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检索条件"任意字段=14th ACM Conference on Computer and Communication Security"

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Real-Time Secure Video Streaming System Based on FPGA and CUDA Technology 24

Real-Time Secure Video Streaming System Based on FPGA and CU...

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Liu, Ziyang Wang, Zongxia Tu, Shanshan Wang, Haoran Fan, Jingxuan Ren, Chang College of Computer Science Beijing University of Technology Beijing China The 6th Research Institute of China Electronics Corporation China Electronics Corporation Bejing China

ISBN: (纸本)9798400717994

In recent years, with the growing demand for real-time video transmission, ensuring the security of video stream data has become critical. this paper addresses the secure transmission of real-time video streams by using FPGA technology on the encryption side, where the SM4 algorithm is applied, and GPU-based CUDA acceleration on the decryption side. A simplified transmission protocol ensures both real-time performance and security. the system, tested on a Nexys A7 board and PC, achieved a frame rate of 27.78 fps, demonstrating its potential in applications such as drone video security, surveillance, and intelligent transportation systems. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Video streaming

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Intrusion Detection in IIoT: A Federated Approach Using TCN-GRU and Lookahead Optimization 24

Intrusion Detection in IIoT: A Federated Approach Using TCN-...

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Wang, Haoran Tu, Shanshan Fan, Jingxuan Liu, Ziyang College of Computer Science Beijing University of Technology Beijing China

ISBN: (纸本)9798400717994

this paper proposes a federated learning-based intrusion detection framework that incorporates the TCN-GRU model for security monitoring in industrial control systems. the TCN module effectively extracts long-term dependencies in network traffic through convolution operations, while the GRU module captures short-term dynamic variations, enhancing the model's ability to represent temporal trends. To ensure the convergence speed and stability of the deep learning model, a combination of the Lookahead optimizer and AdamW optimizer is adopted. Experimental results show that the TCN-GRU model exhibits significant advantages over the CNN-GRU model in terms of accuracy under different communication rounds and numbers of clients. the Lookahead optimizer demonstrates higher precision and more stable performance throughout the entire training process. Overall, the proposed model framework performs excellently in addressing network security issues in IIoT scenarios, providing a reliable solution for enhancing industrial network security. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Federated learning

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Privacy Protection in Mobile Crowdsensing Based on Local Differential Privacy 24

Privacy Protection in Mobile Crowdsensing Based on Local Dif...

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Cui, Xinyue Sun, Pengxuan Guo, Ningning School of Computer Science Beijing University of Technology Beijing China

ISBN: (纸本)9798400717994

We designed a system perception model under edge computing that supports Local Differential Privacy(LDP). To address the privacy protection challenges during the data submission phase in Mobile Crowdsensing(MCS) and the increased costs associated with privacy protection, we introduced an edge computing architecture into the MCS framework. Based on local differential privacy, we developed the MCS-MADP algorithm, which considers the attribute relationships of user-submitted data. Experimental results show that, under the same privacy budget, the MCS-MADP algorithm improves accuracy by an average of 67.75% compared to the LoPub algorithm and by an average of 139.89% compared to the PrivKV algorithm. Additionally, the MCS-MADP algorithm enhances data accuracy while reducing the required data volume. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Differential privacy

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Trust-Based Identity Privacy for Edge Computing 24

Trust-Based Identity Privacy for Edge Computing

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Dong, Jie Wen Kang, Xi Nai Peng, Jin Jiang, Xuan Ming Zhu, Tao Jun Information Technology Department National Key Laboratory of Seience and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute BeiJing China School of Computer Science Beijing University of Technology BeiJing China

ISBN: (纸本)9798400717994

College of computer Science Beijing University of Technology, Beijing 100124, China, 1374622525@*** this paper proposes a trust collaboration technology for edge computing, addressing trust isolation and security issues through a unified trust value calculation method and blockchain technology. the designed trust management model evaluates the identity, capability, and behavior of terminal nodes using static and dynamic trust measurements. A consortium blockchain stores trust information to ensure immutability and efficient sharing. Simulation experiments validate the scheme's effectiveness in countering malicious node attacks, improving task completion rates, and reducing system risks. this solution offers an efficient and secure approach to trust management in edge computing environments. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Differential privacy

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A Lightweight and Trustworthy Authentication Protocol for UAV Networks Based on PUF 24

A Lightweight and Trustworthy Authentication Protocol for UA...

