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security analysis and secured access design for networks of image remote sensing

Digital Communications and networks 2025年第1期11卷 136-144页

作者： Juan Zhao Haibo Dai Xiaolong Xu Hao Yan Zheng Zhang Chunguo Li School of Network Security Jinling Institute of TechnologyNanjing 211169China School of IoT Nanjing University of Posts and Telecommunications(NJUPT)Nanjing 210003China Jiangsu Key Lab.of Big Data Security and Intelligent Processing NJUPTNanJing 210003China School of Information Science and Engineering Southeast UniversityNanjing 210096China

The secured access is studied in this paper for the network of the image remote *** sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection *** order to enhance the sensing quality for the remote uploading,the passive reflection surface technique is *** one eavesdropper that exists nearby this sensor is keeping on accessing the same networks,he may receive the same image from this *** goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing *** order to achieve this goal,the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading *** on this theoretical result,the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper ***,the analytical expression is theoretically derived for the optimum uploading *** simulations verify the design approach.

关键词： Image remote sensing Secured access Energy efficiency Sensor transmit power Secured access design

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CYBERSHIELD: A Competitive Simulation Environment for Training AI in Cybersecurity 11

CYBERSHIELD: A Competitive Simulation Environment for Traini...

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11th International Conference on Internet of Things: Systems, Management and security, IOTSMS 2024

作者： Carrasco, José Álvaro Fernández Pagola, Iñigo Amonarriz Urrutia, Raúl Orduna Román, Rodrigo San Sebastian Donostia20009 Spain University of Malaga Network Information and Computer Security Lab Malaga29071 Spain

ISBN: (纸本)9798350366501

Simulation environments are crucial in cybersecurity for training AI algorithms, providing a secure and controlled space to explore the impact derived from diverse cyber threads. They offer a flexible platform for accelerated learning and development, especially useful to train Decision Support Systems in response contexts. This paper introduces CyberShield, an advanced simulation environment tailored for cybersecurity tasks, specifically focusing on supporting the implementation and evaluation of AI algorithms, with an emphasis on RL. CyberShield encompasses a comprehensive environment with multiple computers, each hosting various services with unique vulnerabilities. Within this environment, two opposing agents, defender and attacker, participate in a strategic battle, each equipped with distinct actions aimed at outsmarting the other. CyberShield is optimized for competitive multi-agent training using RL algorithms. The specifically adapted environment facilitates the exploration of novel strategies, thereby fostering the automation of defense and attack strategies. Taking inspiration from Capture The Flag (CTF) competitions, CyberShield offers a dynamic and realistic platform for refining advanced cybersecurity techniques, fostering innovation, and strengthening the resilience of AI algorithms against sophisticated cyber threats. © 2024 IEEE.

关键词： Chatbots

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Enhancing TrUStAPIS Methodology in the Web of Things with LLM-Generated IoT Trust Semantics 26th

Enhancing TrUStAPIS Methodology in the Web of Things with LL...

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26th International Conference on information and Communications security, ICICS 2024

作者： Ferraris, Davide Kotis, Konstantinos Kalloniatis, Christos Network Information and Computer Security Lab University of Malaga Malaga Spain Department of Cultural Technology and Communication University of the Aegean Mytilene Greece

ISBN: (纸本)9789819787975

In the Internet of Things (IoT) there are ecosystems where their physical’smart’ entities virtually interact with each other. Often, this interaction occurs among unknown entities, making trust an essential requirement to overcome uncertainty in several aspects of this interaction. However, trust is a complex concept, and incorporating it in IoT is still a challenging topic. For this reason, it is highly significant to specify and model trust in early stages of the System Development Life Cycle (SDLC) of IoT-integrated systems, thus enhancing the aforementioned task. TrUStAPIS is a requirements engineering methodology recently introduced for incorporating trust requirements during IoT-based system design. The scope of this paper is to provide an extension of TrUStAPIS by introducing IoT trust semantics compatible with the W3C Web of Things (WoT) recommendations generated with the assistance of Large Language Models (LLMs). Taking advantage of LLMs as a tool for integrating and refining existing methodologies, in this paper we present our work towards a revision of the TrUStAPIS methodology. In this work, we contribute a new conceptual model and a refined JSON-LD ontology that takes into account IoT trust semantics, providing eventually a valuable tool for software engineers to design and model IoT-based systems and services. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Requirements engineering

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New results on quantum boomerang attacks

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Quantum information Processing 2023年第4期22卷 1-27页

作者： Zou, Hongkai Zou, Jian Luo, Yiyuan College of Computer and Data Science Fuzhou University Fuzhou China Key Lab of Information Security of Network Systems Fuzhou University Fuzhou China School of Information Sciences and Technology Huizhou University Huizhou China

