With electric vehicle's charging information, the utilities can increase the efficiency and reliability of Vehicle-to-Grid (V2G) while the electric vehicle consumers can better manage their energy consumption and costs. However, since charging information are commonly transmitted via public network or wireless link, their communications lack trusted third party for identity authentication and key distribution, and are constantly exposed to traffic analysis attacks. In this article, we propose a secure and anonymous communication scheme for delivering charging information in V2G. Different from previous works, the scheme in this article creatively incorporates identity authentication into key distribution without trusted third party, which improves the security of communication in public networks. Moreover, the proposed scheme is more resistant to traffic analysis since it preserves the anonymity of charging information by splitting and forwarding them pseudo-randomly. As the performance analysis reveals, our scheme is able to provide better anonymity without the support of trusted third party, and what's more, it can achieve high cryptography capability as traditional communication schemes do. Therefore, it is more practical in real-world V2G.

The Road Side Unit (RSU) is an important part of the Internet of Vehicles (IoV), which collects a large number of user's privacy information and connects vehicles to the Internet. The current RSU is running with static configurations, and the adversary can get enough time to analyze the vulnerability of the RSU and launch attacks, which poses a huge threat to the privacy security of the IoV. Under this asymmetrical condition, the attackers occupy a predominant position, and it is difficult to fully defend. To solve the above asymmetry offense-defense problem, we adopt the moving target defense (MTD) to dynamically change the IP address of the RSU, which increases the difficulty of the attacker's attack. However, due to the unreasonable selection of the RSU's IP hopping frequency, it is difficult for the RSU's IP hopping to exert its defense effect or it may introduce excessive defense overheads. Given the above issue, we propose an intelligent offense and defense mechanism based on a differential game approach, which can adaptively adjust the RSU's IP hopping frequency and maximize its defense benefits. First, based on the offense and defense relationship, we model the RSU's IP hopping frequency intelligent arrangement as a differential game (i.e., IP hopping game) in which the attacker attempts to maximize his potential benefits, and the RSU manages to maximize its defense benefits. On this basis, we calculate a potential Nash equilibrium of the IP hopping game. Finally, simulation results show our proposed mechanism can adaptively adjust the RSU's IP hopping frequency according to the attack frequency and effectively defend attacks. Compared with the mechanisms with a fixed IP hopping frequency, our proposed mechanism can make up for the ineffectiveness of the fixed low-frequency IP hopping defense and avoid the excessive defense overheads of the fixed high-frequency IP hopping defense.

In an untrusted Internet environment, there is a large amount of user privacy information being vulnerable to various attacks, and it is an important security concern for users on how to protect their privacy, and to further provide the anonymity guarantee. Recently, most privacy-sensitive users prefer anonymous communication to protect their private information from eavesdropping by attackers. Each user has different privacy protection demands for anonymous communication. However, anonymous communication methods cannot meet the various anonymity needs of users. Hence, the user on-demand anonymous communication is proposed, which can dynamically adjust the anonymity level according to a user’s anonymity needs. However, the defense capabilities against attacks are insufficient in the existing user on-demand anonymous communication. Some malicious users in the network employ anonymous communication to hide their identities and attack the Internet. Moreover, the existing user on-demand anonymous communication is weak against traffic classification attacks based on machine learning. Therefore, this paper investigates its progresses and defects in privacy protection and network security. User on-demand anonymous communication is mainly composed of the user side and the transmission side. We separately investigate privacy protection and network security of user on-demand anonymous communication from the user side and the transmission side. By surveying various identity anonymity of users on the user side and the hierarchical anonymous transmission on the transmission side, we find two kinds of serious attacks in user on-demand anonymous communication, i.e., abuse of anonymous communication and traffic classification attacks based on machine learning. To solve the above security issues, we suggest the balancing mechanism of anonymous communication and behavior tracking which is used to prevent anonymous abuse, and the secure defense mechanism which is used to resist traffic classification attacks. To inspire follow-up research, we identify some open problems and emphasize future trends concerning user on-demand anonymous communication.

Crowdsensing enables extensive data collection for Location-Based Services (LBS). However, there is a large amount of sensitive private information within the sensing data of the user's location. Hence, it will pose a huge threat to user's privacy if the sensing locations are published without protection. As usual, the user's location has two typical attributes, i.e., a geographic one and a social semantic one. Hence, the secure publishing of the user's sensing location data should consider how to protect both of the attributes-related privacy security. However, even for the same location, the same user may have different privacy protection needs along with different sensitive events, let alone that different users have different privacy protection needs due to their differences in age, gender, occupation, etc. Therefore, we propose a personalized secure publishing mechanism of the sensing location data. At first, it makes collaborative protection between semantic and geographic attribute-related privacy from two aspects, i.e., adjusting the user's location information loss to meet different privacy protection needs of users, and personalizing the privacy-attack tolerance degree to achieve different privacy protection levels. Then, it optimizes the collaborative protection effects with the Stackelberg game to achieve the best balance between user data security and data quality. The experiments based on the real-world dataset demonstrate the effectiveness of our proposed mechanism.

In ITS environment, the driver-assistant services usually demand delivering video content to vehicular users, which is very useful in the intervention of emergency services, and reminds the drivers the traffic jam in ahead road. Nowadays for online video delivery in connected vehicle networks, HTTP adaptive streaming (HAS) is one of the most promising technologies, where a video is encoded into multiple bitrates and then split into small segments. It is crux for ITS service providers how to improve users’ QoE through an adaptive video segments request strategy. From the perspective of adaptive matching among segment bitrate, network bandwidth, and buffer occupancy, we propose a bandwidth-aware video segment request strategy to optimize user’s QoE (for short Bw-QoE), which consists of two parts, i.e., available bandwidth estimation, and segment’s bitrate selection. First, based on the severity of bandwidth fluctuation, Bw-QoE estimates the available bandwidth with different historical weighted average methods. Then constrained by the estimated available bandwidth and buffer occupancy, the adaptive bitrate selection is formulated as an optimization model to maximize user’s QoE of a video streaming session. It is fairly attractive for Bw-QoE to prevent buffer overflow, underflow and unuseful download, and to reduce bitrate switching. Compared with the classic strategy (e.g., LIU’s strategy), the simulation results show that the proposed strategy Bw-QoE has higher average video bitrate (about 8%-10%), less interruption (about 100%), less segment bitrate switching (about 15%-17%) and higher buffer occupancy (about 13%-51%), which demonstrate that our strategy effectively improves QoE.