Connected-vehicle and roadside telemetry enable low-latency safety navigation, and traffic-optimisation services at the edge, but finegrained mobility streams (locations, speeds, events, and contexts) create high re-identification and linkage risk when accessed by multiple stakeholder domains. We present a Zero Touch Network and Service Management (ZSM) integrated, policy-driven data-collection service that operationalises mobility data governance through intent-based automation. Stakeholders submit high-level collection intents (purpose, fields, spatial/temporal granularity, latency, and utility targets); a policy engine evaluates and rewrites intents into compliant, effective intents; and a plan generator compiles them into executable data-collection pipelines deployable within a ZSM closed loop. Experiments on Beijing taxi mobility traces execute 87,500 DP-protected releases and achieve 1.26% relative error for Road Safety Authority (RSA) at ϵ = 8.0, while DP-Stochastic Gradient Descent (DP-SGD) risk scoring reaches 0.97 ± 0.03 test accuracy at ϵ = 0.5, with δ= 10-5.

Federated Learning (FL) is a distributed Machine Learning (ML) technique that trains a collaborative ML model without sharing data and by sharing only the model updates. FL is critical in 6 G networks as it enables decentralized and privacy-preserving Artificial Intelligence (AI) model training across distributed devices, reducing communication overhead and enhancing data security, which is crucial for supporting AI-driven 6G networks and applications such as autonomous vehicles, healthcare, and immersive Extended Reality. Since the FL clients transmit only the model updates instead of data, FL is vulnerable to poisoning attacks. The result of a poisoning attack is an incorrect outcome at the inference, affecting the application requirements when employed in 6 G systems. Existing defense mechanisms focus on the attacks in a static nature disregarding the dynamic behavior of attackers. Since the 6 G networks are highly AI-driven, attackers can also learn about the network using AI techniques allowing them to execute more sophisticated dynamic attacks. In this paper, we evaluate how existing defense mechanisms fail in the presence of dynamic poisoning attacks. We also propose novel defense DBFFL against dynamic poisoning attacks in FL, to ensure robustness when deployed in 6 G networks and applications.

Device-to-Device (D2D) communication operating in relay mode has become an essential strategy for extending network coverage and ensuring reliable connectivity, particularly in environments where direct links are unavailable in 5G network communications. However, securing D2D communication in 5G networks in resource-constrained Internet of Things (IoT) environments remains a significant challenge, especially authentication. The state-of-the-art for D2D communication in 5G reveals that existing authentication and key agreement protocols are often vulnerable to severe security threats, including denial-of-service (DoS) attacks, anonymity, ephemeral secret leakage and replay attacks, also do not offer perfect forward secrecy. Moreover, their computational complexity makes them unsuitable for deployment on constrained IoT devices. To address these limitations, this paper proposes a Secure and Efficient D2D authentication Protocol for 5G Communication based on Elliptic Curve Diffie-Hellman (ECDH) key exchange. The proposed protocol is rigorously evaluated through both informal and formal security methods (Real-Or-Random (ROR) logic and Scyther tool) to demonstrate its robustness against various known attacks. Additionally, a comprehensive performance comparison with existing schemes highlights the proposed protocol’s advantages in terms of security features, computational efficiency, communication overhead, and storage requirements.

Cyberattacks on e-mails are of different types, but the most pervasive and ubiquitous are spoofing attacks. Our approach uses memory forensics to extract e-mail headers from live memory to perform an e-mail header investigation to identify spoofing attacks. We have identified the research gaps and advanced our work to achieve better results. In this paper, we have made two significant improvements. First is URL validation module that uses a novel technique of checking each captured URL with an MX record and e-mail URL features. This scheme is fast, and reduces the total time from 35 sec to 27 sec. Second, spoofed e-mail detection is ameliorated by applying an ML model built using two novel e-mail header fields (BIMI and X-FraudScore) and four authentication header fields (SPF, DKIM, DMARC, and ARC). This enhances the spoofed e-mail detection accuracy from 96.15% to 97.57% with low false positives.

