Safety of the intended functionality (SOTIF) is paramount in autonomous driving, particularly at and beyond Level 3. An essential aspect of SOTIF research involves constructing and accurately assessing a broad range of hazardous scenarios. The current research landscape presents challenges in extensively testing autonomous vehicles and identifying all the unknown triggering events within their intended functionalities. Filling this gap, this article introduces a new methodology, noisy-HBN, driven by four-layer factors aggregated through the Internet of Vehicles (IoV), which integrates the Bayesian network with noisy nodes to assess the impact of unknown causes on SOTIF. To appraise the efficacy of this model, a new virtual data set, DADA-Plus, was developed, an extension of the open-source DADA data set, created using the twin scenario generation algorithm. The scenario-based verification underscores that the noisy-HBN model is adept at estimating the influence of unknown factors. Furthermore, the sensitivity analysis reveals that the known factors identified significantly correlate with the occurrence of accidents. Comparative analysis results show that the risk assessment coverage of the noisy-HBN has reached the state-of-the-art (SOTA) level.

Android is undergoing unprecedented malicious threats daily, but the existing methods for malware detection often fail to cope with evolving camouflage in malware. To address this issue, we present Hawk, a new malware detection framework for evolutionary Android applications. We model Android entities and behavioral relationships as a heterogeneous information network (HIN), exploiting its rich semantic meta-structures for specifying implicit higher order relationships. An incremental learning model is created to handle the applications that manifest dynamically, without the need for reconstructing the whole HIN and the subsequent embedding model. The model can pinpoint rapidly the proximity between a new application and existing in-sample applications and aggregate their numerical embeddings under various semantics. Our experiments examine more than 80 860 malicious and 100 375 benign applications developed over a period of seven years, showing that Hawk achieves the highest detection accuracy against baselines and takes only 3.5 ms on average to detect an out-of-sample application, with the accelerated training time of 50× faster than the existing approach.

There is a demand of high bandwidth in the emerging real-time applications, such as autonomous vehicles, robotics, and industrial automation, where time-sensitive networking (TSN) is a promising solution. According to IEEE 802.1, a port in a TSN switch has eight prioritized FIFO (first-in first-out) queues, whose gates are opened or closed following a gate control list (GCL). Most of the existing works use one TT (time-triggered) queue for the hard real-time traffic, i.e., traffic flows with hard deadlines, which easily achieves timing determinism through GCL. Unfortunately, as a rigid mechanism, GCL is not able to handle timing jitter. In this work, we propose a hybrid strategy towards robust TSN. GCL is applied to only one queue named TT T1 for a small number of hard real-time flows with negligible jitter. The remaining flows with hard deadlines are allocated to a prioritized queue named TT T2 without GCL. Similarly, GCL is removed from all other queues handling AVB (audio-video-bridging) flows with soft deadlines and BE (best-effort) flows with no deadlines. Two analyses are proposed to obtain delay bounds for the TT T2 flows and periodic AVB flows, respectively, with interference from TT T1. Although safety is not compromised if the periodic AVB flows miss their deadlines, it is often desirable in practice to satisfy them for quality of service. In order to strike a balance, contention between the AVB queues is resolved with credit values on top of priorities. Experiments support that the delay bounds for the TT T2 and AVB flows are safe. In addition, changing the credit function can lead to different delay bounds of AVB flows, which is valuable for real-world configurations of TSN.

Empowered with advanced computation units, autonomous sensing platforms and various wireless access capabilities, connected and autonomous vehicles evolve over time and become tightly coupled and closely cooperative. Being one of the most active research fields in both academic and industry, the Internet of Vehicles (IoV) enables various types of vehicular applications, such as autonomous driving, precise fleet management, and real-time video analytics, which contribute significantly to bring us traffic efficiency, driving safety, and ride comfort. However, these powerful applications always require intensive computation and very large size caching services under ultra-low latency constraints, and thus pose significant challenges on resource-constrained vehicles.

Nowadays we are witnessing the formation of a massive Internet-of-Things (IoT) ecosystem that integrates a variety of wireless-enabled devices ranging from smartphones, wearables, and virtual reality facilities to sensors, drones, and connected vehicles. As IoT is penetrating every aspect of people’s life, work, and entertainment, an increasing number of IoT devices and the emerging IoT applications are driving exponential growth in wireless traffic in the foreseeable future. As a result, current IoT system architectures are facing significant challenges to handle millions of devices; thousands of servers; the transmission and processing of large volume of data, etc.

