De-anonymization attacks in blockchains are significant concerns as they compromise the privacy of users on a public ledger. Such attacks, in the form of network analysis and transaction patterns, aim to link a blockchain address to the identity of its owner, potentially revealing sensitive information. Though researchers introduce various solutions using Tor, VPN, and i2P to protect against de-anonymization in blockchains, they have certain limitations: i) non-verification of the private transactions, ii) reveal of the transaction graph, and iii) requirement of a trusted setup that is itself vulnerable to the adversary. All these lead to the revocation of de-anonymization problems. In this paper, we show a novel privacy assurance framework for blockchains. The proposed framework is called De-Anonymization Withstanding Solution (DAWS). DAWS is the first privacy-preserved blockchain framework against de-anonymization attacks. DAWS uses privacy-classifying smart contract execution and a novel consensus called Proof-of-Privacy (PoPri). A set of experiments is executed on PoPri as well as DAWS. The blockchain transactions are modified by including user-defined privacy labels. DAWS can handle attacker advantage ≥0.008 with a privacy breach probability < 0.01% under our threat model. Besides, an improvement in the throughput of DAWS is noticed as compared to Ethereum (almost 80 times) with the Hyperledger configuration for consensus. The gas consumption improvement is 20%. All the listed features enhance the appeal of the proposed DAWS as a robust privacy-preserving solution against blockchain de-anonymization attacks.

Medical Internet of Things (MIoT) is a rapidly growing field that promises to revolutionize health care. The ability to connect devices and collect data from them has the potential to transform the way it monitors and treat patients. However, the security and privacy of this data is a major concern. The cryptography and other conventional methods for security in resource constrained MIoT has several shortcomings. First, it does not provide adequate protection for patient data. Second, it is not designed to work with the large number of devices and huge volumes of data that are typically generated in MIoT applications. In this article, secure M-Trust privacy protocol (SMP) has been designed to address these issues. The SMP protocol uses a combination of trust, cryptographic, and machine learning techniques to provide security and privacy for data in transit. The SMP protocol has been designed to work with the smart health care monitoring system to provide a secure and private communication channel between devices in the system. The SMP protocol is an improvement over the existing security and privacy protocols for medical data. The simulation results proves that the SMP protocol is more efficient and scalable than the existing protocols. The SMP protocol is a valuable addition to the MIoT landscape and can help improve the privacy of data exchanged between medical devices.

The decentralization and transparency have provided wide acceptance of blockchain technology in various sectors through numerous applications. The claimed security services by blockchain have been proved using various cryptographic techniques, mainly public key infrastructure and digital signatures. However, the use of generic cryptographic primitives using large prime numbers or elliptic curves with logarithms is going to be an issue with quantum computers as those techniques are vulnerable in post-quantum era. Therefore, the paradigm shift from pre-quantum to the post-quantum era has necessitated new cryptographic developments which are robust against quantum attacks and applicable in blockchain for post-quantum decentralization. Therefore, we have presented a solution for post-quantum decentralization in the blockchain. It uses lattices with polynomials for identity-based encryption (IBE) and aggregate signatures for the consensus to ensure efficiency and suitability in post-quantum blockchain applications. We experiment the proposed approach based on delay, throughput, energy consumption and complexity. The comparative results prove that the presented work is efficient.

Internet of Things (IoT) composed of large number of sensing devices with a variety of features applicable for various applications. In such scenarios, due to low data handling capabilities, limited storage, and security aspects, it is quite challenging to protect networks against illegal information access and utilizes storage efficiently. Though researchers provide various solutions for security and data storage, but a few solutions are appropriate for wireless sensor networks (WSNs)-enabled IoTs. Therefore, a blockchain-based decentralized framework integrated with authentication and privacy-preserving schemes is developed for the secure communication in WSNs-enabled IoTs. Registration, certification, and revocation process are employed for the communication with sensor nodes and base station (BS) in a cloud computing environment. In this scheme cluster heads forward the collected information to the BS. Consequently, BS records all the key parameters on the distributed blockchain and large data is forwarded to clouds for the storage. The revoked certificates of all malicious nodes are eliminated from blockchain by BS. The performance of the proposed scheme is scrutinized in terms of detection accuracy, certification delay, computational, and communicational overheads. The simulated results, comparative analysis, and security validation support the superiority of the proposed solution over the existing approaches.

The pandemic/epidemic of COVID-19 has affected people worldwide. A huge number of lives succumbed to death due to the sudden outbreak of this corona virus infection. The specified symptoms of COVID-19 detection are very common like normal flu; asymptomatic version of COVID-19 has become a critical issue. Therefore, as a precautionary measurement, the oxygen level needs to be monitored by every individual if no other critical condition is found. It is not the only parameter for COVID-19 detection but, as per the suggestions by different medical organizations such as the World Health Organization, it is better to use oximeter to monitor the oxygen level in probable patients as a precaution. People are using the oximeters personally; however, not having any clue or guidance regarding the measurements obtained. Therefore, in this article, we have shown a framework of oxygen level monitoring and severity calculation and probabilistic decision of being a COVID-19 patient. This framework is also able to maintain the privacy of patient information and uses probabilistic classification to measure the severity. Results are measured based on latency of blockchain creation and overall response, throughput, detection, and severity accuracy. The analysis finds the solution efficient and significant in the Internet of Things framework for the present health hazard in our world.