The plethora of Internet of Things (IoT) devices and their diversified requirements have opted to design security mechanisms that cover all major security requirements. Wireless Local Area Networks (WLANs) is the most common network domains where IoT devices are launched, particularly because of its easy availability. Security, in other words authentication however, remains to be a major constriction for IoT-WLAN deployments. Though there are IoT based authentication protocols prevailing, such protocols are either prone to threats such as perfect forward secrecy violations, insider with database access attack, traceability attack, stolen device attack, ephemeral secret leakage, or they consume excessive computational and communication resources that result in an unprecedented burden for the IoT system. This paper presents an Extensible Authentication Protocol (EAP) based mechanism for IoT devices deployed in a WLAN that addresses the above security issues and achieves cost-effectiveness. Validation follows an informal and formal approaches (using GNY and BAN logic, and Scyther verification tool) for the proposed protocol, demonstrating its robustness. Our performance analysis shows that the proposed protocol is lightweight and more secure in contrast to the state-of-the-art solutions. In addition, performance of the proposed protocol subjected to unknown attacks is investigated, which deduces that the proposed protocol has less overhead under unknown attacks than its competitors. A prototype of the protocol has been developed to demonstrate its feasibility and accuracy.

The rapid proliferation of the Internet of Things (IoT) in recent years has fostered the swift development of various applications, enabling seamless connections between consumers and everyday utilities. One sector that has seen significant transformation is healthcare, thanks to the adoption of IoT and Ambient Intelligence (AmI). However, this growing utilization of IoT-AmI systems has raised substantial concerns about privacy and security, particularly in user authentication. Numerous authentication techniques have been established for IoT-AmI systems. Nevertheless, the current state-of-the-art reveals that these methods are vulnerable to various severe attacks, such as impersonation, Man-in-the-middle (MITM), traceability, replay, privacy and violation of perfect forward secrecy. Considering the above, this paper aims to propose a secure authentication protocol for IoT-AmI systems. The security of the proposed protocol for IoT-AmI is verified using the formal analysis tool Scyther. Furthermore, the performance of the designed protocol is assessed to show that it has lower computational and communication costs compared to existing protocols.

The next generation of mobile communication systems must be secured because of the ongoing entrance of numerous security attacks. Thus, to secure the underlying network, the 3GPP has designed an authentication and key agreement protocol, 5G-AKA, to safely and stably access the mobile services. However, some recent observations indicate that 5G-AKA has numerous shortcomings such as perfect forward secrecy violation, malicious Serving Network (SN), de-synchronization attack, privacy theft, stolen device, and denial of Service (DoS) attacks when the user uses the roaming mobile services. Considering the shortcomings of existing protocols and the requirement to offer increased security, we propose a provable secure, efficient 5G-AKA authentication protocol using the blockchain. The security features of the proposed protocol are examined using the Real-Or-Random (ROR) logic and Scyther tool. Furthermore, the performance of the proposed protocol is evaluated, which shows that it is the least costly compared to its counterparts in terms of computational and communication costs. In addition, the comparison of the Ethereum blockchain depicts that the proposed protocol takes less transaction and execution costs compared to its counterparts.

The fifth generation (5G) is now widely used to access network services due to the emergence of the Internet of Things (IoT) and mobile devices. To secure 5G communication, the Third Generation Partnership Project (3GPP) organization created the 5G-Authentication and Key Agreement (AKA) protocol. Security evaluations have found a number of problems in the 5G-AKA, including a violation of perfect forward secrecy, a traceability attack, and denial of service (DoS) attacks. To address the shortcomings of 5G-AKA, several enhanced versions have been developed. However, it has been shown that either these versions are expensive or do not address security issues. Additionally, less effort is put into providing security when a user utilizes roaming mobile services while a malicious Serving Network (SN) is present. This paper introduces an authentication mechanism to handle the above issues. In addition to this, a handover mechanism is also designed for re-connection. The authentication and handover phase security assessment uses the mathematical model Real-Or-Random (ROR), AVISPA, and Scyther tool. Furthermore, the performance comparison depicts that the authentication and handover phase is more efficient than existing protocols. An assessment of the smart contract function’s cost and effectiveness is also provided.

Several symmetric and asymmetric encryption based authentication protocols have been developed for the wireless local area networks (WLANs). However, recent findings reveal that these protocols are either vulnerable to numerous attacks or computationally expensive. Considering the demerits of these protocols and the necessity to provide enhanced security, a lightweight extensible authentication protocol based authentication protocol for WLAN-connected Internet of Things devices is presented. We conduct an informal and formal security analysis to ensure robustness against the attacks. Furthermore, the empirical performance analysis and comparison show that the proposed protocol outperforms its counterparts, reducing computational, communication, storage costs, and energy consumption by up to 99%, 80%, 91.8%, and 98%, respectively. Simulation results of the protocol using the NS3 and its overhead under unknown attacks demonstrate that the proposed protocol performs better in all scenarios. A prototype implementation of the protocol has also been tested to evaluate its feasibility in real-time applications.

