Secur. Commun. Networks最新文献

An Effective Credit Evaluation Mechanism with Softmax Regression and Blockchain in Power IoT 基于Softmax回归和区块链的电力物联网有效信用评估机制

Secur. Commun. Networks Pub Date : 2022-02-14 DOI: 10.1155/2022/3842077

Da Li, Dong Wang, Wei Jiang, Qinglei Guo, Desheng Bai, Wei-Nan Shi, Linna Ruan

引用次数: 1

Fast Implementation of Multiplication on Polynomial Rings 多项式环上乘法的快速实现

Secur. Commun. Networks Pub Date : 2022-02-14 DOI: 10.1155/2022/4649158

Bo Wang, Haiying Gao, F. Yang

引用次数: 0

An Improved Particle Swarm Optimisation Method for Performance Evaluation of Instructors 基于改进粒子群算法的教师绩效评价方法

Secur. Commun. Networks Pub Date : 2022-02-14 DOI: 10.1155/2022/3333005

Mu Yuanhong

{"title":"An Improved Particle Swarm Optimisation Method for Performance Evaluation of Instructors","authors":"Mu Yuanhong","doi":"10.1155/2022/3333005","DOIUrl":"https://doi.org/10.1155/2022/3333005","url":null,"abstract":"Performance evaluation of counselors plays a vital role for education industry (schools, colleges, universities, and vocational colleges). The problem can be stated with the phrases; how to design reasonable and appropriate performance indicators? The objective of this research is to design an effective performance evaluation. The purpose of this study is to explore a new method of performance evaluation that combines strategic goals with personal development goals. The purpose of performance evaluation is to better motivate the enthusiasm of counselors. With the methodology, a new issue faced at modern colleges and universities is being resolved. Therefore, for explaining methodology, this study has carried out the application analysis of the fusion particle swarm algorithm (FPSA) in the performance evaluation of instructors. First, on the basis of comprehensive analysis of performance evaluation, it discusses the advantages and disadvantages of university performance evaluation. Secondly, particle swarm and fuzzy comprehensive evaluation methods are used in the research of instructor performance evaluation. Pass the superiority of this assessment system. Index parameter evaluation is from 2.5 to 3.0. The range indicates an excellent value. In result this improved particle swarm can be compared with the state of the art (Liu et al., 2019). In conclusive remarks, this study is to provide state-of-the-art study for the current research on the topic of instructor performance appraisal in colleges and universities.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133047669","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: 4

Multiple-Layer Security Threats on the Ethereum Blockchain and Their Countermeasures 以太坊区块链的多层安全威胁及其对策

Secur. Commun. Networks Pub Date : 2022-02-14 DOI: 10.1155/2022/5307697

Li Duan, Yangyang Sun, Kejia Zhang, Yong Ding

引用次数: 11

A New V-Net Convolutional Neural Network Based on Four-Dimensional Hyperchaotic System for Medical Image Encryption 基于四维超混沌系统的新型V-Net卷积神经网络医学图像加密

Secur. Commun. Networks Pub Date : 2022-02-14 DOI: 10.1155/2022/4260804

Xiaowei Wang, Shoulin Yin, M. Shafiq, A. Laghari, Shahid Karim, O. Cheikhrouhou, Wajdi Alhakami, Habib Hamam

{"title":"A New V-Net Convolutional Neural Network Based on Four-Dimensional Hyperchaotic System for Medical Image Encryption","authors":"Xiaowei Wang, Shoulin Yin, M. Shafiq, A. Laghari, Shahid Karim, O. Cheikhrouhou, Wajdi Alhakami, Habib Hamam","doi":"10.1155/2022/4260804","DOIUrl":"https://doi.org/10.1155/2022/4260804","url":null,"abstract":"In the transmission of medical images, if the image is not processed, it is very likely to leak data and personal privacy, resulting in unpredictable consequences. Traditional encryption algorithms have limited ability to deal with complex data. The chaotic system is characterized by randomness and ergodicity, which has advantages over traditional encryption algorithms in image encryption processing. A novel V-net convolutional neural network (CNN) based on four-dimensional hyperchaotic system for medical image encryption is presented in this study. Firstly, the plaintext medical images are processed into 4D hyperchaotic sequence images, including image segmentation, chaotic system processing, and pseudorandom sequence generation. Then, V-net CNN is used to train chaotic sequences to eliminate the periodicity of chaotic sequences. Finally, the chaotic sequence image is diffused to change the raw image pixel to realize the encryption processing. Simulation test analysis demonstrates that the proposed algorithm has better effect, robustness, and plaintext sensitivity.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126343540","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: 12