The integration between blockchains, Internet-of-Thing (IoT), and smart contracts is an emerging and promising technology. The advantages of this technology have raised the importance of Industrial Internet-of-Thing (IIoT) and have paved the pathway for “Industry 4.0.” Surprisingly, access control has received less attention in IIoTs. Though there are some solutions coming forward to use blockchains for IIoT to enable secure and resilient access control management, the challenge is to satisfy the low-latency requirements of IIoTs for validating and adding the blocks to the chain. Besides, role-based and rule-based access controls in the existing systems can be forged without organizational access controls and compliance. Therefore, we address these problems in this article. In the present work, we proposeDHACS, aDecentralized Hybrid Access Control for Smart contract, for IIoTs. DHACS aims to provide transparency, reliability, and robustness to the existing access control mechanism in IIoTs. The framework is based on blockchain feasibilities that contribute to an interconnected hybrid access control through smart contract provision. It is a novel idea in the domain of IIoTs. We use three access control strategies, role-based, rule-based, and organization-based, to develop a hybrid approach for smart contract in DHACS. The operational transactions along with their access controls are accounted and blocks are made by the transaction pooler and block creator. We use a private blockchain environment; however, it can be extended to a public blockchain or consortium blockchain for geographical distributed dependency. We compare DHACS with three existing approaches in recent time. We measure the performance in terms of computational costs, storage complexity, and energy consumption. DHACS outperforms the others approaches and is considered to be efficient for IIoT applications with more than 30% better efficiency in access control management. To the best of our knowledge, DHACS is the first attempt to use decentralized blockchains with smart contract for hybrid access control in IIoTs.

The papers in this special section focus on data analytics for public health care. Growing and intensive attention for the use of data analytics in healthcare due to its proven benefits to gain insights on the macro and micro depths to support decisionmaking at the patient, clinical, bench side and business levels. Health data analytics contributed to the improvements to patient care, faster and more accurate diagnoses, preventive measures, more personalized treatment, narrow the gap between bedside and bench side and provide more informed decision-making. However, the recent pandemic of COVID-19 draw the world attention to need to extend the power of data analytics beyond the legacy data channels including Electronic Health Records (EHRs) and Patient Portals. Data analytics can assist population health management in improving patient outcomes, enhancing care management, and address social determinants of health. As the population health analytics continues to grow in the healthcare space, healthcare systems must be able to gather data from multiple sources, apply variety of data analytics (e.g., Descriptive Analytics, Predictive Analytics Prescriptive Analytics), and manage the provide insights for the population.

Regardless of whether we are living in smart cities or not smart cities, the technologies involved in organizing and planning for smart transportation systems are already in use including smart sensors, controlled actuators, and other sensing and action devices along with massive information collected on logistics, routing, vehicles, passengers, mapping, and planning. The use of these technologies and many other associative technologies including smart connected vehicles and traffic forecasting systems are contributing to the development of a sustainable transport system that can have minimal incidents. However, these technologies did not solve most of the traffic congestions nor be able to use a mobility single interface to plan trips as well as to integrate more smart algorithms for efficient traffic management.

Abstract Social computing is a disruptive technology that is changing how we do business and building the enterprises. Mining consumer insights and consumer segmentation are the new drivers that are likely to be the cornerstone of developing new service innovations and social interactions. This special issue was designed to stimulate research on the data mining tools and methods for social computing. In this editorial, we are outlining the broad research framework on social computing, including the papers in this special issue and areas for future research.

As blockchain technology is becoming a driving force in the global economy, it is also gaining critical acclaim in the e-commerce industry. Both the blockchain and e-commerce are inseparable as they involve transactions. Blockchain protect transactions and e-commerce activities rely on them. Blockchain technology enables a decentralized marketplace to support important business activities like secure payments, managing the supply chain and reducing the fraud to mention few. In this special issue editorial we are introducing 11 research articles in this hot area of research that were selected by our reviewers from over than 250 submissions. As blockchain technology is becoming a driving force in the global economy, it is also gaining critical acclaim in the e-commerce industry. Both the blockchain and e-commerce are inseparable as they involve transactions. Blockchain protect transactions and e-commerce activities rely on them. Blockchain technology enables a decentralized marketplace to support important business activities like secure payments, managing the supply chain and reducing the fraud to mention few. In this special issue editorial we are introducing 11 research articles in this hot area of research that were selected by our reviewers from over than 250 submissions.