Empowered with urban informatics, transportation industry has witnessed a paradigm shift. These developments lead to the need of content processing and sharing between vehicles under strict delay constraints. Mobile edge services can help meet these demands through computation offloading and edge caching empowered transmission, while cache-enabled smart vehicles may also work as carriers for content dispatch. However, diverse capacities of edge servers and smart vehicles, as well as unpredictable vehicle routes, make efficient content distribution a challenge. To cope with this challenge, in this article we develop a social-aware nobile edge computing and caching mechanism by exploiting the relation between vehicles and roadside units. By leveraging a deep reinforcement learning approach, we propose optimal content processing and caching schemes that maximize the dispatch utility in an urban environment with diverse vehicular social characteristics. Numerical results based on real urban traffic datasets demonstrate the efficiency of our proposed schemes.

Along with an integration of wearable devices, wireless communications and big data in the smart health, biomedical data is collected referring to multiple associated patients during interactions. Due to communication channel openness and data sensibility, privacy preservation become increasingly noteworthy in the edge and cloud hybrid computing-based healthcare applications. In this paper, a cooperative privacy preservation scheme is designed for wearable devices with identity authentication and data access control considerations in the space-aware and time-aware contexts. In the space-aware edge computing mode, secret sharing and MinHash-based authentication is designed to enhance privacy preservation along with similarity computing without revealing sensitive data. In the time-aware cloud computing mode, ciphertext policy attribute-based encryption is applied for fine-grained access control, and bloom filter is used to achieve efficient data structure without privacy exposure. The GNY logic-based security formal analysis is performed to prove theoretical correctness, and the proposed scheme achieves cooperative privacy preservation for wearable devices in smart health with communication overhead and computation cost.

In order to meet low latency, service sensitive and location awareness requirements of digital manufacturing, fog computing is introduced to be an intermediate layer between industrial Internet of Things and cloud. The distributed, dynamic characteristics and the collaboration requirement make it face many new security and privacy issues that cannot be solved by the traditional public key or symmetric cryptosystem. For addressing them, a registered but anonymous attribute credential is designed to manage the network entities. Based on it, an attribute credential based public key cryptography (AC-PKC) is constructed to provide flexible key management by taking the advantage of the certificate-less public key cryptography and the combination property of the elliptic curve cryptography. Encryption, authentication, and access control with privacy preserving can be realized on the basic operations of AC-PKC, which can meet various security requirements of fog computing based digital manufacturing. The performance analyses and comparison with the existing public key schemes and attribute based encryption solutions show that the proposed scheme can work flexibly at a relatively low cost.

Cyberspace is a new basic space after the three traditional basic spaces-physical, social, and thinking spaces (PST spaces). It is a trend that entities (objects) and PST spaces they are living in to be cyberized. On the one hand, the rapidly developing of cyberspace has the increasingly significant influences to PST spaces. On the other hand, the cyberization of objects in PST spaces have been continuously deepening and strengthening. Cyberization leads to the convergence of the four basic spaces, which also called cyberspace and cyber-enabled physical-social-thinking spaces (CPST spaces). In recent years, the philosophy research on CPST spaces and objects (short for cyber philosophy) has been developing rapidly while some researchers try to figure cyber science and its fundamental issues. Up to now, the bridge, fundament logic from cyber philosophy to cyber science, has not yet formed. This paper proposes a new concept of “cyberlogic” for establishing a bridge from cyber philosophy to cyber science. The etymology, concept, contents, and methods of cyberlogic are presented, and the cyberlogic for the CPST spaces is shown. Moreover, main issues and methodologies for cyberlogic are discussed.

Cloud computing is an emerging data interactive paradigm to realize users’ data remotely stored in an online cloud server. Cloud services provide great conveniences for the users to enjoy the on-demand cloud applications without considering the local infrastructure limitations. During the data accessing, different users may be in a collaborative relationship, and thus data sharing becomes significant to achieve productive benefits. The existing security solutions mainly focus on the authentication to realize that a user’s privative data cannot be illegally accessed, but neglect a subtle privacy issue during a user challenging the cloud server to request other users for data sharing. The challenged access request itself may reveal the user’s privacy no matter whether or not it can obtain the data access permissions. In this paper, we propose a shared authority based privacy-preserving authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access authority is achieved by anonymous access request matching mechanism with security and privacy considerations (e.g., authentication, data anonymity, user privacy, and forward security); 2) attribute based access control is adopted to realize that the user can only access its own data fields; 3) proxy re-encryption is applied to provide data sharing among the multiple users. Meanwhile, universal composability (UC) model is established to prove that the SAPA theoretically has the design correctness. It indicates that the proposed protocol is attractive for multi-user collaborative cloud applications.

