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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Liu, Lu Li, Yuhui Wang, Ting Qin, Yuhan Ren, Yuhan College of International Education SiChuan Normal University Chengdu610000 China School of Automotive Engineering Harbin Institute of Technology Harbin150001 China Faculty of Computing Harbin Institute of Technology Harbin150001 China Law School SiChuan Normal University Chengdu610000 China

ISBN: (纸本)9781510680234

Image encryption has become one of the key techniques for information protection in today's context of increasing number and rising importance of digital communication. The purpose of this paper is to explore a creative image encryption method based on Rijndael algorithm and chaos algorithm, which disambiguates the image, hash value calculation. Then encrypted by Rijndael algorithm and generates a secure ciphertext. Compared to traditional encryption, this algorithm greatly improves the security and speed of encryption by combining multiple encryption techniques, and by conducting several encryption and decryption experiments on this algorithm, we prove that this method has a great prospect for security applications. © 2024 SPIE.

关键词： Cryptography

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A secure routing protocol for wireless sensor network

A secure routing protocol for wireless sensor network

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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Ye, Peishun Yulin University Yulin China

ISBN: (纸本)9781510680234

In this paper, we design a Reputation-based Diffusion Routing (RDR) algorithm based on the reputation evaluation model for selective forwarding attacks in wireless sensor network routing. We introduce the reputation evaluation model to gather the monitoring mechanism of neighbor nodes to obtain more comprehensive security performance. The algorithm judges whether the routing is successful or not through the neighbor node monitoring and evaluates the reputation to defend the selective forwarding attack of internal nodes. It can bypass the area of malicious nodes, improve the success rate of data routing, and reduce energy consumption. The experimental results verify that the RDR algorithm can maintain a high transmission rate with a small energy consumption, and can effectively defend malicious nodes. © 2024 SPIE.

关键词： Routing protocols

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FMAMPN: lightweight feature map attention multipath network for semantic segmentation of remote sensing image

FMAMPN: lightweight feature map attention multipath network ...

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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Hou, Songqi Yuan, Ying Institute of Spatial Information Technology Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781510680234

Deep neural networks excel in remote sensing image semantic segmentation, but existing methods, despite their sophistication, often focus on channel and spatial dependencies within identical feature maps. This can lead to a uniform treatment of diverse feature maps, hindering information exchange and impacting model efficacy. To address this, we introduce Feature Map Attention, dynamically modulating weights based on interdependencies among various feature maps. This fosters connections and feature fusion, enhancing the model's capability to represent features. Importantly, this improvement comes with minimal additional computational expense. We also incorporate multipath skip connections, efficiently transmitting features at various scales from encoder to decoder, boosting overall model effectiveness. Our FMAMPN, a lightweight neural network, outperforms other state-of-the-art lightweight models across various datasets. © 2024 SPIE.

关键词： Deep neural networks

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In-vehicle CAN bus security communication protocol based on identity encryption

In-vehicle CAN bus security communication protocol based on ...

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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Feng, Yao Qin, Guihe Zhang, Zizhan Wang, Guofeng Wang, Kunpeng College of Computer Science and Technology Jilin University Changchun China

ISBN: (纸本)9781510680234

The CAN network bus is one of the most widely used buses in the vehicle, but the lack of sufficient security mechanisms allows criminals to maliciously attack the vehicle, which is a very serious security risk. In this paper, an identity-based encryption algorithm is used to design a secure communication protocol for an in-vehicle CAN network. Compared with the method based on digital certificates, it reduces the overhead of verification, management, and storage of digital certificates. The combination of asymmetric key and symmetric key ensures sufficient security and a small time cost for the data communication phase. In addition, the Hash message authentication code (HMAC) is used to ensure the integrity and authenticity of the data during the transmission phase. Experimental results show that the proposed protocol can resist forgery attacks, tampering attacks, and replay attacks, and meet the real-time requirements of automotive-grade microcontrollers. © 2024 SPIE.

关键词： Vehicles

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TEN: Temporal Excitation network For Video Action Recognition

TEN: Temporal Excitation Network For Video Action Recognitio...