Interconnection and intercommunication between people, processes, and things have been enhanced with the development of the Internet of Things (IoT) and extended with fog computing for better efficiency. Fog computing improves the network services and circumvents the problem of escalated data management as an interface between cloud and terminal with the requirement of secure data transmission. In this article, a novel security framework is designed for fog computing intended for improving the security of IoT. This framework uses single point of aggregation from fog interface and lattice cryptographic approach to establish the security for the services. Azure cloud platform and Sage lattice cryptographic base have been employed to evaluate the performance of the framework. It is noticed that the Level 1-Level 2 (L1-L2) cache implementation in the system significantly improves the efficiency of the framework. The results show that the proposed framework is robust in preventing attacks on fog nodes and additionally provides an advantage for low communication overhead.

Blackboxes are being increasingly used in the vehicular context to store and transmit information related to safety, security and many other applications. The plethora of sensors available at the different parts of the vehicle can provide enriched gathering of the data related to these applications. Nonetheless, to support multiple use cases, the blackbox must be accessible by various actors (e.g. vehicle owner, insurance company, law enforcement authorities). This raises significant challenges regarding the privacy of the data collected and stored in the blackbox. In fact, these data can often lead to tracing back accurate facts about the behaviour of the owner of the vehicle. To cope with this problem, we propose a new blackbox architecture supporting searchable encryption. This feature allows multiple users who are not able to decipher the content of the blackbox to validate properties such as path traceback and velocity. To illustrate the implementation of the proposed technique in practice, we discuss a case study related to post-accident processing by insurance companies.

Over the last few years, the rapid development of smart grids and the deployment of smart metering infrastructures on a much larger scale have raised a crucial privacy concern related to the collection of real-time energy consumption data. For these purpose, data aggregation is a widely used technique for privacy preservation. Securing the data aggregation process is a challenge since smart grids are susceptible to many cyber security threats and attacks. Therefore, several approaches have been proposed to address this issue. However, many of them are vulnerable to various types of attacks and suffer from high communication and computation costs in addition to the use of complex key management schemes. To overcome this problem, we propose a secure and privacy-preserving data aggregation scheme based on homomorphic encryption. In this solution, we take advantage of the opportunities offered by ECEL-Gamal and its homomorphic property as well as the ECDSA and ECDHE algorithms to use them in order to aggregate privacy-preserving data. Through detailed analyses, we show that our proposed scheme can meet various security requirements and preserves user privacy. In addition, experiment results demonstrate that our scheme is more efficient than existing competing approaches in terms of communication and computation overhead.

Various research efforts have focused on the problem of customer privacy protection in the smart grid arising from the large deployment of smart energy meters. In fact, the deployed smart meters distribute accurate profiles of home energy use, which can reflect the consumers' behaviour. This paper proposes a privacy-preserving lattice-based homomorphic aggregation scheme. In this approach, the smart household appliances perform the data aggregation while the smart meter works as relay node. Its role is to authenticate the exchanged messages between the home area network appliances and the related gateway. Security analysis show that our scheme guarantees consumer privacy and messages confidentiality and integrity in addition to its robustness against several attacks. Experimental results demonstrate the efficiency of our proposed approach in terms of communication complexity.

In this paper, we discussed an efficient statistical method with proof-of-work consensus approach for cloud and fog computing. With this method, solution with precise probability in minimal time is realized. We have used the expectation maximization algorithm and polynomial matrix factorization. The advantages of this statistical method are the less iteration to converge to the consensus solution and easiness to configure the complete mathematical model as per the requirement. Moreover, the energy and memory consumption are also less which make this approach appealing for cloud and fog computing. The experimental results also show that the proposed approach is significantly efficient in terms of time and memory consumption. This novel approach seems beneficial for Internet-of-Things (IoT), one of the most fast-growing technologies in network computing.

The development of digital media, the increasing use of social networks, the easier access to modern technological devices, is perturbing thousands of people in their public and private lives. People love posting their personal news without consider the risks involved. Privacy has never been more important. Privacy enhancing technologies research have attracted considerable international attention after the recent news against users personal data protection in social media websites like Facebook. It has been demonstrated that even when using an anonymous communication system, it is possible to reveal user’s identities through intersection attacks or traffic analysis attacks. Combining a traffic analysis attack with Analysis Social Networks (SNA) techniques, an adversary can be able to obtain important data from the whole network, topological network structure, subset of social data, revealing communities and its interactions. The aim of this work is to demonstrate how intersection attacks can disclose structural properties and significant details from an anonymous social network composed of a university community.