At SAC 2021, Frixons et al. proposed quantum boomerang attacks that can effectively recover the keys of block ciphers in the quantum setting. Based on their work, we further consider how to quantize the generic boomerang attacks proposed by Biham et al. at FSE 2002, so as to obtain more generic quantum boomerang attacks. Similar to Frixons et al.’s work, we only consider quantum key recovery attacks in the single-key setting. With the help of some famous quantum algorithms, this paper presents two methods to convert the attacks of Biham et al. into some new quantum key recovery attacks. In order to proof our methods, we apply our new ideas to attack Serpent-256 and ARIA-196. To sum up, for Serpent-256, we give valid 9-round and 10-round quantum key recovery attacks respectively. The quantum time complexity of 9-round and 10-round of Serpent-256 is 2 115.43 and 2 126.6 respectively. Furthermore, we show a valid quantum key attack on 6-round ARIA-196 which has a time complexity of 2 89.8 with negligible memory. The time complexity of the above quantum attacks are better than the corresponding classical attacks and quantum generic key recovery attack via Grover’s algorithm. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Quantum theory

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Integration of MPC into Besu through an extended private transaction model

Integration of MPC into Besu through an extended private tra...

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2023 IEEE International Conference on Metaverse Computing, networking and Applications, MetaCom 2023

作者： Morales, Daniel Agudo, Isaac Lopez, Javier Itis Software Universidad de Málaga Network Information and Computer Security Lab Department of Computer Science Málaga Spain

ISBN: (纸本)9798350333336

In the last few years we have seen many different approaches to incorporate privacy features to blockchains. In the area of cryptocurrencies that would normally mean protecting the identity of the owner of some funds, but there are other applications where privacy is even more important, especially in permissioned blockchains. Permissioned blockchain platforms, such as Hyperledger Besu or Hyperledger Fabric, already include the concept of private transactions, which essentially defines a sub-group of the blockchain where their participants share some private data. We want to go one step ahead and propose an extended model for private transactions where the different participants can have a separated view of the same transaction, allowing the integration of Multi-party Computation protocols in the blockchain. Our work extends Hyperledger Besu's design for private transactions, offering better security properties and a finer grain customization. We cover two specific MPC examples, Private Set Intersection and Byzantine Fault-Tolerant Random Number Generation, and propose a mechanism to run them using smart contract interfaces. © 2023 IEEE.

关键词： Blockchain

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Toward data privacy preservation with ciphertext update and key rotation for IoT

Toward data privacy preservation with ciphertext update and ...

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作者： Shen, Shuaiyong Yang, Yang Liu, Ximeng College of Mathematics and Computer Science Key Lab of Information Security of Network Systems Fuzhou University Fujian Fuzhou China

Fine-grained access control become a research spotlight in the scenario of the smart home with Internet-of-Things (IoTs). However, most of the existing works could only realize ciphertext outsourcing with an unchangeable encryption key in the cloud. That is because the trivial solution needs great communication overhead. To overcome this challenge, we propose an updatable encryption based on SM9 (SM9-UE) scheme for the IoT smart home scenario, where SM9 is an identity and cryptographic standard adopted by GM/T0044. SM9-UE realizes secure and lightweight ciphertext updating through using the token generated by the data owner, which is information independent with the plaintext. We give the formal security definition and prove it to be adaptive update indistinguishability (IND-UPD) secure. Theoretical comparison and analysis show that our scheme is efficient in computation and storage overhead. Experimental results also indicate that SM9-UE can be practically applied to IoT smart home. © 2021 John Wiley & Sons Ltd.

关键词： Internet of things

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Task Offloading and Resource Allocation Based on Reinforcement Learning and Load Balancing in Vehicular networking

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IEEE Transactions on Consumer Electronics 2025年第1期71卷 2217-2230页

作者： Tian, Shujuan Xiang, Shuhuan Zhou, Ziqi Dai, Haipeng Yu, Enze Deng, Qingyong Xiangtan University Key Laboratory of Hunan Province for Internet of Things and Information Security Hunan International Scientific and Technological Cooperation Base of Intelligent network School of Computer Science and School of Cyberspace Security Xiangtan411105 China Nanjing University School of Computer Science and Technology Nanjing211189 China Guangxi Normal University Key Lab of Education Blockchain and Intelligent Technology Ministry of Education Guilin541004 China Guangxi Normal University Guangxi Key Lab of Multi-source Information Mining and Security Guilin541004 China

