Journal of Cyber Security and Mobility最新文献_第2页

Security of Encrypted Images in Network Transmission Based on an Improved Chaos Algorithm 基于改进混沌算法的加密图像网络传输安全性研究

Journal of Cyber Security and Mobility Pub Date : 2023-08-12 DOI: 10.13052/jcsm2245-1439.1253

G. Du

引用次数: 0

Camera Network Topology Mapping Based on the Integration of Network Information and Physical Distribution Under the Background of Communication Security 通信安全背景下基于网络信息与物理分布融合的摄像机网络拓扑映射

Journal of Cyber Security and Mobility Pub Date : 2023-08-12 DOI: 10.13052/jcsm2245-1439.1256

Min Chen

{"title":"Camera Network Topology Mapping Based on the Integration of Network Information and Physical Distribution Under the Background of Communication Security","authors":"Min Chen","doi":"10.13052/jcsm2245-1439.1256","DOIUrl":"https://doi.org/10.13052/jcsm2245-1439.1256","url":null,"abstract":"At present, most cameras use internal networks and use methods such as Traceroute for security protection, which cannot meet the requirements of camera network mapping. Therefore, a camera mapping scheme of network information and physical distribution is proposed. Firstly, the network topology problem of video content information collection was analyzed. This paper uses the mapping relationship between network space and physical space to propose the subnet division conjecture method and complete the preliminary mapping of the network through video data screening. Considering the insufficient coverage of topology mapping, a judgment and inference method based on Bayesian classification technology and network information is proposed, and the results are corrected and evaluated through the test of Jackard coefficient. In the preliminary network topology performance test, two state-of-the-art schemes are selected for experimental comparison. When the number of nodes in the proposed scheme is 5, 25, and 50, the mapping can be completed in the shortest time, and the accuracy reaches 80%. However, the surveying and mapping accuracy of the proposed scheme in the preliminary test is low, and the network information method is used for data screening. In the final surveying and mapping performance test, when the number of nodes is 40, the accuracy of the proposed scheme is 96%, which is better than previously proposed schemes, while the testing delay time is shorter. The technology proposed in the study has the best overall performance. It can effectively solve the problem of intranet surveying and mapping and has important reference value for the security protection of the camera network.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"79 1","pages":"733-756"},"PeriodicalIF":0.0,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85155661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptation of the Ant Colony Algorithm to Avoid Congestion in Wireless Mesh Networks 自适应蚁群算法避免无线Mesh网络拥塞

Journal of Cyber Security and Mobility Pub Date : 2023-08-12 DOI: 10.13052/jcsm2245-1439.1258

Fadhil Mohammed Salman, Ahssan Ahmed Mohammed, Fanar Ali Joda

{"title":"Adaptation of the Ant Colony Algorithm to Avoid Congestion in Wireless Mesh Networks","authors":"Fadhil Mohammed Salman, Ahssan Ahmed Mohammed, Fanar Ali Joda","doi":"10.13052/jcsm2245-1439.1258","DOIUrl":"https://doi.org/10.13052/jcsm2245-1439.1258","url":null,"abstract":"Wireless mesh networks have recently presented a promising environment for many researchers to develop large-scale wireless communication. Traffic in WMNs often suffers from congestion due to heavy traffic load’s saturation of certain routes. Therefore, this article proposes an efficient approach for congestion awareness and load balancing in WMNs, based on the Ant Colony Optimization (ACO) approach. The proposed approach aims to raise the performance of the WMN by distributing the traffic load between optimal routes and avoiding severe traffic congestion. The proposed approach relies on three basic mechanisms: detection of severe congestion within the ideal paths used for data transmission, creation of ideal secondary paths with updated pheromone values, and distribution of the traffic load (data packet flow) between the primary and secondary ideal paths. According to the results of the NS2 simulator, the suggested approach increased the WMN throughput by 14.8% when compared to the CACO approach and by 37% when employing the WCETT approach. The results also showed that the proposed approach achieved an average end-to-end delay closing of 0.0562, while WCETT and CACO approaches achieved an average end-to-end delay close to 0.1021 and 0.0976, respectively. The results indicated that the proposed approach achieved a lower percentage of dropped packets by 6.97% and 0.99% compared to the WCETT and CACO approaches. Thus, the proposed approach is effective in improving the performance of WMNs.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"148 1","pages":"785-812"},"PeriodicalIF":0.0,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86076916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine Learning: Research on Detection of Network Security Vulnerabilities by Extracting and Matching Features 机器学习:基于特征提取与匹配的网络安全漏洞检测研究