Wireless Body Area Networks (WBANs), are becoming more and more popular. They are taking a significant proportion of the E-health market. WBANs rely on medical sensors, such as electrocardiography (ECG) and blood glucose, to continuously monitor the patient's physiological parameters. These signals are then forwarded, via a network infrastructure, to an analysis center. Despite their large deployment, security issues, mainly related to data privacy, are often considered as potential obstacles that might limit the extent of such solutions. This paper introduces a new approach to cope with data privacy in WBANs. Our major contribution is two-fold: (1) to reduce a noise and obtain correct data by improving Kalman filter; and (2) to propose a new secure privacy-preserving model based on homomorphic properties and chaotic cryptosystems. The proposed model conserves a real-time analytics for monitoring healthcare and preserves data confidentiality, data privacy, and data integrity.

With the proliferation of sophisticated attacks against communication and information systems, existing protection mechanisms are becoming inefficient to guarantee an acceptable security level. Hence, new security techniques are being developed to keep up with the evolution of threats and exploits. One of the security issues that is being investigated by the research community is per-packet authentication, where security mechanisms should be implemented to enforce the authentication of a specific network flow. This paper mainly focuses on the use of biometric techniques since they offer a promising potential to enforce per-packet authentication policies in highly dynamic contexts. We provide a review of how biometrics have been proposed in the literature as an alternative to purely cryptographic mechanisms for per-packet authentication. The drawbacks of the existing are pointed out and discussed. We finally explore the research niches that will shape the evolution of this field in the near future.

The main goal of the Internet of Things (IoT) in supply chains is to provide accurate and real-time tracking of items. But, in modern business management, new perspectives are opened and new tasks are invented. In this network involving a myriad of businesses and relationships, the supply chain management (SCM) process should assure global interoperability between trading entities and partners. The traditional technologies are still unable to offer a cost efficient and trusted system for information sharing and provenance recording between these entities and partners having different clearance and priorities. Therefore, security and scalability become an important consideration for the design of supply chain architecture (SCA). In 1979, Ralph Merkle has proposed the Merkle tree which is a key management scheme based on tree architecture. In this paper, we present a secured distributed supply chain architecture based on Merkle tree. The proposed design aims at replacing the current Peer to Peer architecture using a scalable and secure key management scheme.

Nowadays, the evolving threats of terrorist and criminal attacks against public places have urged the need for active video surveillance systems. Such systems rely on video analytics modules that identify and pre-alarm abnormal events occurring in sensed visual scenes in real-time. By implementing these smart features in the digital cameras, the design of distributed and adaptive physical security policies is made possible. Yet, within these systems, data security and privacy are a major concern. In this paper, we introduce a video surveillance system whose architecture is based on the IoT model. The device layer of this architecture includes smart cameras that communicate in machine-to-machine (M2M) manner. Then, we propose a tunneling framework that ensures the security of the M2M communications. The novelty of this framework is that it uses a shared secret in order to generate a cipher key and the video sensor fingerprints as the main authentication parameter. The security evaluation of our framework has also shown its resistance to well known attacks.

The emergence of the Social Internet of Things (SIoT) paradigm brought new opportunities in terms of service provisioning and collaboration in distributed Internet of Things environments. However, while augmenting smart devices with more autonomy, this trend deepened the privacy hole of the Internet of Things (IoT). As a mitigation, we propose in this paper a SIoT profile matching framework allowing collaboration between devices interested in the same services. The services to be included in the SIoT profile are selected by the owner of the IoT devices. The profile is then published in a privacy preserving fashion. Since trust is critical in social networks, we propose a trust model fitting with the distributed nature of IoT interactions. This trust model is based on the decentralized trustless Blockchain concept. Security analysis and performance evaluation of our scheme showed a promising tradeoff between security and efficiency.

Most of the traditional approaches for gathering data in the information sharing platforms of manufacturing supply chains are outdated and can negatively impact the speed of real-time sharing of information. In this technology-driven world, the supply chain management operations based on the Internet of Things (IoT) are bringing day after day a great business potential. Therefore, connecting physical objects together in support of intelligent decision making, consists an enabler of real-time quality management and control in the supply chain. The connected objects should meet market demands correctly, rapidly, and profitably. The supply chains should maintain and sustain technology-based and quality-driven capabilities in order to decrease network wide costs, reduce lead duration and transit duration and improve user experience. This work tackles the implications of the roll-out of the internet of things in supply chain management tasks. We focus on the quality of experience and the quality assurance arising from data consumption as a result of connecting objects to the Internet and how this can be translated into traces and evidences for some selected properties. The proposed model will be illustrated with a test scenario to verify the selected requirements.

Advanced Encryption Standard (AES) is a standard algorithm for block ciphers for providing security services. A number of variations of this algorithm are available in network security domain. In spite of the strong security features, this algorithm has been recently broken down by the cryptanalysis processes. Therefore, it is required to improve the security strength of this algorithm as AES is popular in commercial use. In this paper, we have shown the reasons of the loopholes in AES and also have provided a solution by using our Symmetric Random Function Generator (SRFG). The use of randomness in the key generation process in block cipher is novel in this domain. We have also compared our results with the original AES based upon some parameters such as nonlinearity, resiliency, balancedness, propagation characteristics, and immunity. The results show that our proposed version of AES is better in withstanding attacks.

