention of event calculus (EC). Behavior policies can be expressed with the EC style syntax as well as access control policies

Attacks against data in memory are one of the most serious threats these days. Although many detection systems have been proposed so far, most of them can detect only part of alteration. Some detection systems use canaries to detect alteration. However, if an execution code has bugs that enable attackers to read data in memory, the system could be bypassed by attackers who can guess canaries. To overcome the problems, we propose a system using alteration of data. Our proposed system detects illegal alteration with verifier for vulnerable data. Verifier is made before vulnerable data could be altered by attackers, and verifier is checked when the program uses the vulnerable data. Part of verifier is stored in kernel area to prevent attackers from reading data in user memory. Our approach can detect illegal alteration of arbitrary data in user memory. Our proposed system, moreover, does not have the problem systems using canaries have.

No abstract available.

With the multiplication of attacks against computer networks, system administrators need to monitor carefully the networks they manage. However, that monitoring task is made harder because of the increasing amount of data to process. Conventional automated tools provide limited support and most of the time require high skilled operators. Recently, tools using visualization techniques started to be proposed to resolve those issues. In this paper we introduce an original visualization design which combine 3D and 2D representations of the network traffic and activity. Both representations are based on the same interactive grid representation of the network space and are linked together as they provide complementary functionalities.The 3D representation provides an overview of the communications between several network zones and the 2D representation provides a detailed view of selected parts of the 3D one. A prototype was built according to the proposed visualization design.

A home-network is expected to spread now. We considered the security issues on home networks based on power line communication, because these topics have not been sufficiently considered. We discuss the issues, risk and required countermeasures. These issues are categorized into control network, information network, AV network and community network. We also discuss differences on the security between the power line communication and wired-LAN or wireless-LAN.

An RFID tag is a small and cheap device which is combined in IC chip and an antenna for radio communications. The tag is used for management of goods and its distribution. Moreover it reduces the cost of managements of goods. However, an RFID system has some security problems. Juels proposed a "yoking-proof" which guarantees the existence of two tags (Juels, 2004). But we point out that this scheme is not secure against a replay attack. In this paper, we propose a scheme which deals with the problem by using time stamp. Moreover, we propose a scheme which guarantees the existence of a group of RFID tags.

To exchange an important information through the Internet, an authenticated key exchange is required. In this paper, we consider the following attacks as the problems of an authenticated key exchange using shared secret: eavesdropping on identity, DoS attack, replay attack, and impersonation. Besides prevention from all these attacks, efficient key exchange should be realized. In this paper, we propose an authenticated key exchange system based on Diffie-Hellman key exchange with one-time ID, which can be used only once.

The public key infrastructure (PKI) technology is very important to support secure global electronic commerce and digital communications on networks. In electronic commerce, different PKIs need to be interoperated. Especially, they need to be merged for merger and acquisition of companies. We take a different approach from cross-certification techniques toward merging different PKIs. Our method is to merge the multiple CAs into one. By using our method, the trust model with an efficient path processing can be built in comparison with the traditional merging methods. Then we formalize merging processes and discuss the certification path processing and the operational cost.

The paper proposes ways to counter the cyber terrorist (CT) advantages of surprise and anonymity. It recommends the creation of a Cyberint Analysis Center to develop and evaluate methods to improve the ability to detect, identify and deter cyber terrorist attacks. It also proposes ways to implement responsible, accountable and identifiable use of the Internet, and deny anonymity to the attackers.

We show that the advanced version of the randomized addition-subtraction chains countermeasure against side channel attacks is vulnerable to a multiple power analysis attack, a new kind of side channel attack, under distinguishability between addition and doubling. The side channel attack takes advantage of information leaked during execution of a cryptographic procedure. The randomized addition-subtraction chains countermeasure was proposed by E. Oswald and M. Aigner (see Lect. Notes in Comp. Sci., vol.2162, p.39-50, 2001), and is based on a random decision inserted into computations. The countermeasure has two versions; the basic version and the advanced version. The basic version has been proved to be vulnerable to a side channel attack. This is due to a shrinkage of states for randomization if a bit of the secret scalar is zero. However, the advanced version does not have such a shrinkage. The multiple power analysis uses plural AD sequences, which are sequences of additions and doublings, and obtained by the distinguishability and measurements. The multiple power analysis relates the AD sequences to each other, and deduces the secret scalar. A point of the multiple power analysis against the advanced version is that two different states are combined, and regarded as the same state. This provides a shrinkage of states if a bit of the secret scalar is zero.

Article On zero-knowledge proofs (extended abstract): "from membership to decision" Share on Authors: Giovanni Di Crescenzo Telcordia Technologies Inc., 445 South Street, Morristown, NJ Telcordia Technologies Inc., 445 South Street, Morristown, NJView Profile , Kouichi Sakurai Dept. of Computer Science, Kyushu University, Fukuoka 812-8581, Japan Dept. of Computer Science, Kyushu University, Fukuoka 812-8581, JapanView Profile , Moti Yung CertCo, New York, NY CertCo, New York, NYView Profile Authors Info & Claims STOC '00: Proceedings of the thirty-second annual ACM symposium on Theory of computingMay 2000 Pages 255–264https://doi.org/10.1145/335305.335336Online:01 May 2000Publication History 3citation509DownloadsMetricsTotal Citations3Total Downloads509Last 12 Months8Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access