Journal of Cyber Security and Mobility Pub Date : 2023-08-12 DOI: 10.13052/jcsm2245-1439.1254

Ying Xue

引用次数: 0

An Evaluation Model for Network Security Based on an Optimized Circular Algorithm 基于优化循环算法的网络安全评估模型

Journal of Cyber Security and Mobility Pub Date : 2023-08-12 DOI: 10.13052/jcsm2245-1439.1255

Xingfeng Li

{"title":"An Evaluation Model for Network Security Based on an Optimized Circular Algorithm","authors":"Xingfeng Li","doi":"10.13052/jcsm2245-1439.1255","DOIUrl":"https://doi.org/10.13052/jcsm2245-1439.1255","url":null,"abstract":"With more and more control systems accessing computer networks, the increase in their associated vulnerabilities has led to a decreasing security evaluation of the networks. It is essential to secure computer networks from attacks. To this end, the study constructs a network of computer network security evaluation model based on an optimized circular algorithm. To avoid detecting the model’s parameters falling into the local optimum, the model is first optimized based on the Corsi grey wolf optimization (CGWO) algorithm for the hyperparameters of the Gaussian process (GP). To solve the problem of unbalanced data and the GP not having memory capability, the study proposes an optimized Gaussian Mixture Model-Recurrent neural networks (GMM-RNN) algorithm. Experimental results of attack type recognition accuracy showed that the research CGWO-GP algorithm can jump out of the local optimum, and its average value of accuracy reached 98.99%. The average value of the leakage rate was 0.42%, and the average value of the false alarm rate was 0.11%. The average detection accuracy of the GMM-RNN model for eight attack types was 95.899%. The optimal detection accuracy of this model performance was 96.3948%. The training time of the GMM-RNN model was 67.96 s, and the detection time of the test set was 6.45 s, which greatly optimized the real-time performance. The GMM-RNN model was more effective in predicting the security posture of computer networks, and the prediction value can reach 97.65%. The research model was significantly better than other algorithmic models in the performance and evaluation of computer network security and had certain research values.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"79 1","pages":"711-732"},"PeriodicalIF":0.0,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79299595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multi-Path Approach to Protect DNS Against DDoS Attacks 多路径防御DDoS攻击

Journal of Cyber Security and Mobility Pub Date : 2023-06-30 DOI: 10.13052/jcsm2245-1439.1246

S. Alouneh

{"title":"A Multi-Path Approach to Protect DNS Against DDoS Attacks","authors":"S. Alouneh","doi":"10.13052/jcsm2245-1439.1246","DOIUrl":"https://doi.org/10.13052/jcsm2245-1439.1246","url":null,"abstract":"Domain Name System (DNS) is considered a vital service for the internet and networks operations, and practically this service is configured and accessible across networks’ firewall. Therefore, attackers take advantage of this open configuration to attack a network’s DNS server in order to use it as a reflector to achieve Denial of Service (DoS) attacks. Most of protection methods such as intrusion prevention and detection systems use blended tactics such as blocked-lists for suspicious sources, and thresholds for traffic volumes to detect and defend against DoS flooding attacks. However, these protection methods are not often successful. In this paper, we propose a new method to sense and protect DNS systems from DoS and Distributed DoS (DDoS) attacks. The main idea in our approach is to distribute the DNS request mapping into more than one DNS resolver such that an attack on one server should not affect the entire DNS services. Our approach uses the Multi-Protocol Label Switching (MPLS) along with multi-path routing to achieve this goal. Also, we use threshold secret sharing to code the distributed DNS requests. Our findings and results show that this approach performs better when compared with the traditional DNS structure.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"9 1","pages":"569-588"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83524505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Hybrid Domain Medical Image Encryption Scheme Using URUK and WAM Chaotic Maps with Wavelet - Fourier Transforms 基于小波傅里叶变换的URUK和WAM混沌映射混合域医学图像加密方案

Journal of Cyber Security and Mobility Pub Date : 2023-06-30 DOI: 10.13052/jcsm2245-1439.1241

Ali Akram Abdul-Kareem, W. A. M. Al-Jawher

引用次数: 0

The Assessment of Cyber Security's Significance in the Financial Sector of Lithuania 立陶宛金融部门网络安全重要性评估