An advance multiresolution wavelet based approach for wideband spectrum sensing for cognitive radio system is proposed in this paper. Prime focus is made on the coarse detection part for interweaved system, in which unoccupied spectrum can be used efficiently by the cognitive users. Quick and immediate shifting over the sensed vacant channel is extremely vital and is a challenging task. To overcome this issue, fast and efficient spectrum sensing technique is proposed for cognitive radios by improvising the Discrete Wavelet Packet Transform (DWPT) for multiresolution interweaved systems. This proposed scheme not only increases the system speed but also reduces complexity. Simulation results are used to analyse the system performance and numerical analysis for computing system complexity.

Cloud computing is an emerging economic model that provides a broad network access to services with many benefits to many tenants at the same time. Although it creates a large potential to develop new online services the evolution of cloud computing has been accompanied by the proliferation of various attacks against the services on the cloud infrastructures. The importance of risk management in cloud computing is mainly motivated by the dynamic context in which the services and applications are implemented. In fact, the intrinsic characteristics of cloud infrastructures prevent the use of previously developed process of traditional frameworks. The goal of this paper is to present a new risk management framework for better considering context parameters of cloud computing environment. An example is considered in which the risk treatment process in this framework proposes how to dynamically balance between the security and performance degradation due to the implementation of security mechanism.

Cloud computing has the benefit of offering scalability and efficiency, as well as cost-effectiveness. However, the existence of security breaches exacerbates the reluctance of potential users to host their sensitive data and services on the cloud. Indeed, the intrinsic characteristics of cloud infrastructures prevent the use of traditional security policy engineering frameworks. The dynamic context in which services and applications are implemented on the cloud does not support previously developed security risk management process. This paper proposes a novel game-theoretic model that models the trade-off between the effectiveness of the adaptive risk treatment and the cost resulting from the execution of the selected security mechanisms. The objective is to implement dynamic security policies that adapt to the dynamic nature of the cloud.

Radio frequency identification (RFID) technology is paramount for the automation and optimization of supply-chain activities. RFID tags can drastically improve the efficiency of inventory management, especially in the pharmacy supply chain. Thus, the drugs tracking can be enhanced in the pharmaceutical manufacturing plants all across the world paving the way for the wide deployment of the Internet of Things (IoT). The connected things in manufacturing processes have gained prominence owing to the growing number of unqualified pharmacies and counterfeit drugs. These sensors continuously generate a large amount of contextual information like locations and time points so as to control and manage drugs quality and distribution. Based on these contextual information, business logic can be implemented efficiently. Collection, modeling, reasoning, and distribution of context in relation to sensor data plays a critical role. In this paper, we propose a context-aware middleware for RFID based pharmacy supply chain, which aims to offer a deeper intelligence for the objects monitoring. A variant of Fosstrack middleware was proposed to offer a deeper intelligence in the RFID based supply chain.

The evolution of cloud gaming systems is substantially the security requirements for computer games. Although online game development often utilizes artificial intelligence and human computer interaction, game developers and providers often do not pay much attention to security techniques. In cloud gaming, location-based games are augmented reality games which take the original principals of the game and applies them to the real world. In other terms, it uses the real world to impact the game experience. Because the execution of such games is distributed in cloud computing, users cannot be certain where their input and output data are managed. This introduces the possibility to input incorrect data in the exchange between the gamer's terminal and the gaming platform. In this context, we propose a new gaming concept for augmented reality and location-based games in order to solve the aforementioned cheating scenario problem. The merit of our approach is to establish an accurate and verifiable proof that the gamer reached the goal or found the target. The major novelty in our method is that it allows the gamer to submit an authenticated proof related to the game result without altering the privacy of positioning data.

Cloud gaming addresses multiple challenges related to the constraints on the resources of the players computer as well as the compatibility between the online game platform and the computers. The abundant CPU, memory and storage resources available in the cloud infrastructures enable new interaction schemes between the game and the player. For instance, through the development of new video coding strategies, the user experience can be improved, especially in the case where the access to the game is made through resource-impoverished mobile terminals. The objective of this paper is to introduce a new video coding strategy for cloud gaming. The proposed strategy takes into consideration the QoS parameters and the energy-consumption of the decoder. This allows balancing the graphic quality to the lifetime of the mobile terminal. Our strategy combines the use of the Kalman filter and the Adaptive Control Feedback Control Loop. This allows the implementation of interpolation and prediction mapping functionalities in order to compensate the loss of significant information from several frames. Through an experimental comparison of our scheme with respect to the most popular cloud gaming techniques, we show that we improve the trade-off between QoS parameters (i.e., processing delay, network bandwidth) and the lifetime of the mobile terminals.

