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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Zhou, Lingyun Ning, Xinzhi You, Ming-Yi Zhang, Rongqing Shi, Qingjiang Department of Hubei Key Laboratory of Intelligent Wireless Communications Hubei Engineering Research Center of Intelligent Internet of Things Technology College of Electronics and Information Engineering South-Central Minzu University Wuhan China School of Software Engineering Tongji University Shanghai China National Key Laboratory of Electromagnetic Space Security No.36 Research Institute of CETC Jiaxing China

Unmanned aerial vehicle (UAV) swarm-based localization technology has become increasingly popular due to its exceptional maneuverability, versatile coverage capabilities, and reliable line-of-sight (LoS) connectivity. However, the accuracy improvement by exploiting UAVs' placement poses a new challenge on multi-UAV localization system. This paper investigates the placement optimization problem for a multi-UAV localization network, where each UAV is equipped with a uniform circular array (UCA) to locate the target by adopting the angle-ofarrival (AOA) measurement. To measure the accuracy of the UCA-based localization system, we characterize the measurement error to be dependent on target-to-UAV distance and present a comprehensive derivation of the Cramer-Rao lower bound ´ (CRLB). Next, we formulate the problem as a non-convex semi-infinite optimization, aiming to minimize the worst-case squared position error bound (SPEB) by designing the robust placement strategy under some stringent geometric position constraints. We address this problem by alternatively solving two sub-problems, corresponding to a slave problem for calculating the worstcase SPEB of the uncertainty region under a fixed deployment of UAVs, as well as a master problem for optimizing UAVs' placement. By virtue of the particular problem structure, we develop the gradient projection-based method for the slave problem. Meanwhile, considering the lack of a closed expression for the maximum SPEB concerning UAVs' deployment in the master problem, we devise an iterative algorithm to acquire an efficient solution with the aid of Gibbs Sampling approach. Extensive simulation results demonstrate the efficacy of the proposed algorithms. IEEE

关键词： Unmanned aerial vehicles (UAV)

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Direct-Unitary MUSIC: A Real-Valued Method for Co-Array-Based Direction-of-Arrival Estimation

Direct-Unitary MUSIC: A Real-Valued Method for Co-Array-Base...

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2024 OES China Ocean Acoustics, COA 2024

作者： Song, Guangming Qu, Xinghao Shang, Zhigang Qiao, Gang Li, Tianshui School of Aerospace Engineering China Harbin Engineering University National Key Laboratory of Underwater Acoustic Technology Harbin150001 China Ministry of Industry and Information Technology Key Laboratory of Marine Information Acquisition and Security Harbin150001 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China Eastern Theater Naval Security Department Immediate Security Unit Unit 91007 China Naval Research Institute China

ISBN: (纸本)9798350340297

Spatial smoothing (SS) has become a common technique targeted at direction-of-arrival estimation based on sparse linear arrays, which rearranges the corresponding co-array model to favor subspace methods. This paper provides the insight that the resulting matrix will possess the centro-Hermitian structure. To fully leverage this underlying property, we directly apply unitary transformation to the structured matrix and propose a real-valued subspace algorithm called direct-unitary MUSIC (DU-MUSIC). The crucial advantage of DU-MUSIC is that the steps of eigendecomposition and spectrum search can be performed in the real domain. Furthermore, such computational convenience will not compromise the algorithm performance. Analytical derivations and simulations verify the equivalence of DU-MUSIC and the classical SS-based MUSIC in terms of spatial spectrum performance. © 2024 IEEE.

关键词： Direction of arrival

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Transformation Method from AltaRica3.0 to SBIP model

Transformation Method from AltaRica3.0 to SBIP model

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2022 International Conference on Signal Processing, Computer Networks, and Communications, SPCNC 2022

作者： He, Hongbin Yang, Lin Zhang, Long Yang, Feng National Key Laboratory of Science and Technology on Information System Security Systems Engineering Institute Academy of Military Sciences Beijing100141 China

ISBN: (纸本)9781510664616

In order to provide reliability and safety assessments for safety-critical systems, Model-Based Safety Analysis (MBSA) methods have been developed, of which AltaRica3.0 is one representative method. However, there are still several limitations. The most important one is its inability to verify system behaviors when the system has stochastic behaviors. As a widely used safety analysis and evaluation software, SBIP is an emphasis on formal modeling and statistical analysis of safety-critical systems exhibiting stochastic behaviors. In this paper, we present a transformation approach that integrates the advantages of AltaRica3.0 and SBIP, realizes the function of conducting multiple analyses by modeling the system only once, reduces the modeling cost of safety-critical systems, and improves the reliability and safety analysis efficiency of safety-critical systems. © 2023 SPIE.