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2023 international conference on computer network security and software engineering, cnsse 2023

作者： Sun, Dengdi He, Zhenhao Luo, Bin Ding, Zhuanlian School of Artificial Intelligence Anhui University Hefei230601 China School of Computer Science and Technology Anhui University Hefei230601 China School of Internet Anhui University Hefei230039 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230026 China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

Temporal modeling has attracted the attention of a large number of researchers in the past few years. In this work, we propose a new video architecture, termed as Temporal Excitation network (TEN). The core of TEN is Temporal Excitation Module (TEM) block, which consists of Temporal Convolution Module (TCM) and Temporal Difference Module (TDM). TCM applies a channel-wise convolution to supplements the short-range temporal information. TDM works by computing feature-level long-range temporal differences and then exploiting it to excite motion-sensitive channels. These two-stage modeling scheme can be fused into existing 2D CNNs to model temporal structures flexibly and efficiently. Extensive experiments demonstrate the effectiveness of the proposed TEN on several benchmarks (e.g., UCF101, HMDB51, Something-Something V1 and Jester). The proposed TEN can guarantee high recognition accuracy while maintaining high recognition efficiency on these datasets. © 2023 SPIE.

关键词： Convolution

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A Rational Decision-Making Approach Based on Bayesian network and BDI Model For Autonomous Driving System

A Rational Decision-Making Approach Based on Bayesian Networ...

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2023 international conference on computer network security and software engineering, cnsse 2023

作者： Zhang, Xinyuan Du, Dehui Software Engineering Institute East China Ormal University Shanghai200062 China Shanghai Key Laboratory of Trnstworthy Computing Shanghai200062 China Intemational Joint Laboratory of Trnstworthy Software of Ministry of Education Shanghai200062 China

ISBN: (数字)9781510666528

ISBN: (纸本)9781510666511

The safety of decision-making in autonomous driving systems (ADSs) is a challenging issue, which is very important for ADS development. As a highly acceptable decision method, Bayesian Net\vork (BN) has attracted more and more attention, therefore, its decision confidence and robustness have also become a focus. Since BN is a form of reasoning based on probability, for the decision results with low confidence (that is, the probability values of several optional decision actions have a small difference), when the data is slightly disturbed, it is likely to change, resulting in serious consequences such as car crash. To generate safe decision-making, we innovatively propose a rational Bayesian network decision-making approach based on BDI model. It helps to improve the decision confidence of the traditional B. BDI model is a well-known theory of inferencing agents' mental states (belief, desire and intention). We use it to guide the decision-making process of Bayesian network. According to the domain knowledge of ADS, we introduce and design rule-based intention inference for the decision agent to build a Bayesian net\vork with BDI-layer. And for other uncertain agents in the environment, we utilize LSTM model to predict their intentions and provide scenario information for the construction of the above network. To sum up, we propose a rational decision-making approach based on Bayesian network guided by BDI model. Our novel approach makes the traditional Bayesian network decision more humanized and improves the confidence of decision results. Finally, we take the lane-change and overtaking scenario as an example to illustrate our approach in detail and demonstrate the effectiveness in improving decision confidence. © 2023 SPIE.

关键词： Decision making

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Can large language model replace static analysis tools

Can large language model replace static analysis tools

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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Cui, Han School of Software Engineering East China Normal University Shanghai China

ISBN: (纸本)9781510680234

Static analysis tools are widely used to ensure code quality and security, especially in large software projects. Recently, the advent of large language models (LLM), such as the Generative Pre-trained Transformer (GPT), seems to present a strong ability to handle tasks about static code analysis. This paper aims to answer the question, can large language model replace static analysis tools? We present an extensive evaluation of ChatGPT’s capabilities in identifying and analyzing issues detectable by three well-known Java static analysis tools: PMD, SpotBugs, and SonarQube. Through a series of experiments, we assess the performance of two versions of GPT, GPT-3.5 and GPT-4, across various categories of code issues. We conduct a detailed analysis of the experiment results and discuss the limitation of using ChatGPT to perform as a static analysis tool. The findings during our research suggest that while GPT, especially GPT-4 performs outstanding marks on the dataset we chose, it is improper to fully replace the static code analyzers at the time. Working as the supplementary of static code analyzers can be a nice way to enhance the code quality ensuring projects. © 2024 SPIE.