Due to limited on-board resources and the mobility characteristics of vehicles in a multi-access edge computing (MEC)-based vehicular network, efficient task offloading and resource allocation schemes are essential for achieving low-latency and low-energy consumption applications in the Internet of Vehicles (IoV). The spatial distribution of vehicles, influenced by various factors, leads to significant workload variations across MEC servers. In this paper, we address task offloading and resource allocation as a joint optimization problem and propose a Load-Balancing Deep Deterministic Policy Gradient (LBDDPG) algorithm to achieve optimal results. The joint optimization problem is modeled as a Markov Decision Process (MDP), enabling the LBDDPG algorithm to systematically address the challenges of workload imbalance and resource inefficiency. The algorithm incorporates a load optimization strategy to balance workload distribution across MEC servers, mitigating disparities caused by uneven vehicle distributions. The reward function is designed to account for both energy consumption and delay, ensuring an optimal trade-off between these critical factors. To enhance training efficiency, a noise-based exploration strategy is employed, preventing ineffective exploration during the early stages. Additionally, constraints such as computational capacity and latency thresholds are embedded to ensure the algorithm's practical applicability. Experimental results demonstrate that the proposed LBDDPG algorithm achieves faster convergence and superior performance in terms of energy consumption and latency compared to other reinforcement learning algorithms. © 1975-2011 IEEE.

关键词： Markov processes

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EVPIR: Efficient and Verifiable Privacy-Preserving Image Retrieval in Cloud-assisted Internet of Things

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IEEE Internet of Things Journal 2025年第13期12卷 24259-24274页

作者： Li, Mingyue Li, Yuntao Du, Ruizhong Jia, Chunfu Shao, Wei Hebei University School of Cyber Security and Computer Baoding071000 China Key Lab on High Trusted Information Sys tem in Hebei Province Hebei China College of Cyber Sciences Nankai university Tianjin300350 China Tianjin Key Laboratory of Network and Data Security Technology Tianjin300350 China Jinan250014 China

With the proliferation of mobile devices and the advancement of cloud computing capabilities, cloud-assisted Internet of Things (IoT) attracts increased attention based on its computational and storage advantages. Upon these conveniences, there also raises privacy concerns that numerous solutions have been proposed to solve it. However, existing methods suffer from challenges such as low retrieval accuracy, inefficiency in large-scale image retrieval, and lack of efficient result verification. In this paper, we propose an Efficient Verifiable Privacy-preserving Image Retrieval scheme (EVPIR). Specifically, we design a hierarchical graph index to significantly enhance retrieval efficiency, which organizes image feature vectors into a multi-level structure, establishing connections between neighboring nodes within each layer and creating a highly structured and efficient retrieval framework. During the retrieval process, we employ greedy search algorithm to navigate these connections and identify the closest neighbors across different levels, which make the proposed multi-level approach reduce the search space at each level, achieving faster and more accurate retrieval. Furthermore, we design an efficient dynamic verifiable framework leveraging Chameleon hash functions and BLS signatures where we utilize Chameleon hash nodes based on Merkle Hash Trees (MHT) to enable dynamic updates of the verification tree and employ BLS signatures to construct multiple verification nodes for effectively shortening the verification path. Finally, security analysis shows that EVPIR can defend various threat models and extensive experiments further demonstrates that EVPIR can improve retrieval and verification efficiency. (Figure presented) © 2014 IEEE.

关键词： Differential privacy

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STGAT: A Spatio-Temporal Graph Attention network for Travel Demand Prediction

STGAT: A Spatio-Temporal Graph Attention Network for Travel ...

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2023 International Conference on networking and network Applications, NaNA 2023

作者： Zhang, Tao Yi Wang, YuBo Wei, ZhiCheng Key Lab of Network and Information Security China College of Computer and Cyberspace Security China Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Security Hebei Normal University Hebei Province Shijiazhuang China

ISBN: (纸本)9798350327380

Forecasting travel demand is a challenging task due to the complex spatial dependencies and dynamic temporal correlation of the traffic data. Furthermore, a limited representation of the given spatial graph structure may restrict the model's ability to effectively learn spatial-temporal dependencies. To extract latent semantic features from traffic data, this paper proposes a method to construct a traffic graph using the Markov cluster algorithm. The traffic semantic correlation matrix is constructed based on a traffic graph to obtain the deep semantic information. Specifically, this study proposes a Spatio-Temporal Graph Attention network(STGAT) for travel demand prediction. STGAT uses a graph attention layer based on the Node2Vec graph embedding algorithm, two convolutional layers based on the Markov cluster algorithm, and a long short-term memory network to capture spatial-temporal dependencies. Experimental results on the NYC Taxi dataset and the Chengdu online car dataset demonstrate that STGAT achieved state-of-the-art performance compared to other baseline models. © 2023 IEEE.

关键词： Forecasting

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A Caching Strategy Based on Many-to-Many Matching Game in D2D networks

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Tsinghua Science and Technology 2021年第6期26卷 857-868页

作者： Kaihang Yu Zhonggui Ma Runyu Ni Tao Zhang School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Key Lab of Information Network Security Ministry of Public SecurityShanghai 201204China

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

关键词： caching strategy Device-to-Device(D2D)networks Gauss determinantal point process many-to-many matching game

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