Mitigation Impact of Energy and Time Delay for Computation Offloading in an Industrial IoT Environment Using Levenshtein Distance Algorithm 利用Levenshtein距离算法缓解工业物联网环境中能量和时间延迟对计算卸载的影响

Secur. Commun. Networks Pub Date : 2022-02-12 DOI: 10.1155/2022/6469380

Ahsan Rafiq, P. Wang, Min Wei, Mohammed Saleh Ali Muthanna, Nteziriza Nkerabahizi Josbert

{"title":"Mitigation Impact of Energy and Time Delay for Computation Offloading in an Industrial IoT Environment Using Levenshtein Distance Algorithm","authors":"Ahsan Rafiq, P. Wang, Min Wei, Mohammed Saleh Ali Muthanna, Nteziriza Nkerabahizi Josbert","doi":"10.1155/2022/6469380","DOIUrl":"https://doi.org/10.1155/2022/6469380","url":null,"abstract":"Due to the explosive growth of the Internet of things (IoT) devices and the emergence of diverse new applications, network traffic volume is growing exponentially. The traditional centralized network architecture cannot fulfill IoT devices demand because of the heavy network traffic in industrial IoT. Moreover, IoT devices have limited computational ability and battery power. Energy consumption and time delay problems during computation offloading are fundamental issues. A new architecture known as mobile edge computing (MEC) was introduced to overcome these issues, which brings cloud services and its contents to the edge of the network. IoT devices can offload the data for computation to the cloud server or edge nodes. Different schemes have been proposed to overcome this problem under many scenarios (i.e., single-user, multiuser, and vehicular networks). In this paper, we proposed a modified delay mitigation Levenshtein distance algorithm (MDML). We consider an industrial scenario with multiple IoT devices and multiple servers (edge nodes). Each edge node consists of one MEC server. The proposed algorithm solves the offloading optimization problem of energy and mitigation of time delay with much lower complexity while significantly reducing offloading tasks’ execution time. It works on the basis of dynamic programming, where we break down a complex problem into subproblems. Performance evaluation of our proposed algorithm shows that it can achieve satisfactory energy efficiency and mitigate time delay in the industrial IoT environment.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131276814","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: 3

Research on Marketing Strategy of Chinese Painting and Calligraphy Art Based on Wireless Communication Network Resources 基于无线通信网络资源的中国书画艺术营销策略研究

Secur. Commun. Networks Pub Date : 2022-02-12 DOI: 10.1155/2022/7788645

Tian Zhong

引用次数: 0

Bridging the Last-Mile Gap in Network Security via Generating Intrusion-Specific Detection Patterns through Machine Learning 通过机器学习生成特定于入侵的检测模式，弥合网络安全的最后一英里鸿沟

Secur. Commun. Networks Pub Date : 2022-02-12 DOI: 10.1155/2022/3990386

Xibin Sun, Du Zhang, Haiou Qin, Jiahua Tang

{"title":"Bridging the Last-Mile Gap in Network Security via Generating Intrusion-Specific Detection Patterns through Machine Learning","authors":"Xibin Sun, Du Zhang, Haiou Qin, Jiahua Tang","doi":"10.1155/2022/3990386","DOIUrl":"https://doi.org/10.1155/2022/3990386","url":null,"abstract":"With successful machine learning applications in many fields, researchers tried to introduce machine learning into intrusion detection systems for building classification models. Although experimental results showed that these classification models could produce higher accuracy in predicting network attacks on the offline datasets, compared with the operational intrusion detection systems, machine learning is rarely deployed in the real intrusion detection environment. This is what we call the last mile problem with the machine learning approach to network intrusion detection, the discrepancy between the strength and requirements of machine learning and network operational semantics. In this paper, we aim to bridge the aforementioned gap. In particular, an LCC-RF-RFEX feature selection approach is proposed to select optimal features of the specific type of attacks from dataset, and then, an intrusion-specific approach is introduced to convert them into detection patterns that can be used by the nonmachine-learning detector for the corresponding specific attack detection in the real-world network environment. To substantiate our approach, we take Snort, KDDCup’99 dataset, and Dos attacks as the experimental subjects to demonstrate how to close the last-mile gap. For the specific type of Dos attacks in the KDDCup’99 dataset, we use the LCC-RF-RFEX method to select optimal feature subset and utilize our intrusion-specific approach to generate new rules in Snort by using them. Comparing performance differences between the existing Snort rule set and our augmented Snort rule set with regard to Dos attacks, the experimental results showed that our approach expanded Snort’s detection capability of Dos attacks, on average, reduced up to 25.28% false-positive alerts for Teardrop attacks and Synflood attacks, and decreased up to 98.87% excessive alerts for Mail bomb attacks.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123781033","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