Network slicing is considered one of the key technologies in future telecommunication networks as it can split the physical network into a number of logical networks tailored to diverse purposes that allow users to access various services speedily. The fifth-generation (5G) mobile network can support a variety of applications by using network slicing. However, security (especially authentication) is a significant issue when users access the network slice-based services. Various authentication schemes are designed to secure access, and only a few offer cross-network slice authentication. The security analysis of existing cross-network authentication schemes shows they are vulnerable to several attacks such as device stolen, ephemeral secret leakage, violation of perfect forward secrecy, identity theft. Therefore, we propose an authentication mechanism that offers cross-network slice authentication and prevents all the aforementioned vulnerabilities. The security verification of the authentication mechanism is carried out informally and formally (ROR logic and Scyther tool) to ensure that it handles all the vulnerabilities. The comparison of empirical evaluation shows that the proposed scheme is least costly than its competitors. Java-based implementations of the proposed protocols imitate a real environment, showing that our proposed protocol maintains almost the same performance as state-of-the-art solutions while providing additional security features.

Due to the constant penetration of various security attacks, it is highly important to secure the underlying communication networks between the IoT, Fog and Cloud in the next generation of mobile communication system (5G). Thus, secure authentication and key agreement protocol, namely 5G-AKA, has been proposed in the literature to safely and stably access the 5G mobile services. However, some recent findings reveal that 5G-AKA and its numerous versions based on symmetric or asymmetric encryption are either vulnerable to different attacks such as perfect forward secrecy violation, malicious Serving Network (SN), de-synchronization attack, privacy theft, stolen device, or are computationally intensive. Apart from that, these protocols use single-factor authentication. Considering the above demerits of these protocols and the necessity to provide enhanced security, we propose an Elliptic Curve-Cryptography (ECC)-based multi-factor 5G-AKA authentication protocol. It provides additional security and achieves cost-effectiveness in terms of computational, communication, storage costs and energy consumption. The formal security analysis using Real-Or-Random (ROR) logic has been done to confirm its security. Moreover, we evaluate the performance of the proposed protocol in terms of computational, communication, storage costs and energy consumption. The evaluation results show that the proposed protocol requires less cost than its counterparts, reducing computational cost by up to 57%, communication cost by up to 59%, storage cost by up to 52%, and energy consumption by up to 51%.

The growing usage of wireless devices has significantly increased the need for Wireless Local Area Network (WLAN) during the past two decades. However, security (most notably authentication) remains a major roadblock to WLAN adoption. Several authentication protocols exist for verifying a supplicant’s identity who attempts to connect his wireless device to an access point (AP) of an organization’s WLAN. Many of these protocols use the Extensible Authentication Protocol (EAP) framework. These protocols are either vulnerable to attacks such as violation of perfect forward secrecy, replay attack, synchronization attack, privileged insider attack, and identity theft or require high computational and communication costs. In this paper, a lightweight EAP-based authentication protocol for IEEE 802.11 WLAN is proposed that not only addresses the security issues in the existing WLAN authentication protocols but is also cost-effective. The security of the proposed protocol is verified using BAN logic and the Scyther tool. Our analysis shows that the proposed protocol is safe against all the above attacks and attacks defined in RFC-4017. A comparison of the computational and communication costs of the proposed protocol with other existing state-of-the-art protocols shows that the proposed protocol is lightweight than existing solutions.