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Zhu, Juntao Peng, Jin Wang, Long College of Computer Science Beijing University of Technology Beijing China The 6th Research Institute of China Electronics Corporation Beijing China

ISBN: (纸本)9798400717994

With the continuous development of drone remote sensing technology, drone networks have garnered widespread attention. the application of drones has expanded from military uses to industrial and civilian sectors, facilitating tasks such as automated combat, production, and rescue operations. However, since drones operate in public environments, their communications are vulnerable to physical attacks and tampering, which can lead to privacy leaks and pose security risks. Additionally, as resource-constrained devices, drones find it difficult to support complex encryption algorithms. To address this issue, this paper proposes a lightweight authentication protocol based on Physical Unclonable Functions (PUF). this protocol leverages PUF to prevent physical capture attacks and enhances system efficiency through hash and XOR operations. Furthermore, trust management technology is applied to further evaluate the network access behavior of drones, ensuring trustworthy access to the drone network. the security of this protocol is verified using the ROR model and AVISPA tool, and informal analysis demonstrates that it meets the security requirements of drone networks. Compared with existing protocols, this protocol shows significant advantages in terms of computational and communication overhead, achieving a good balance between security and efficiency. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Drones

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A Lightweight PUF-Based Authentication Protocol for M2M communications in Industrial IoT 24

A Lightweight PUF-Based Authentication Protocol for M2M Comm...

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Fan, Jingxuan Tu, Shanshan Wang, Haoran Liu, Ziyang College of Computer Science Beijing University of Technology Beijing China

ISBN: (纸本)9798400717994

In the Industrial Internet of things (IIoT) landscape, machine-to-machine (M2M) communication is extensively employed, allowing IoT devices to interact autonomously without human intervention. Despite its benefits, M2M communication faces substantial challenges related to privacy and data security, particularly due to malicious attacks within the network and data transmission over insecure channels. Existing security solutions often incur high computational costs, making them impractical for resource-constrained IoT devices. Furthermore, many of these solutions remain vulnerable to replay attacks, denial-of-service (DoS) attacks, and fail to provide sufficient anonymity, limiting their real-world applicability. To tackle these issues, we propose a secure, lightweight authentication protocol leveraging Physical Unclonable Functions (PUFs) and cryptographic hash functions, aimed at safeguarding M2M communications within IIoT environments. Our protocol effectively verifies participant legitimacy and secures data transmission without imposing significant computational burdens. Informal analyses indicate that the proposed protocol offers enhanced security and performance compared to existing approaches. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Hash functions

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Meta GPT-Based Agent for Enhanced Phishing Email Detection 24

Meta GPT-Based Agent for Enhanced Phishing Email Detection

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Ling, Feng Yang, Hao Xiao, Yongcai Hu, Lei Schoolof Computer and Information Engineering Jiangxi Normal University Jiangxi Nanchang China Electric Power Research Institute State Grid Jiangxi Electric Power Co. Ltd. Jiangxi Nanchang China

ISBN: (纸本)9798400717994

Phishing emails are a common means of phishing and their detection is an important aspect of email security. In this study, Meta Phishing Detector Agent system is designed, which is constructed based on Meta GPT framework and uses LLMs as the core of agent to detect phishing emails. the agent has three actions: Check Header, Check Body and Make Decision. Check Header and Check Body are used to analyze the header and body information of emails, and Make Decision is responsible for giving structured decision results based on the previous analysis results. Unlike previous email classification systems, our system provides users with detailed evidence-based reasons for judgment while giving judgment results. the performance of the system was evaluated on a novel phishing email dataset, and the experimental results show that the agent system, using the GLM-4 large language model for example, achieves 99.30% accuracy. Our study gives a new practical approach for the application of LLMs-based agents in the field of cyber security. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Phishing