关键词： Reliability analysis

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Secure RFID-Assisted Authentication Protocol for Vehicular Cloud Computing Environment

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IEEE Transactions on Intelligent Transportation Systems 2024年第9期25卷 12528-12537页

作者： Saleem, Muhammad Asad Li, Xiong Mahmood, Khalid Tariq, Tayyaba Alenazi, Mohammed J. F. Das, Ashok Kumar University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Institute for Cyber Security School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Sichuan University Key Laboratory of Data Protection and Intelligent Management Ministry of Education Chengdu610065 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518000 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Yunlin Douliu64002 Taiwan King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500032 India

Vehicular network technology has made substantial advancements in recent years in the field of Intelligent Transportation Systems. Vehicular Cloud Computing (VCC) has emerged as a novel paradigm with a substantial increase in data exchange within Vehicular ad-hoc networks (VANETs). VCC integrates cloud computing, vehicular networking, and Internet of Things (IoT) technologies. It enables Infrastructure-to-Vehicle (I2V), Vehicle-to-Vehicle (V2V), and Vehicle-to-Device (V2D) communication. VCC optimizes vehicle, cloud infrastructure, and IoT resources while addressing significant communication security and vehicle-user privacy challenges. To address these issues, we developed an RFID-based authentication protocol for VCC based on a Henon map using a hash function. In addition, we also incorporated a Physical Unclonable Function (PUF) to resist physical tampering attacks. We validate the protocol's security formally and informally. The formal security analysis is conducted through a widely used RoR model. We use the Scyther simulation tool to verify the proposed protocol's security against various attacks. Moreover, we compare the performance of our protocol with similar existing protocols across important performance parameters such as communication and computation overheads and security attributes. The proposed protocol yields substantial improvements, demonstrating a 40.74% reduction in computation overhead and a 13.03% decrease in communication overhead as compared to related protocols, delivering both enhanced performance and resource efficiency. The analysis demonstrates its capacity to support secure communication in the VCC environment and satisfy desirable security attributes. © 2024 IEEE.

关键词： Authentication

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Segmenting foreground objects in a multi-modal background using modified Z-score

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Journal of Ambient Intelligence and Humanized Computing 2024年第2期15卷 1213-1227页

作者： Choudhury, Suman Kumar Sa, Pankaj Kumar Choo, Kim-Kwang Raymond Bakshi, Sambit Department of Computer Science and Engineering National Institute of Technology Rourkela Rourkela India Department of Information Systems and Cyber Security The University of Texas at San Antonio San AntonioTX78249 United States School of Information Technology and Mathematical Sciences University of South Australia AdelaideSA5095 Australia

This article presents a background subtraction method to detect moving objects across a stationary camera view. A hybrid pixel representation is presented to minimize the effect of shadow illumination. A non-recursive background model is developed to address the problem with gradual illumination change. Modified Z-score labeling is employed to analyze the sample variation of the temporal sequence to build a multi-modal background. The same measure is further applied to detect the foreground pixels against the stationary background classes. Morphological filtering is employed to suppress the sensor noise as well as to fill the camouflage holes. A decision rule is formulated that considers the period of being stationary of a foreground object and the period of being absence of a background class to tackle the object relocation problem. The proposed approach along with nine other state-of-the-art methods are compared on various image sequences taken from the Wallflower and the I2R datasets in terms of recall, precision, figure of merit, and percentage of correct classification. The tabular results, as well as the obtained figures demonstrate the efficacy of the proposed scheme over its counterparts. © Springer-Verlag Berlin Heidelberg 2017.

关键词： Object detection

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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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Green Energy and Intelligent Transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad Asad Mujeeb Imran Khan Mirani Muhammad Hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN Green transportation Hybrid model Intelligent transportation K-means

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Driving into Danger: Adversarial Patch Attack on End-To-End Autonomous Driving Systems Using Deep Learning 28

Driving into Danger: Adversarial Patch Attack on End-To-End ...

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28th IEEE Symposium on Computers and Communications, ISCC 2023

作者： Wang, Tong Kuang, Xiaohui Li, Hu Du, Qianjin Hu, Zhanhao Deng, Huan Zhao, Gang Institute of System Engineering Academy of Military Sciences Beijing China National Key Laboratory of Science and Technology on Information System Security Beijing China

ISBN: (纸本)9798350300482

Deep learning-based autonomous driving systems have been extensively researched due to their superior performance compared to traditional methods. Specifically, end-To-end deep learning systems have been developed, which directly output control signals for vehicles using various sensor inputs. However, deep learning techniques are vulnerable to security issues, generating adversarial examples that can attack the output of the relevant model. This paper proposes an adversarial example generation method that applies a patch to pedestrians' clothing, which can generate dangerous behaviors when the pedestrian appears within the camera lens, thereby attacking the end-To-end autonomous driving system. The proposed method is validated using the CARLA simulator, and the results demonstrate successful attacks in various weather and lighting conditions, exposing the security vulnerabilities of this type of system. This study highlights the need for further research to address these vulnerabilities and ensure the safety of autonomous driving systems. © 2023 IEEE.

