The security of collaboration among drone swarms necessitates the creation of inter-swarm/group keys. However, current solutions lack an inter-group key establishment mechanism that supports uniformity, flexibility, trustworthiness, efficiency and scalability to enable secure and efficient inter-swarm communications. In this paper, we propose DeGKG, an efficient decentralized inter-group key generation scheme that offers the construction of inter-swarm encryption keys for various drone swarms. It leverages the regional similarity of satellite cluster signals to construct drone swarm public/private key pairs, and employs the Chinese remainder theorem to integrate the swarm public keys for creating inter-group encryption keys, significantly reducing the number of complex cryptographic operations and the burden of inter-swarm key creation, and ensuring the scalability. In addition, the inter-swarm key creation allows the division of drones without the regional similarity of satellite cluster signals into various swarms, each composed of drones with the signal similarity, thus supporting the key establishment among all the drones and efficacy. An efficient blockchain consensus mechanism is implemented to uniformly generate inter-group encryption keys for various swarm combinations without relying on a trusted third party, thus ensuring the efficiency, flexibility, and trustworthiness of the generation. We prove the security of DeGKG, and demonstrate its efficacy and efficiency through simulations and comparisons.

The sixth-generation (6G) mobile communication networks are perceived as large-scale heterogeneous networks. With their increased heterogenization and densification, it is crucial to guarantee the security and efficiency of user equipment's handovers between networks. However, existing cross-domain handover authentication schemes cannot ensure handover authentication efficiency and cannot balance privacy and system efficiency, which thus cannot be directly applied in heterogeneous networks. In this paper, we present PECHA, a privacy-preserving and efficient cross-domain handover authentication scheme for heterogeneous networks, which enables anonymous authentication on user equipment (UE) through the collision property of chameleon hash functions. PECHA ensures authentication efficiency by employing the interplanetary file system and blockchain to synchronize UE's authentication information to target networks in advance. The privacy and system efficiency are balanced by modeling the unlinkability of UE's new and old chameleon hash values and determining the update frequency of UE chameleon hash value. PECHA also achieves correctness, mutual authentication and key agreement, anonymity, unlinkability, conditional privacy, forward/backward secrecy, robustness, known randomness secrecy, key escrow freeness and rapid response, and resists against spoofing attacks, replay attacks and man-in-the-middle attacks. Comprehensive performance analysis, evaluation and comparisons show that PECHA is efficient with respect to both computation and communication.

Vehicle platoon has attracted much attention in recent years for its benefits in improving traffic efficiency, road safety, and energy consumption. In a vehicle platoon, vehicles can take on the roles of either a leading vehicle or a following vehicle, depending on the need. Selecting a reliable leading vehicle is crucial to improve the reliability of the vehicle platoon, and reputation management plays a vital role in this selection process. However, the existing reputation management schemes do not distinguish the leading vehicle's reputation value (LV-Reputation value) and the following vehicle's reputation value (FV-Reputation value), and merge them into a single reputation value, which exposes the reputation management scheme to the single reputation attack, an attack identified for the first time in this work. Additionally, some schemes fail to preserve the vehicle reputation value privacy, feedback score privacy, or identity privacy, and some overlook the security of the reputation management scheme. To address these issues, we propose a Privacy-Preserving Dual Reputation (PPDR) management scheme in vehicle platoon. The PPDR scheme separates a vehicle's reputation value into LV-Reputation value and FV-Reputation value, effectively mitigating the single reputation attack. Furthermore, under the premise of preserving reputation value privacy, feedback score privacy, and identity privacy, the PPDR scheme employs a score difference calculation algorithm to support the weighted average mechanism and the dual reputation management mechanism, which can significantly improve the accuracy of reputation management scheme. It also provides strong security with acceptable computation communication overheads. Comprehensive theoretical analysis and simulation evaluation have been carried out, and the results demonstrate that the PPDR scheme is significantly superior than the existing schemes in several aspects.