Cloud computing is a paradigm that is redrawing the information technology landscape by outsourcing the computation and data storage services to public cloud service providers. Over the last years, cloud storage services revealed an unprecedented opportunity for Internet users to profit from online storage services. Thanks to their enriched toolbox for file sharing and syncing, cloud storage platforms provide organizations and individuals with a reliable and cost-effective collaborative workspace. However, in addition to the traditional security issues, cloud storage services introduce new security concerns that are mainly related to the insecure state in which the files are while being synchronized. Recent publications highlighted the significant impact of the security flaws that exist in the syncing protocols used by the most popular cloud storage application. In this paper, we consider the Man in the Cloud (MitC) attack demonstrated in 2015 which allows accessing the files stored in a private repository without the possession of the authentication and authorization credentials. To address this issue, we propose a biometric-based framework for cloud storage services aiming to impede intruders from launching MitC attacks. Our framework is based on our previously published technique to combine chaotic maps and fuzzy extractors. The experiments performed on real biometric features confirm the potential brought by our framework to implement strong authentication in cloud storage applications.

The Internet of Things is a disruptive paradigm based on the cooperation of a plethora of heterogeneous smart things to collect, transmit, and analyze data from the ambient environment. To this end, many monitored variables are combined by a data analysis module in order to implement efficient context-aware decision mechanisms. To ensure resource efficiency, aggregation is a long established solution, however it is applicable only in the case of one sensed variable. We extend the use of aggregation to the complex context of IoT by proposing a novel approach for secure cooperation of smart things while granting confidentiality and integrity. Traditional solutions for data concealment in resource constrained devices rely on hop-by-hop or end-to-end encryption, which are shown to be inefficient in our context. We use a more sophisticated scheme relying on homomorphic encryption which is not compromise resilient. We combine fully additive encryption with fully additive secret sharing to fulfill the required properties. Thorough security analysis and performance evaluation show a viable tradeoff between security and efficiency for our scheme.

The Internet of Things (IoT) is one of the revolutionary technologies for healthcare. However, this flourishing still faces too many challenges including security and privacy preservation information. To address these problems, our contribution is to present a scenario of diabetes disease assume a matching between the situation of the patient and the relevant data from monitoring point view. This scenario describes how a patient can collect enormous of vital sign and activity. Wireless Body Sensor Networks (WBSN) is one of the IoT building blocks in which a patient can be monitored using a collection of sensor nodes to improve the patients quality of life. This technology in healthcare applications should not ignore security requirements. The aim of this paper is, (1) to design a healthcare architecture for a patient monitoring system, and (2) to explore the major security requirements in WBSN.

Recent technological advances have given rise to the popularity and success of cloud. This new paradigm is gaining an expanding interest, since it provides cost efficient architectures that support the transmission, storage, and intensive computing of data. However, the prospect of outsourcing an increasing amount of data storage and management, the abstract nature of the cloud and the diversity of the delivered services increase their vulnerability to security incidents and attacks. The objective of this paper is to provide a comprehensive review of the existing security requirements in cloud storage environments. In addition, it explores ID-based Cryptography power to address the protection of cloud storage infrastructures. As a main contribution, a new authentication scheme for Cloud-based Storage applications is proposed.

Due to the characteristics of resource-constrained in wireless sensor networks (WSNs), energy consumption is a major concern. Data aggregation is an important method to reduce the energy consumption and communication overhead ; however, it suffers from the security problems of data integrity. In fact, designing integrity schemes for data aggregation is an imperative problem for securing WSNs. In this paper, we propose a secure data aggregation based on homomorphic MAC scheme that provide efficient secure data integrity with different trade-offs between security assumptions, computation cost, and communication payload. The scheme uses two types of homomorphic MAC (i.e., MACs and EMACs). Each MAC provides integrity of the transmitted message and each EMAC provides integrity of the MACs. Our experiments show that our scheme requires less computation overheads and energy consumption than previously methods and can effectively preserve data integrity.

SUMMARY The auto‐design of electronic circuits for the next generation Information Technology (IT) computing environments is currently one of the most extensively studied issues in the field of evolvable hardware (EHW) architectures. It aims to improve the reliability and fault‐tolerance of hardware systems using embedded techniques. As the scalability of logic circuits becomes larger and more complex nowadays, its auto‐design is more and more difficult. In order to improve the efficiency and the capability of digital circuit auto‐design, in this paper, a multi‐objective simulated annealing (MSA)‐based increasable evolution approach is proposed in an embedded system. First, an extended matrix encoding method is used to indicate the potential performance of a circuit. Therefore, the risk of deleting a circuit with a good developing potential during evolution can be reduced. Second, we consider each output of a digital circuit as an objective, and MSA is designed for digital logic circuits with gradual evolution scheme. In the process of evolution, each objective is evolved in parallel with adaptive mechanism of neighborhood and a performance evaluation. Finally, a framework of online evolution with macro‐blocks is employed to implement MSA on a field‐programmable gate array efficiently and securely. In our experiments, six arithmetic circuits are designed to assess the performance of MSA with gate‐level and function‐level approaches comparing to other algorithms. The comparison results show that our method is very efficient in the auto‐design of EHW. Copyright © 2010 John Wiley & Sons, Ltd.