关键词： Quality control

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Research on network topology visualization under HTML5 technology

Research on network topology visualization under HTML5 techn...

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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Liu, Jian Dongying Vocational Institute Shandong Dongying257091 China

ISBN: (纸本)9781510680234

With the rapid development of computer network technology, the network structure has become increasingly complex, and the number and types of network devices have also shown explosive growth. In order to better understand, manage and optimize the network, visualization of network topology has become an important research field. However, the current visualization framework and tools have some problems in the practical process, such as complicated application process, single display effect and insufficient interaction ability, which can not meet the actual needs of users. In this regard, this paper will take network topology visualization as the research object, and build a network topology visualization system based on HTML5 through Web technology to realize the innovation of network topology management. Practice has proved that the whole system adopts B/S architecture design, and the front end is mainly based on HTML5, CSS and JavaScript, combined with BootStrap layout framework to complete the design and construction. At the same time, the Canvas is used to complete the drawing and rendering of visual graphics, which greatly improves the efficiency of network monitoring, conforms to the expected goal of network management system in displaying topological functions, and has certain practical application value. © 2024 SPIE.

关键词： network topology

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Preface to the special issue on engineering of computer-based systems

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international JOURNAL ON software TOOLS FOR TECHNOLOGY TRANSFER 2025年第1期27卷 1-3页

作者： Kofron, Jan Margaria, Tiziana Seceleanu, Cristina Charles Univeristy Prague Czech Republic Univ Limerick Limerick Ireland LERO Limerick Ireland Malardalen Univ Vasteras Sweden

This special issue contains nine extended and rigorously peer-reviewed papers selected from those originally presented at ECBS 2023, the 8th international conference on engineering of computer-Based Systems, held at M & auml;lardalen University, Sweden, October 16-18, 2023, under the theme "engineering for Responsible AI". The included papers represent innovative contributions addressing critical aspects of responsible artificial intelligence and integrated engineering practices. These contributions span from formal verification and security analyses of IoT protocols and federated learning frameworks to machine learning-based simulations and predictions in hardware and software systems. The selection also includes work on automata learning techniques for protocol compliance, continuous integration approaches for neural network-based autonomous systems, assertion usage in software testing, language-driven engineering for code generation, and the integration of IoT backends in digital twin infrastructures. Together, these papers showcase recent advances, offering valuable insights into the rigorous integration of modern technologies within complex, computer-based systems.

关键词： security of IoT Machine learning Automata learning Testing Digital twins

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Vehicle CAN bus intrusion detection model based on Bayesian network

Vehicle CAN bus intrusion detection model based on Bayesian ...

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2024 international conference on computer network security and software engineering, cnsse 2024

作者： Dong, Kangyao Beijing City University 101330 China

ISBN: (纸本)9781510680234

With the rapid development of in-vehicle network technology, vehicle safety and protection are facing more and more challenges. The vehicle CAN bus is the main network for vehicle internal communication. However, due to its lack of necessary security mechanisms, the vehicle CAN bus is vulnerable to intrusion attacks. Therefore, developing an effective intrusion detection model is crucial to secure vehicle networks. This study proposes a vehicle CAN bus intrusion detection model based on Bayesian network. This model utilizes the probabilistic reasoning of Bayesian networks and the update characteristics of conditional probability, combined with the characteristic attributes of the vehicle CAN bus, to achieve accurate detection of potential intrusion behaviors. By learning historical data, the conditional probability of the Bayesian network can be updated to achieve real-time detection and prediction of intrusion behavior. In order to verify the effectiveness of the model, we used a real vehicle CAN bus data set for experiments. Experimental results show that the intrusion detection model based on Bayesian network has achieved good results in identifying and predicting intrusion behavior of the vehicle CAN bus. Compared with traditional intrusion detection methods, this model can provide higher accuracy and lower false alarm rate, effectively protecting the security of in-vehicle networks. © 2024 SPIE.

关键词： Intrusion detection

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