Because of the enormous potential to guarantee road safety and improve driving experience, social Internet of Vehicle (SIoV) is becoming a hot research topic in both academic and industrial circles. As the ever-increasing variety, quantity, and intelligence of on-board equipment, along with the evergrowing demand for service quality of automobiles, the way to provide users with a range of security-related and user-oriented vehicular applications has become significant. This paper concentrates on the design of a service access system in SIoVs, which focuses on a reliability assurance strategy and quality optimization method. First, in lieu of the instability of vehicular devices, a dynamic access service evaluation scheme is investigated, which explores the potential relevance of vehicles by constructing their social relationships. Next, this work studies a trajectory-based interaction time prediction algorithm to cope with an unstable network topology and high rate of disconnection in SIoVs. At last, a cooperative quality-aware system model is proposed for service access in SIoVs. Simulation results demonstrate the effectiveness of the proposed scheme.

This paper presents techniques to verify the identity of computer users using the keystroke dynamics of computer user's login string as characteristic patterns using pattern recognition and neural network techniques. This work is a continuation of our previous work where only interkey times were used as features for identifying computer users. In this work we used the key hold times for classification and then compared the performance with the former interkey time-based technique. Then we use the combined interkey and hold times for the identification process. We applied several neural network and pattern recognition algorithms for verifying computer users as they type their password phrases. It was found that hold times are more effective than interkey times and the best identification performance was achieved by using both time measurements. An identification accuracy of 100% was achieved when the combined hold and intekey time-based approach were considered as features using the fuzzy ARTMAP, radial basis function networks (RBFN), and learning vector quantization (LVQ) neural network paradigms. Other neural network and classical pattern algorithms such as backpropagation with a sigmoid transfer function (BP, Sigm), hybrid sum-of-products (HSOP), sum-of-products (SOP), potential function and Bayes' rule algorithms gave moderate performance.

The Internet of Things (IoT) enables all objects to connect to the Internet and exchange data via different emerging technologies, which makes the intelligent identification and management a reality. Wireless sensor networks (WSNs), as a crucial basis of IoT, have been applied in many fields like smart health care and smart transportation. With the development of WSNs, data security has attracted more and more attention, and user authentication is a popular mechanism to ensure the information security of WSNs. Recently, many authentication mechanisms for wireless medical sensor networks (WMSNs) have been proposed, but most of the protocols cannot achieve the features of local password change and forward secrecy while resisting stolen smart card attack. To enhance the security based on previous work, an ECC-based secure three-factor authentication protocol with forward secrecy for WMSN is proposed in this paper. It utilizes a fuzzy commitment scheme to handle the biometric information. Meanwhile, fuzzy verifier and honey_list techniques are used to solve the contradiction of local password verification and mobile device lost attack. The security of our protocol is evaluated by provable security, Proverif tool, and information analysis. Besides, the comparisons with the relevant protocols are given, and the results indicate that our protocol is robust and secure for WMSN systems.

Wireless Powered Mobile Edge Computing (WPMEC) is an integration of Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) technologies, to both improve computing capabilities of mobile devices and energy compensation for their limited battery capabilities. Generally, energy transmitters, mobile devices, and edge servers form a WPMEC system that realizes a closed loop of sending and collecting energy as well as offloading and receiving task data. Due to constraints of time-varying network environments, time-coupled battery levels, and the half-duplex character of mobile devices, the joint design of computation offloading and resource allocation solutions in WPMEC systems has become extremely challenging, and a great number of studies have been devoted to it in recent years. In this article, we first introduce the basic model of the WPMEC system. Then, we present key issues and techniques related to WPMEC. In addition, we summarize solutions for computation offloading and resource allocation to solve critical issues in WPMEC networks. Finally, we discuss some research challenges and open issues.

With the emergence of the concept of smart city and the increase of vehicles, the vehicular ad-hoc network (VANET) is widely accepted for the communication of vehicles to get information including road condition, traffic congestion description, speed, and location of vehicles. Naturally, the security of the data transmission in VANET has become one of the urgent tasks of researchers. Many privacy-preserving authentication protocols for VANETs have been presented. However, heavy computations and security flaws exist in them. Thus, we put forward a lightweight authentication protocol in a suitable communication model for VANET that meets the privacy protection needs, with only hash functions and exclusive-OR operations. Formal security analysis using BAN logic shows that our protocol achieves the security goals. Proverif is used to verify the security of the protocol and the results show that the privacy can be guaranteed under the simulated attacker. Moreover, through security properties analysis, our protocol is robust enough to get rid of common attacks and keep the communication data secretly. The performance comparison results show that our protocol is lightweight and efficient. Furthermore, we simulate the network with SUMO and NS-3, and all show that our protocol is efficient and practical for VANETs.