Gap between Prediction and Truth: A Case Study of False-Positives in Leakage Detection 预测与真实之间的差距:泄漏检测中误报的案例研究

Secur. Commun. Networks Pub Date : 2022-02-12 DOI: 10.1155/2022/6904232

Pengbo Wang, Ming Tang, Shoukun Xiang, Yaru Wang, Botao Liu

{"title":"Gap between Prediction and Truth: A Case Study of False-Positives in Leakage Detection","authors":"Pengbo Wang, Ming Tang, Shoukun Xiang, Yaru Wang, Botao Liu","doi":"10.1155/2022/6904232","DOIUrl":"https://doi.org/10.1155/2022/6904232","url":null,"abstract":"Since leakage detection was introduced as a popular side-channel security assessment, it has been plagued by false-positives (a.k.a. type I errors). To fix this error, the previous solutions set detection thresholds based on an assumption-based prediction of false-positive rate (FPR). However, this study points out that such a prediction (of FPR) may be inaccurate. We notice that the prediction in EuroCrypt2016 is much smaller than (approximately \u0000 \u0000 1\u0000 /\u0000 \u0000 779\u0000 \u0000 \u0000 times) the true FPR. The gap between prediction and truth, called underpredicted false-positives (UFP), leads to severe false-positives in leakage detection. Then, we check the statistical distribution of test statistics to analyze the cause of UFP. Our analysis indicates that the overlap between cross-validation (CV) blocks gives rise to an assumption error in the distribution of the CV-based estimates of \u0000 \u0000 ρ\u0000 \u0000 -statistics, which is the root cause of UFP. Therefore, we tackle the UFP by eliminating the overlap between blocks. Specifically, we propose a profiling-shared validation (PSV) and utilize this validation to improve the detection of any-variate any-order leakages. Our experiments show that the PSV solves the UFP and saves more than 75% of the test time costs. In summary, this article reports a potential flaw in leakage detection and provides a complete analysis of the flaw for the first time.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125147219","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

Your WAP Is at Risk: A Vulnerability Analysis on Wireless Access Point Web-Based Management Interfaces 您的WAP处于危险之中:对基于web的无线接入点管理接口的漏洞分析

Secur. Commun. Networks Pub Date : 2022-02-12 DOI: 10.1155/2022/1833062

Efstratios Chatzoglou, G. Kambourakis, C. Kolias

{"title":"Your WAP Is at Risk: A Vulnerability Analysis on Wireless Access Point Web-Based Management Interfaces","authors":"Efstratios Chatzoglou, G. Kambourakis, C. Kolias","doi":"10.1155/2022/1833062","DOIUrl":"https://doi.org/10.1155/2022/1833062","url":null,"abstract":"This work provides an answer to the following key question: Are the Web-based management interfaces of the contemporary off-the-shelf wireless access points (WAP) free of flaws and vulnerabilities? The short answer is not very much. That is, after performing a vulnerability assessment on the Web interfaces of six different WAPs by an equal number of diverse renowned vendors, we reveal a significant number of assorted medium-to-high severity vulnerabilities that are straightforwardly or indirectly exploitable. Overall, 13 categories of vulnerabilities translated to 28 zero-day attacks are exposed. Our findings range from legacy path traversal, cross-site scripting, and clickjacking attacks to HTTP request smuggling and splitting, replay, denial of service, and information leakage among others. In the worst-case scenario, the attacker can acquire the administrator’s (admin) credentials and the WAP’s Wi-Fi passphrases or permanently lock the admin out of accessing the WAP’s Web interface. On top of everything else, we identify the already applied hardening measures by these devices and elaborate on extra countermeasures that are required to tackle the identified weaknesses. To our knowledge, this work contributes the first wholemeal appraisal of the security level of this kind of Web-based interfaces that go hand in glove with the myriads of WAPs out there, and it is therefore anticipated to serve as a basis for further research in this timely and challenging field.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131831344","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: 4