Journal of Cyber Security and Mobility Pub Date : 2023-06-30 DOI: 10.13052/jcsm2245-1439.1243

Julija Gavėnaitė-Sirvydienė, Algita Miečinskienė

引用次数: 0

FedBully: A Cross-Device Federated Approach for Privacy Enabled Cyber Bullying Detection using Sentence Encoders FedBully:一种使用句子编码器的跨设备联邦方法，用于支持隐私的网络欺凌检测

Journal of Cyber Security and Mobility Pub Date : 2023-06-30 DOI: 10.13052/jcsm2245-1439.1242

Nisha P. Shetty, Balachandra Muniyal, Aman Priyanshu, Vedant Rishi Das

{"title":"FedBully: A Cross-Device Federated Approach for Privacy Enabled Cyber Bullying Detection using Sentence Encoders","authors":"Nisha P. Shetty, Balachandra Muniyal, Aman Priyanshu, Vedant Rishi Das","doi":"10.13052/jcsm2245-1439.1242","DOIUrl":"https://doi.org/10.13052/jcsm2245-1439.1242","url":null,"abstract":"Cyberbullying has become one of the most pressing concerns for online platforms, putting individuals at risk and raising severe public concerns. Recent studies have shown a significant correlation between declining mental health and cyberbullying. Automated detection offers a great solution to this problem; however, the sensitivity of client-data becomes a concern during data collection, and as such, access may be restricted. This paper demonstrates FedBully, a federated approach for cyberbullying detection using sentence encoders for feature extraction. This paper introduces concepts of secure aggregation to ensure client privacy in a cross-device learning system. Optimal hyper-parameters were studied through comprehensive experiments, and a computationally and communicationally inexpensive network is proposed. Experiments reveal promising results with up to 93% classification AUC (Area Under the Curve) using only dense networks to fine-tune sentence embeddings on IID datasets and 91% AUC on non-IID datasets, where IID refers to Independent and Identically Distributed data. The analysis also shows that data independence profoundly impacts network performance, with AUC decreasing by a mean of 5.1% between Non-IID and IID. A rich and extensive study has also been performed on client network size and secure aggregation protocols, which prove the robustness and practicality of the proposed model. The novel approach presented offers an efficient and practical solution to training a cross-device cyberbullying detector while ensuring client-privacy.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"37 1","pages":"465-496"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81264947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Network Security Prediction and Situational Assessment Using Neural Network-based Method 基于神经网络的网络安全预测与态势评估方法

Journal of Cyber Security and Mobility Pub Date : 2023-06-30 DOI: 10.13052/jcsm2245-1439.1245

Liu Zhang, Yanyu Liu

{"title":"Network Security Prediction and Situational Assessment Using Neural Network-based Method","authors":"Liu Zhang, Yanyu Liu","doi":"10.13052/jcsm2245-1439.1245","DOIUrl":"https://doi.org/10.13052/jcsm2245-1439.1245","url":null,"abstract":"Technology development has promoted network construction, but malicious network attacks are still inevitable. To solve the problem that the current network security assessment is not practical and the assessment effect is poor, this study proposes a network security monitoring tool based on situation assessment and prediction to assist network security construction. The framework of the evaluation module is based on convolution neural network. The initial module is introduced to convert some large convolution cores into small convolution cores in series. This is to reduce the operating cost, because building multiple evaluators in series can maximize the retention of characteristic values. This module is the optimized form of Elman neural network. The delay operator is added to the model to respond to the time property of network attack. At the same time, particle swarm optimization algorithm is used to solve the initial weight dependence problem. The research adopts two methods of security situation assessment and situation prediction to carry out model application test. During the test, the commonly used KDD Cup99 is used as intrusion detection data. The experimental results of the network security situation evaluation module show that the optimization reduces the evaluation error by 3.34%, and the accuracy meets the evaluation requirements. The model is superior to the back propagation neural network and the standard Elman model. The model proposed in this study achieves better prediction of posture scores from 0.3 to 0.9, which is more stable than BP neural network. It proves that the model designed by the research can achieve more stable and higher prediction than similar models. It is more practical to obtain better results on the basis of a more stable model architecture and lower implementation costs, which is a meaningful attempt in the wide application of network security.","PeriodicalId":37820,"journal":{"name":"Journal of Cyber Security and Mobility","volume":"24 1","pages":"547-568"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77926762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0