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Multi-Scene Fire Smoke Detection Algorithm Based on YOLO v8 24

Multi-Scene Fire Smoke Detection Algorithm Based on YOLO v8

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Li, Aiguo Song, Xiaowan School of Computer Science and Technology Xi'an University of Science and Technology Shaanxi Xi'an China

ISBN: (纸本)9798400717994

Aiming at the problems of semi-transparent smoke misdetection and fire missing detection in multi-scene fire smoke detection, a multi-scene fire smoke detection algorithm based on YOLOv8 is proposed. Firstly, deformable convolution DCN V2 is introduced to solve the problems of great difference in size and shape of flame target and high difficulty in detection, so as to achieve full feature extraction. Secondly, dynamic sparse attention is used to filter out irrelevant key-value pairs at the rough area level, so as to enhance the focus on fire. Finally, by fusing generalized feature pyramid GFPN to enrich the multi-scale feature sensing field, further improve the performance of the algorithm and save computational resources. Experimental results show that the precision rate of YOLOv8-FS algorithm is 94.7% mAP50 reaches 96.1% and the model size is only 7.2 MB. the algorithm can balance precision and lightweight, and can meet the requirements of fire detection in complex scenes. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Smoke detectors

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RanCF: Optimizing Ransomware Classification in IIoT Environments with Random Forest 24

RanCF: Optimizing Ransomware Classification in IIoT Environm...

引用

14th International conference on communication and Network security, ICCNS 2024

作者： Gong, Mowei Lu, Xuepeng Peng, Tianqi Zheng, Guiping Zhu, Haotian Cui, Xinyue College of Computer Science Beijing University of Technology Beijing China Department of Technical Support Beijing Luo'an Technology Co. Ltd. Beijing China

ISBN: (纸本)9798400717994

the advent of Industry 4.0 has established the Industrial Internet of things (IIoT) as the technological bedrock for achieving intelligent industrial production across key sectors, including smart manufacturing, power, coal mining, and gas. Consequently, it has increasingly become the target of malicious actors. Recent years have witnessed a dramatic surge in ransomware attacks against the Industrial IoT, inflicting significant economic losses and jeopardizing production safety. In this paper, we introduce an optimized ransomware classification and identification algorithm tailored to the IIoT environment. Utilizing the Random Forest algorithm, this method distinguishes ransomware families by analyzing a comprehensive set of static and dynamic features. Experimental results confirm that our approach achieves an accuracy of 98.6%, demonstrating substantial efficacy in identifying prevalent ransomware families. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Random forests

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Trust Collaboration for Edge Computing 24

Trust Collaboration for Edge Computing

引用

14th International conference on communication and Network security, ICCNS 2024

ISBN: (纸本)9798400717994

As edge computing becomes an increasingly important computing model, trust management and security issues are becoming more severe. Problems such as malicious node attacks and trust isolation pose threats to the security and stability of edge computing environments. therefore, designing an efficient and secure trust management mechanism is imperative. this paper proposes a trust collaboration technology for edge computing, addressing trust isolation and security issues through a unified trust value calculation method and blockchain technology. the designed trust management model evaluates the identity, capability, and behavior of terminal nodes using static and dynamic trust measurements. A consortium blockchain stores trust information to ensure immutability and efficient sharing. Simulation experiments validate the scheme's effectiveness in countering malicious node attacks, improving task completion rates, and reducing system risks. this solution offers an efficient and secure approach to trust management in edge computing environments. © 2024 Copyright held by the owner/author(s). Publication rights licensed to acm.

关键词： Mobile edge computing

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