ABSTRACT Static password authentication has security drawbacks. In two‐factor authentication (2FA,) each user carries a device, called token, to generate passwords that are valid only one time. 2FA based on one‐time passwords (OTPs) provides improved protection because users are prompted to provide something they know (i.e., PIN) and something they have (i.e., token). Many systems have satisfied the 2FA requirements by sending an OTP through an SMS to the user's phone device. Unfortunately, international roaming, and SMS costs, delays, and security put restrictions on this system reliability. Also, time synchronous‐based solutions are not applicable for mobile phones. In this paper, we present a novel 2FA scheme whereby multiple OTPs are being produced by utilizing an initial seed and two different nested hash chains: one dedicated to seed updating and the other used for OTP production. We overcome all the restrictions that come from other techniques. We analyze our proposal from the viewpoint of security and performance compared with the other algorithms. Copyright © 2011 John Wiley & Sons, Ltd.

In the past decade, as new wireless technologies are developed and deployed, they also need a new generation of security and privacy control techniques. Thus, security and privacy are becoming primary concerns. There are many security challenges ahead if wireless technologies are to gain the trust and confidence of users. Thus, this Special Issue on Security and Privacy in Wireless Systems aims to address many aspects of wireless communication security and covers advances in wireless communication systems that have enabled the Internet to be even more ubiquitous in terms of network deployment and management. This issue highlights some of the latest research results in this area and presents some novel and innovative security and privacy techniques especially used in Wireless Networks. This issue summarizes the current state-of-the-art research and provides valuable insights into future directions and challenges in the field. An eavesdropper can use reverse packet-routing to identify the location of the source sensor, and then capture the information. In “A Privacy-Aware Overlay Routing Scheme in WSNs,” L. Kazatzopoulos, K. Delakouridis, and G.F. Marias, introduced a novel approach that uses a non-geographical, overlay routing method for packet forwarding, routing, and delivery. By using enhanced information privacy and source-to-sink unlinkability, the authors conducted simulation experiments to assess the performance of their approach and compared this with related approaches. Topology Maintenance Protocols (TMPs) have been widely used in Wireless Sensor Networks (WSNs). Although different TMPs have been presented in the literature, few address security issues. Recently, a Secured TMP (Sec-TMP), which does not require pair-wise node confidentiality, has been proposed. In “Secure Topology Maintenance and Events Collection in WSN,” authors A. Gabrielli, M. Conti, R. Pietro, and V. Mancini investigated the performance of Sec-TMP without any assumption on the show-up time of the data-collecting node, nor on the mobility model. In particular, they tested Sec-TMP against a realistic, unpredictable, data-collecting mobility scenario. Their results suggest that Sec-TMP is effective and secure in a realistic, unpredictable and mobile environment. In a Wireless Sensor Network (WSN), the location of sensors is very critical since the monitored event can be detrimental if the location of the sensors is compromised and/or inaccurate. In “SecLoc- Secure Localization in WSNs Using CDS,” author A. Srinivasan proposed a novel localization method for WSNs, which exploits the connected dominating set property of a network graph. This proposed method uses a set of beacon nodes with a large resource base and assumes the role of dominant nodes. Using simulation results, the author confirms the efficiency and robustness of this model. In Vehicular Ad Hoc Networks (VANETs), message verification is not given much importance due to its excessive resource consumption. In “On Resource-Aware Message Verification in VANETs,” authors Z. Li and C. Chigan proposed a novel Resource Aware Message Versification (RAMV) scheme which streamlines existing message verification schemes to keep their resource consumption within the budget of the available resource for message verification. On the other hand, it also verifies that common security requirements for message verification are also properly met using several novel techniques. Position and velocity in VANETs play an important role. Forging such information can cause serve impact on both the performance and security of VANETs. In “Verifying Position and Velocity for Vehicular Ad-Hoc Networks,” authors H. D. Weerasinghe, R. Tackett, and H. Fu proposed a position and velocity verification scheme. This proposed scheme uses both the Global Positioning System (GPS) and Differential GPS (DGPS) to verify both the velocity and position of the vehicle. The proposed scheme is simulated using the NS-2 simulator to verify and test it in various robust and dynamic environments. We would like to take this opportunity to thank the Editor-in-chief of the Wiley Journal of Security and Communication Networks, Professor Hsiao-Hwa Chen, and all the anonymous reviewers who devoted much precious time reviewing all the papers submitted to this Journal. Their timely review and feedback helped us select the best papers included in this special issue. Last but not least, we would like to thank all authors who contributed to this special issue and the staff at Wiley for their support during its preparation. A Privacy-Aware Overlay Routing Scheme in WSNs by L. Kazatzopoulos, K. Delakouridis, and G.F. Marias. Secure Topology Maintenance and Events Collection in WSN by A. Gabrielli, M. Conti, R. Pietro and V. Mancini. SecLoc- Secure Localization in WSNs Using CDS by A. Srinivasan. On Resource-Aware Message Verification in VANETs by Z. Li and C. Chigan. Verifying Position and Velocity for Vehicular Ad-Hoc Networks by H. D. Weerasinghe, R. Tackett, and H. Fu.