Wireless Local Area Networks (WLANs) have experienced significant growth in the last two decades due to the extensive use of wireless devices. Security (especially authentication) is a staple concern as the wireless medium is accessible to everybody. Extensible Authentication Protocol (EAP) is the widely used authentication framework in WLANs to secure communication. The authentication mechanism designed on EAP is called EAP method. There are numerous EAP based and nonEAP based authentication protocols for WLANs, but there is no protocol that fulfills all the security requirements, as mentioned in RFC-4017 and other additional requirements like perfect forward secrecy, Denial-of-service (DoS) attack protection, and lightweight computation. Hence, it is fair to infer that there is an impelling need to design a protocol that can meet all the security requirements. In this paper, we propose a secure and user efficient EAP-based authentication protocol for IEEE 802.11 WLANs. The proposed protocol has been formally validated by BAN logic and the AVISPA tool [18]. The simulation results depict that the proposed protocol achieves all security requirements, as mentioned in RFC-4017 along with perfect forward secrecy, Denial-of-service (DoS) attack protection, and lightweight computation. The proposed protocol outperforms the existing protocols in terms of computation cost by reducing the computation cost by ≈ 99.9956%, 99.991%, 27.27%, 22.705% in comparison to EAP-TLS, EAP-TTLS, EAP-Ehash, EAP-SELUA, respectively. Keywords-AP, AS, AVISPA, BAN, EAP, WLANs.

Prediction of ribonucleic acid (RNA) secondary structure is one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. We present a novel algorithm to optimize Zuker Algorithm on CUDA GPUs and achieve a speedup of ~10x for certain viruses.

Abstract Phishing is a fraudulent technique that is used over the Internet to deceive users with the goal of extracting their personal information such as username, passwords, credit card, and bank account information. The key to phishing is deception. Phishing uses email spoofing as its initial medium for deceptive communication followed by spoofed websites to obtain the needed information from the victims. Phishing was discovered in 1996, and today, it is one of the most severe cybercrimes faced by the Internet users. Researchers are working on the prevention, detection, and education of phishing attacks, but to date, there is no complete and accurate solution for thwarting them. This paper studies, analyzes, and classifies the most significant and novel strategies proposed in the area of phished website detection, and outlines their advantages and drawbacks. Furthermore, a detailed analysis of the latest schemes proposed by researchers in various subcategories is provided. The paper identifies advantages, drawbacks, and research gaps in the area of phishing website detection that can be worked upon in future research and developments. The analysis given in this paper will help academia and industries to identify the best anti‐phishing technique. Copyright © 2016 John Wiley & Sons, Ltd.

The network traffic management is a key issue as many new emerging applications are flooding the network with their packets. Several time sensitive and low bandwidth applications run along with other time insensitive and bandwidth intensive applications. As a result, most of the time, channel capacity is exhausted by the bandwidth intensive applications like P2P file sharing, Bittorent etc. Hence, there is a limited space left for critical applications. As a result, the accurate identification of network applications through proper observation of associated packets is vital to the areas of network management and surveillance. The overall implication of the accurate traffic management provides space for critical application and also it helps in better management of available network resources like channel capacity etc.

Context Aware computing has been one of the most challenging and interesting developments from the past decade. But as it turns out, context is a poorly used source of information which, most of the times is utilized inefficiently in Ubiquitous Computing Environments due to impoverished understanding of the term. To address this, in this paper, we first discuss how existing context aware systems exploit context and our own categorization of context. Then, we define two concepts - long term context and short term context. We discuss how they can be obtained and how their importance varies in different scenarios. They help in understanding context in a much better way and are necessary for an accurate data provisioning. Also, we introduce a method of estimating long term context using short term context patterns over a time duration.

Ad-hoc networks establish communication in improvised environments without requiring any fixed infrastructure. These networks are inherently prone to security attacks, with node mobility being the primary cause in allowing security breaches. Therefore secure routing is a must for such networks. A number of secure routing protocols based on trust have recently been proposed. However, all these protocols use the traditional route discovery model, where a node drops RREQ packet if its own ID is in the source route of the packet, or if it has previously processed the packet. A misbehaving node takes advantage of this vulnerability and forwards the RREQ fast, so that the RREQ received from other nodes are dropped and the path discovered includes itself (the misbehaving node). In this paper, we present a unique trust based method which is not vulnerable to this behavior. In our method, each node broadcasts a RREQ packet if it is received from different neighbors. A secure and efficient route to the destination is calculated as a weighted average of the trust value of the nodes in the route, with respect to its behavior observed by its neighboring nodes and the number of nodes in the route. We evaluate the misbehaving node detection rate and the efficiency of our method along a number of parameters. Results show that our method increases the throughput of the network while discovering a secure route.