The Internet of Things (IoT) is becoming an attractive system paradigm to realize interconnections through the physical, cyber, and social spaces. During the interactions among the ubiquitous things, security issues become noteworthy, and it is significant to establish enhanced solutions for security protection. In this work, we focus on an existing U2IoT architecture (i.e., unit IoT and ubiquitous IoT), to design an aggregated-proof based hierarchical authentication scheme (APHA) for the layered networks. Concretely, 1) the aggregated-proofs are established for multiple targets to achieve backward and forward anonymous data transmission; 2) the directed path descriptors, homomorphism functions, and Chebyshev chaotic maps are jointly applied for mutual authentication; 3) different access authorities are assigned to achieve hierarchical access control. Meanwhile, the BAN logic formal analysis is performed to prove that the proposed APHA has no obvious security defects, and it is potentially available for the U2IoT architecture and other IoT applications.

Vehicle-to-grid (V2G), involving both charging and discharging of battery vehicles (BVs), enhances the smart grid substantially to alleviate peaks in power consumption. In a V2G scenario, the communications between BVs and power grid may confront severe cyber security vulnerabilities. Traditionally, authentication mechanisms are solely designed for the BVs when they charge electricity as energy customers. In this paper, we first show that, when a BV interacts with the power grid, it may act in one of three roles: 1) energy demand (i.e., a customer); 2) energy storage; and 3) energy supply (i.e., a generator). In each role, we further demonstrate that the BV has dissimilar security and privacy concerns. Hence, the traditional approach that only considers BVs as energy customers is not universally applicable for the interactions in the smart grid. To address this new security challenge, we propose a role-dependent privacy preservation scheme (ROPS) to achieve secure interactions between a BV and power grid. In the ROPS, a set of interlinked subprotocols is proposed to incorporate different privacy considerations when a BV acts as a customer, storage, or a generator. We also outline both centralized and distributed discharging operations when a BV feeds energy back into the grid. Finally, security analysis is performed to indicate that the proposed ROPS owns required security and privacy properties and can be a highly potential security solution for V2G networks in the smart grid. The identified security challenge as well as the proposed ROPS scheme indicates that role-awareness is crucial for secure V2G networks.

Along with radio frequency identification (RFID) becoming ubiquitous, security issues have attracted extensive attentions. Most studies focus on the single-reader and single-tag case to provide security protection, which leads to certain limitations for diverse applications. This paper proposes a grouping-proofs-based authentication protocol (GUPA) to address the security issue for multiple readers and tags simultaneous identification in distributed RFID systems. In GUPA, distributed authentication mode with independent subgrouping proofs is adopted to enhance hierarchical protection; an asymmetric denial scheme is applied to grant fault-tolerance capabilities against an illegal reader or tag; and a sequence-based odd-even alternation group subscript is presented to define a function for secret updating. Meanwhile, GUPA is analyzed to be robust enough to resist major attacks such as replay, forgery, tracking, and denial of proof. Furthermore, performance analysis shows that compared with the known grouping-proof or yoking-proof-based protocols, GUPA has lower communication overhead and computation load. It indicates that GUPA realizing both secure and simultaneous identification is efficient for resource-constrained distributed RFID systems.

SUMMARY The open radio frequency identification (RFID) air interface may suffer from severe threats that make security problem become a critical issue for RFID systems and applications. This paper proposes a dual cryptography authentication protocol (DCAP) for RFID systems. DCAP partitions randomly the tag identifier into two partial identifiers that are used in the forward link and in the backward link, respectively. The protocol applies hash function and shared‐key encryption algorithm to safeguard both forward and backward links and provides a three‐round authentication mode on each tag and reader in a session. Then, authentication is carried out by the primary, secondary, and final verifications. For a formal analysis, a graphical method Colored Petri Nets is applied to model and analyze the correctness of DCAP. We prove that the protocol owns tag anonymity and forward security and has the capability to resist major attacks such as replay, reader forgery, and tag forgery. Finally, the performance in terms of storage, communication overhead, and computation load is evaluated to demonstrate that the protocol has modest complexity and high efficiency. Copyright © 2011 John Wiley & Sons, Ltd.