Authenticated key agreement (AKA) between vehicles and road side units (RSUs) is crucial in vehicular ad-hoc networks (VANETs). However, existing solutions still suffer from high overheads of AKA and lack a mechanism to balance privacy strength and system efficiency. In this paper, we present a lightweight anonymous authenticated key agreement (LWAKA) scheme for VANETs, supporting lightweight anonymous authentication and key agreement between vehicles and RSUs simultaneously. In particular, vehicles’ authentication information is synchronized to target RSUs in advance for accelerating authentication, and lightweight cryptographic operations (i.e., hash function, hash-based message authentication, physical unclonable function, fuzzy extractor and symmetric encryption) are employed to ensure the high efficiency of AKA in terms of computation and communication overheads. The system efficiency and privacy are balanced through modeling the relationship between the frequency of pseudonym updates and the unlinkability of the vehicles’ new and old pseudonyms. Security analysis shows that LWAKA not only achieves anonymity, conditional privacy, pseudonym unlinkability, key escrow freeness, and physical security, but also resists against most known attacks. Comparative experimental results demonstrate that LWAKA outperforms existing schemes in terms of lightweight design.

Group-based content push can be widely applied in integrated networks, where group key management is crucial for the push's security. Existing group key management methods mainly include symmetric group key agreement, broadcast encryption, asymmetric group key agreement, and attribute-based encryption. However, most of them do not consider user equipment (UE) identity privacy and unlinkability, cannot support flexibility and efficiency due to each UE maintaining group keys, and lack the trustworthiness of UE and group key management, which hinders the widespread adoption of group-based content push in trustless environments like integrated networks. In this paper, we investigate a novel decentralized group key management (DeGKM) scheme for group-based content push in integrated networks, where different operators manage pseudonyms and group keys across domains in a decentralized manner. In particular, our scheme adopts verifiable shuffling to establish a unified and trustworthy inter-domain pseudonym management approach that can preserve UE identity privacy and pseudonym unlinkability without relying on a trusted third party, and introduces a unified inter-domain group key management method based on Chinese remainder theorem and blockchain that significantly guarantees the flexibility, efficiency and trustworthiness. We formally prove the security of DeGKM and show its efficiency through simulations and comparisons with related works.

Evaluating and sharing user equipment (UE) trust across multiple network domains can greatly support security and trust management of future integrated heterogeneous networks. But the dilemma between identity privacy preservation and trust evaluation efficacy causes a big challenge in pseudonym and trust value management. Most existing approaches either rely on a trusted third party (TTP) and non-collusive parties, or deploy trusted execution environments (TEEs). They cannot be applied directly into a trustless heterogeneous network environment, where network domains do not trust with each other and it is hard to setup a fully trusted party. In this article, we propose DePTVM, a decentralized pseudonym and trust value management scheme for integrated heterogeneous networks, where different network operators jointly maintain a list of$< $pseudonym, trust value$>$pairs by employing verifiable shuffling and trust obfuscation based on blockchain in order to support anonymous trust evaluation and ensure pseudonym unlinkability. We analyze DePTVM with respect to correctness, unforgeability, anonymity and unlinkability, and evaluate its performance through simulations. Experimental results show that trust synchronization can be achieved across domains within 9 seconds with our experimental settings and the time taken by the most complex operation (i.e., verifiable shuffling) of operator agent increases linearly with the scale of maintained list. Analysis and experimental results imply DePTVM's potential in practical applications.

In response to critical security threats such as data tampering, identity impersonation, and channel eavesdropping in Vehicle-to-Grid (V2G) networks, numerous charging authentication schemes have been proposed. However, these schemes either lack sufficient anonymity, physical security, or electricity consumption data aggregation for electricity dispatch. In light of these considerations, we propose a comprehensive solution—a physically secure and privacy-preserving charging authentication framework with data aggregation, comprising two foundational schemes. The first scheme introduces a fully anonymous authentication system. In this approach, an Electric Vehicle (EV) seeking charging generates a random signature for its charging request. Subsequently, a Charging Station (CS) verifies the signature, granting charging services upon successful validation. Notably, this process guarantees the EV’s real identity remains undisclosed, even to the Control Center (CC). Moreover, this scheme also addresses potential physical attacks through the incorporation of a physical unclonable function. The second scheme involves a privacy-preserving data aggregation scheme, aggregating total electricity consumption of CSs in a given area while simultaneously preserving individual CSs’ electricity consumption data from potential leakage. Subsequently, the aggregated electricity consumption data is transmitted back to the CC, enabling efficient electricity coordination. A detailed security and privacy analysis demonstrates that our proposed framework meets intended security and privacy objectives. The final performance evaluation underscores the advantages of our proposed framework in comparison with related work.