A next generation network (NGN) exploits advanced multiple broadband, quality of service (QoS)-enabled service technologies. The NGN is aimed at users and service-related functions, including web services. Recently, web service composition (WSC) has become a new approach for overcoming many difficult problems confronted by B2B e-commerce, inter-organization workflow management, enterprise application integration etc. Due to the uncertainty of the NGNs and various web services, the performance of the WSC cannot be ensured. How to model it and predict its performance becomes a difficult problem for WSC. In this paper, we propose a novel performance simulation model for WSC, called STPM+. The STPM+ model can support modeling and simulating the time and non-time QoS metrics. Based on the stochastic timed colored Petri net, the STPM+ model can simulate and predict multiple QoS metrics, such as cost, reliability, reputation and so on. To examine the validation of our STPM+ model, we have designed and realized a visual performance simulation tool, called VisualWSCPE. Based on VisualWSCPE, we have fulfilled some simulation experiments. The experiment results demonstrate the feasibility and efficiency of the STPM+ model.

Among the research community, on-going efforts are being continued to efficiently interconnect MANETs to fixed infrastructure in order to expand the reach of the Internet to Wireless access networks. Such scenario gives raise to a number of challenges that require solutions involving Internet gateway selection scheme, extensions to ad hoc routing technique. In this paper, we depict a network architecture framework that integrates Mobile IP and to achieve the interconnection between a multipath MANET and the Internet. We propose multipath routing protocol and also depict a gateway selection scheme. We conduct simulation for such an approach and evaluate its performance with various metrics.

Recently, control and coordination of a set of autonomous mobile robots has been paid a lot of attentions, because the cooperation of simple robots offers several advantages, such as redundancy and flexibility, and allows performing hard tasks that could be impossible for one single robot. There are a lot of interesting applications of multiple robots, such as satellite exploration and surveillance missions. So far, there are many papers working on the coordination of mobile robots. The characteristic of simplicity of mobile robots brings potential wide applications; however this characteristic also lead to crash with higher probability during cooperation, especially in harsh environment. Surprisingly, only few researches consider the fault tolerance of mobile robots, especially for dynamic coordination application - robot flocking. In this paper, we summarize the existed flocking algorithms and discuss their characteristics. Then we briefly described our fault tolerant flocking algorithms in different models. Finally we proposed the potential future research directions for dynamic flocking of a group of mobile robots. In all, this work can provide a good reference for the researchers working on dynamic cooperation of agents in distributed system.

As home devices have various functions and have improved computing power and networking ability, home device authentication has become increasingly important for improving the security of home network users. Moreover, device authentication supplies user convenience for the home network service user because it can replace the user authentication required for the used home network service. In addition, the safety of the home network can be strengthened if device authentication is considered in addition to the authentication and access control for the home network user. In this paper, we describe home device authentication, which is a basic and essential element of home network security. We propose a home device authentication framework, home device registration, method of issuing certificates and a home device certificate profile. Our home device certificate profile is based on the Internet X.509 certificate. In short, our device authentication concept can offer convenience and security to users of a home network service.

The requirements for access control have been increased significantly in smart home systems. Many factors such as user ID, user location, service usage conditions and so on, regarded as authorization attributes, are important in making authorization decision in smart home systems. We investigate into the dynamic characteristics of the authorization in smart home systems and propose a new access-control model, SH-CRBAC, which aims to combine the advantages of attribute-based authorization mechanism and role-based access-control mechanism, and imposes attribute and status constraints on the RBAC model and enhances the generality and flexibility of authorization significantly in smart home systems. The status consistency of SH-CRBAC is analysed, and we also analyse the characteristics of SH-CRBAC through comparison with other popular existing authorization models in smart home systems.

We develop a novel collision-free channel assignment and scheduling mechanism (CFCS) for multichannel wireless sensor networks. Firstly, each node is assigned with a quiescent channel to reduce hidden terminal beforehand and then it makes channel adjustment according to dynamic traffic. Secondly, a scalable multichannel scheduling is designed to make a tradeoff between overhead and fairness. We have implemented simulation to evaluate the performance of CFCS by comparing with other relevant protocols. The results show that our protocol exhibits more prominent ability, which utilizes multichannel to make parallel transmission and reduce hidden terminal problems effectively in resource-constrained wireless sensor networks.