Vehicular ad hoc networks (VANETs) leverage information and communications technology to make transportation systems intelligent, safe, and efficient, hence improving people's driving experience. Unfortunately, due to the openness of wireless channels and vehicular mobility, privacy leakage in VANETs poses serious privacy concerns. Once a user's identity is leaked, it will cause serious threats to his/her property and personal safety as a malicious attacker, such as a stalker could utilize the targeted identity to track particular driver and/or launch malicious attack. To address such a privacy problem, by observing the nice properties of ring signature like anonymity, spontaneity, flexibility, and membership equality, we design a novel conditional privacy protection scheme based on ring signcryption, which utilizes the salient features of identity-based cryptosystems and ring signature to achieve conditional privacy. Through security analysis and experiments, we have demonstrated the advantage of our scheme over most existing solutions.

Battery-powered wireless IoT devices are now widely seen in many critical applications. Given the limited battery capacity and inaccessibility to external power recharge, optimizing energy efficiency (EE) plays a vital role in prolonging the lifetime of these IoT devices. However, a sheer amount of existing works only focus on the EE design at the infrastructure level such as base stations (BSs) but with little attention to the EE design at the device level. In this paper, we propose a novel idea that aims to shift energy consumption to a grid-powered cognitive radio mesh network thus preserving energy of battery-powered devices. Under this line of thinking, we cast the design into a cross-layer optimization problem with an objective to maximize devices’ energy efficiency. To solve this problem, we propose a parametric transformation technique to convert the original problem into a more tractable one. A baseline scheme is used to demonstrate the advantage of our design. We also carry out extensive simulations to exhibit the optimality of our proposed algorithms and the network performance under various settings.

Due to the tremendous growth in user population over online social networks (OSNs), interactive messaging traffic has experienced exponential growth, which consequently causes serious privacy concerns. Malicious users may utilize camouflage, phishing, and other unconventional social engineering techniques to lure ordinary users to reveal their sensitive attributes in their interactive messages when they least expect. In addition, during a communication session, attackers may intercept data packets with sensitive attributes to obtain private information. Therefore, it is of paramount importance for the system to successfully identify malicious users and prevent them from obtaining private information from messages containing sensitive attributes when socializing over OSNs. In this article, we propose a privacy-preserving scheme for interactive messaging by leveraging user credibility that characterizes users' reputation based on users' social behaviors and uses the item response theory in psychometrics to assess the risk levels of users' interactive messages. This scheme ensures the privacy preservation during message exchange through message obfuscation with the message replication and the replacement of sensitive attributes. Through the experiments on a Facebook-like Social Network Data Set, we have demonstrated that our proposed scheme has high availability and accuracy while achieving the high success rate to identify malicious users, which can thus greatly reduce the privacy leakage.

Communication technologies supply the blood for smart city applications. In view of the ever-increasing wireless traffic generated in smart cities and our already congested radio access networks (RANs), we have recently designed a data transportation network, the vehicular cognitive capability harvesting network (V-CCHN), which exploits the harvested spectrum opportunity and the mobility opportunity offered by the massive number of vehicles traveling in the city to not only offload delay-tolerant data from congested RANs but also support delay-tolerant data transportation for various smart-city applications. To make data transportation efficient, in this paper, we develop a spectrum-aware (SA) data transportation scheme based on Markov decision processes. Through extensive simulations, we demonstrate that, with the developed data transportation scheme, the V-CCHN is effective in offering data transportation services despite its dependence on dynamic resources, such as vehicles and harvested spectrum resources. The simulation results also demonstrate the superiority of the SA scheme over existing schemes. We expect the V-CCHN to well complement existing telecommunication networks in handling the exponentially increasing wireless data traffic.

In cognitive radio networks (CRNs), primary users (PUs) can leverage secondary users (SUs) as cooperative relays to increase their transmission rates, while SUs will in return obtain more spectrum access opportunities, leading to cooperative CRNs (CCRNs). Prior research works in CCRNs mainly focus on providing ubiquitous access and high throughput for users, but have rarely taken energy efficiency into consideration. Besides, most existing works assume that the SUs are passively selected by PUs regardless of SUs' willingness to help, which is obviously not practical. To address energy issue, this paper proposes an energy-efficient cooperative strategy by leveraging temporal and spatial diversity of the primary network. Specifically, SUs with delay-tolerant packets can proactively make the cooperative decisions by jointly considering primary channel availability, channel state information, PUs' traffic load, and their own transmission requirements. We formulate this decision-making problem based on the optimal stopping theory to maximize SUs' energy efficiency. We solve this problem using a dynamic programming approach and derive the optimal cooperative policy. Extensive simulations are then conducted to evaluate the performance of our proposed strategy. The results show significant improvements of SUs' energy efficiency compared with existing cooperative schemes, which demonstrate the benefits of our proposed cooperative strategy in conserving energy for SUs.

An Incentive Compatible two-hop Multi-copy Routing Protocol (ICMRP) is proposed for disruption-tolerant networks (DTNs), which takes both the encounter probability and transmission cost into consideration to defend the misbehaviors of selfish nodes. ICMRP ensures that nodes can maximize their profit when they report their encounter probability and transmission cost honestly. Meanwhile, the protocol adopts the theory of optimal stopping to select optimal relay nodes. A signature technology based on bilinear map is introduced to ensure the selected relay nodes can get the payment securely, which can prevent the malicious nodes from tampering the messages. Through enough simulations on the ONE simulator, it is proved that ICMPR can effectively stimulate nodes to transmit messages and achieve a higher packet delivery rate with lower cost.