Massive video resources satisfy the interests of users on online video platforms but have led to the problem of the “explosion” of video resources. Meanwhile, some problems will also occur such as the sparse data, difficulty in extracting deep features and dynamic changes in user interests in video recommendation. Aiming at the problems, a video recommendation method is proposed based on the deep learning of group evaluation behavior. Using the Word2Vec word vector model, a video is mapped into a high-dimensional feature vector in an evaluation behavior sequence, a video feature vector library is generated, and a feature vector model of the video sequence is established. The convolutional neural networks (CNN), residual networks, and attention mechanisms are integrated to learn the deep connections between video feature vectors and to predict the candidate video sets. The candidate set is expanded by cosine similarity, and a dynamic interest model is established to filter and sort it. Experiments on the Movie-1M dataset show that this method can effectively improve the accuracy and recall rate of video recommendation, which verifies the feasibility and effectiveness of the method.

Feed recommendation allows users to constantly browse items until feel uninterested and leave the session, which differs from traditional recommendation scenarios. Within a session, user's decision to continue browsing or not substantially affects occurrences of later clicks. However, such type of exposure bias is generally ignored or not explicitly modeled in most feed recommendation studies. In this paper, we model this effect as part of intra-session context, and propose a novel intra-session Context-aware Feed Recommendation (INSCAFER) framework to maximize the total views and total clicks simultaneously. User click and browsing decisions are jointly learned by a multi-task setting, and the intra-session context is encoded by the session-wise exposed item sequence. We deploy our model on Alipay with all key business benchmarks improved. Our method sheds some lights on feed recommendation studies which aim to optimize session-level click and view metrics.

Security-related data collection is an essential part for attack detection and security measurement in Mobile Ad Hoc Networks (MANETs). A detection node (i.e., collector) should discover available routes to a collection node for data collection and collect security-related data during route discovery for determining reliable routes. However, few studies provide incentives for security-related data collection in MANETs. In this article, we propose B4SDC, a blockchain system for security-related data collection in MANETs. Through controlling the scale of Route REQuest (RREQ) forwarding in route discovery, the collector can constrain its payment and simultaneously make each forwarder of control information (namely RREQs and Route REPlies, in short RREPs) obtain rewards as much as possible to ensure fairness. At the same time, B4SDC avoids collusion attacks with cooperative receipt reporting, and spoofing attacks by adopting a secure digital signature. Based on a novel Proof-of-Stake consensus mechanism by accumulating stakes through message forwarding, B4SDC not only provides incentives for all participating nodes, but also avoids forking and ensures high efficiency and real decentralization. We analyze B4SDC in terms of incentives and security, and evaluate its performance through simulations. The thorough analysis and experimental results show the efficacy and effectiveness of B4SDC.

Security-related data collection is an essential part for attack detection and security measurement in Mobile Ad Hoc Networks (MANETs). Due to no fixed infrastructure of MANETs, a detection node playing as a collector should discover available routes to a collection node for data collection. Notably, route discovery suffers from many attacks (e.g., wormhole attack), thus the detection node should also collect securityrelated data during route discovery and analyze these data for determining reliable routes. However, few literatures provide incentives for security-related data collection in MANETs, and thus the detection node might not collect sufficient data, which greatly impacts the accuracy of attack detection and security measurement. In this paper, we propose B4SDC, a blockchain system for security-related data collection in MANETs. Through controlling the scale of RREQ forwarding in route discovery, the collector can constrain its payment and simultaneously make each forwarder of control information (namely RREQs and RREPs) obtain rewards as much as possible to ensure fairness. At the same time, B4SDC avoids collusion attacks with cooperative receipt reporting, and spoofing attacks by adopting a secure digital signature. Based on a novel Proof-of-Stake consensus mechanism by accumulating stakes through message forwarding, B4SDC not only provides incentives for all participating nodes, but also avoids forking and ensures high efficiency and real decentralization at the same time. We analyze B4SDC in terms of incentives and security, and evaluate its performance through simulations. The thorough analysis and experimental results show the efficacy and effectiveness of B4SDC.