Mobile Ad Hoc Networks (MANETs) are comprised of highly mobile nodes that communicate with each other without relying on a pre-existing network infrastructure. Therefore they are ideally suited for use in rescue and emergency operations. These applications have increased security requirements with low acceptable delays, in order to provide high quality service. However, MANETs were not designed with security protection in mind and they are prone to several attacks. Communication in mobile ad hoc networks comprises of route discovery and data transmission phases.

In most of Wireless Sensor Networks (WSNs) deployments, application requirements at sink and nature of event decide sensing frequency. Very high sensing frequency at sensor node (SNs) may result in generation of useless redundant data and too low sensing frequency may miss useful data about the event. Also, spurious data may be injected into network due to some temporary abnormal conditions near some active SNs. Therefore, in this paper we propose a data reporting scheme where prior to dissemination SN checks accumulated data against a filtering criteria. Further, sensing a slowly changing event with very high frequency results in lot of energy waste as it may generate redundant data. Whereas, sensing rapidly changing event with low frequency may cause loss of useful information. Since, the rate of change in the behavior of an event may be unpredictable, therefore along with data filtering we also propose an approach in which a cluster head node (CHN) dynamically sets sensing frequency in its cluster SNs by analyzing the flow of data reports received from these SNs. Simulation results show significant energy savings when this scheme is applied to various data dissemination approaches as opposed to scenarios when no data filtering is used and sensing frequency is fixed.

In this paper, we address several issues that are imperative to grid environments such as handling resource heterogeneity and sharing, communication latency, job migration from one site to other, and load balancing. We address these issues by proposing two job migration algorithms, which are MELISA (modified ELISA) and LBA (load balancing on arrival). The algorithms differ in the way load balancing is carried out and is shown to be efficient in minimizing the response time on large and small-scale heterogeneous grid environments, respectively. MELISA, which is applicable to large-scale systems (that is, interGrid), is a modified version of ELISA in which we consider the job migration cost, resource heterogeneity, and network heterogeneity when load balancing is considered. The LBA algorithm, which is applicable to small-scale systems (that is, intraGrid), performs load balancing by estimating the expected finish time of a job on buddy processors on each job arrival. Both algorithms estimate system parameters such as the job arrival rate, CPU processing rate, and load on the processor and balance the load by migrating jobs to buddy processors by taking into account the job transfer cost, resource heterogeneity, and network heterogeneity. We quantify the performance of our algorithms using several influencing parameters such as the job size, data transfer rate, status exchange period, and migration limit, and we discuss the implications of the performance and choice of our approaches.

Abstract Sparse connectivity, limited energy, and restricted memory of Mobile Hosts (MHs) are the main characteristics of today's Mobile Ad hoc NETwork (MANET). Present wireless technology is now enabling MHs not only to have multi‐hop communication among themselves, but also to have direct connection with an Access Point (AP) also. The emergence of such heterogeneous technologies brings cooperative caching to reality wherein MHs can access data items from caches at MHs in their neighborhood and can drastically minimize query latency. This key technique reduces the number of uplink channel requests, alleviates server load, and increases data availability. In this paper, we assume a heterogonous mobile environment where combination of ad hoc communication and infrastructured APs can be used to better manage the data needs of MHs through cooperative caching. We call such an environment as Cooperation‐based Access Point MANET (CAPMANET). We present a Hop‐Oriented Cooperative Caching (HOCC) scheme for CAPMANET which helps in reducing the communication overhead and the query latency. HOCC employs a hybrid Pull with Push (PwP) mechanism to maintain data consistency. Simulation results demonstrate that HOCC outperforms the pure push and pure pull‐based strategies by taking advantages of underlying characteristics and avoiding associated weaknesses. Copyright © 2007 John Wiley & Sons, Ltd.

This paper proposes a new commit protocol for real time distributed database systems, dependency sensitive shadow SWIFT (DSS-SWIFT) protocol where the cohort forks off a replica of itself called a shadow, whenever it borrows dirty value of a data item, and if, the created dependency is abort type as compared to creating shadow in all cases of dependency in shadow PROMPT. Also the health factor of cohort is used for permitting to use dirty value of lender rather than health factor of transaction as whole. The performance of DSS-SWIFT is compared with PROMPT, 2SC and SWIFT protocols for both main memory resident and disk resident databases with and without communication delay. Simulation results show that the proposed protocol improves the system performance up to 7% as transaction miss percentage