关键词： Deep learning

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SP-SLAM: Neural Real-Time Dense SLAM With Scene Priors

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IEEE Transactions on Circuits and Systems for Video technology 2025年第6期35卷 5182-5194页

作者： Hong, Zhen Wang, Bowen Duan, Haoran Huang, Yawen Li, Xiong Wen, Zhenyu Wu, Xiang Xiang, Wei Zheng, Yefeng The Institute of Cyberspace Security College of Information Engineering Zhejiang University of Technology Hangzhou310023 China Department of Automation Tsinghua University China Tencent Jarvis Lab Shenzhen518057 China The School of Engineering and Mathematical Sciences La Trobe University MelbourneVIC3086 Australia The Medical Artificial Intelligence Laboratory Westlake University Hangzhou310030 China

Neural implicit representations have recently shown promising progress in dense Simultaneous Localization And Mapping (SLAM). However, existing works have shortcomings in terms of reconstruction quality and real-time performance, mainly due to inflexible scene representation strategy without leveraging any prior information. In this paper, we introduce SP-SLAM, a novel neural RGB-D SLAM system that performs tracking and mapping in real-time. SP-SLAM computes depth images and establishes sparse voxel-encoded scene priors near the surface reconstruction. Simultaneously, we employ triplanes to store scene appearance information, striking a balance between achieving high-quality geometric texture mapping and minimizing memory consumption. Furthermore, in SP-SLAM, we introduce an effective optimization strategy for mapping, allowing the system to continuously optimize the poses of all historical input frames during runtime without increasing computational overhead. We conduct extensive evaluations on five benchmark datasets (Replica, ScanNet, TUM RGB-D, Synthetic RGB-D, 7-Scenes). The results demonstrate that, compared to existing methods, we achieve superior tracking accuracy and reconstruction quality, while running at a significantly faster speed. © 1991-2012 IEEE.

关键词： Mapping

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A Robust Key Exchange and Tamper-Resistant Protocol for HAN and NAN Networks in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21394-21403页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Shamshad, Salman Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China

Smart Grids (SG) rely on Home Area Networks (HAN) and Neighborhood Area Networks (NAN) to ensure efficient power distribution, real-time monitoring, and seamless communication between smart devices. Despite these advantages, the use of public communication channels in HAN and NAN networks introduces critical challenges, such as vulnerability to impersonation, physical tampering, and scalability issues in resource-constrained environments. These issues compromise the stability, reliability, and security of SG environments. Existing protocols often fail to adequately address these challenges, particularly in ensuring resistance to physical tampering of supply lines and impersonation attacks. Additionally, they struggle to minimize the computation, communication, and energy costs associated with securing a resource-constrained SG environment. Therefore, we propose a robust key exchange and tamper-resistant protocol for HAN and NAN networks to address these limitations. The proposed protocol leverages the Physical Unclonable Function (PUF) mechanism to offer physical tampering resistance to smart meters. We validate our protocol formally using the Random or Real (RoR) model, which confirms its security robustness. Additionally, our informal security analysis highlights the protocol's resilience against impersonation, physical tampering attacks, etc. We analyze and compare the performance of the proposed protocol, which further demonstrates our protocol's effectiveness and security compared to competing protocols. Moreover, the proposed protocol achieves resource efficiency with 45.99% and 58.85% substantial reductions in computation overhead and energy overhead, respectively, compared to competing protocols. These results showcase the protocol's enhanced security and practicality for resource-constrained SG environments. © 2014 IEEE.

关键词： Authentication Protocol

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Provably Secure Efficient Key-Exchange Protocol for Intelligent Supply Line Surveillance in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21784-21792页

作者： Ayub, Muhammad Faizan Li, Xiong Mahmood, Khalid Alenazi, Mohammed J.F. Das, Ashok Kumar Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Sichuan Chengdu12599 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan Department of Computer Engineering Riyadh11451 Saudi Arabia International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University College of Informatics Department of Computer Science and Engineering Anam-ro Seoul145 Korea Republic of Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security China Shandong Fundamental Research Center for Computer Science Jinan 250353 China

Intelligent supply line surveillance is critical for modern smart grids. Smart sensors and gateway nodes are strategically deployed along supply lines to achieve intelligent surveillance. They collect data continuously and transmit it to the control centre in real-time. It enables real-time monitoring, fault detection, and efficient energy management across distribution networks. This advanced surveillance system ensures continuous monitoring of supply lines, detecting anomalies, and optimizing operations to maintain the stability and reliability of the smart grid. However, the reliance of all participating nodes on public communication channels to transmit supply line surveillance data exposes these systems to critical cyber attacks. These cyber attacks include impersonation, physical tampering, ephemeral secret leakage, and desynchronization attacks. To address these issues, existing key-exchange protocols often fail to ensure robust security while imposing high computation and communication overheads, limiting their practicality for resource-constrained environments. Therefore, we propose a secure and efficient key exchange and tamper-resistant authentication protocol using Elliptic Curve Cryptography (ECC) and Physical Unclonable Functions (PUFs). The PUF mechanism provides robust resistance against physical tampering and cloning attacks, ensuring enhanced physical security for supply line devices. We validate the security robustness of the devised protocol using the Random or Real (ROR) model. Furthermore, informal security analysis demonstrates the protocol's robustness in rigorously resisting various attacks, including physical tampering, impersonation, ephemeral secret leakage and desynchronization. Moreover, we determine the performance evaluation that reveals the protocol's superior efficiency compared to competing protocols, achieving significant reductions of 28.64% in computation overhead and 9.96% in communication overhead. © 2014 IEEE.

关键词： Authentication Protocol

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