Secur. Commun. Networks最新文献_第5页

Security, Trust and Privacy for Cloud, Fog and Internet of Things 云、雾和物联网的安全、信任和隐私

Secur. Commun. Networks Pub Date : 2022-01-28 DOI: 10.1155/2022/9841709

Chien-Ming Chen, Shehzad Ashraf Chaudhry, Kuo-Hui Yeh, M. Aman

引用次数: 2

A Hidden Attack Sequences Detection Method Based on Dynamic Reward Deep Deterministic Policy Gradient 基于动态奖励深度确定性策略梯度的隐藏攻击序列检测方法

Secur. Commun. Networks Pub Date : 2022-01-28 DOI: 10.1155/2022/1488344

L. Zhang, Zhisong Pan, Yu Pan, Shize Guo, Yi Liu, Shiming Xia, Qibin Zheng, Hongmei Li, Wei Bai

{"title":"A Hidden Attack Sequences Detection Method Based on Dynamic Reward Deep Deterministic Policy Gradient","authors":"L. Zhang, Zhisong Pan, Yu Pan, Shize Guo, Yi Liu, Shiming Xia, Qibin Zheng, Hongmei Li, Wei Bai","doi":"10.1155/2022/1488344","DOIUrl":"https://doi.org/10.1155/2022/1488344","url":null,"abstract":"Attacker identification from network traffic is a common practice of cyberspace security management. However, network administrators cannot cover all security equipment due to the cyberspace management cost constraints, giving attackers the chance to escape from the surveillance of network security administrators by legitimate actions and to perform the attack in both physical domain and digital domain. Therefore, we proposed a hidden attack sequence detection method based on reinforcement learning to deal with the challenge through modeling the network administrators as an intelligent agent that learns their action policy from the interaction with the cyberspace environment. Following Deep Deterministic Policy Gradient (DDPG), the intelligent agent can not only discover the hidden attackers hiding in the legitimate action sequences but also reduce the cyberspace management cost. Furthermore, a dynamic reward DDPG method was proposed to improve defense performance, which set dynamic reward depending on the hidden attack sequences steps and agent’s check steps, compared to the fixed reward in common methods. Meanwhile, the method was verified in a simulated experimental cyberspace environment. Finally, the experimental results demonstrate that there are hidden attack sequences in cyberspace, and the proposed method can discover the hidden attack sequences. The dynamic reward DDPG shows superior performance in detecting hidden attackers, with a detection rate of 97.46%, which can improve the ability to discover hidden attackers and reduce the 6% cyberspace management cost compared to DDPG.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130882827","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

Taxi Dispatch Optimization in Smart Cities Using TOPSIS 基于TOPSIS的智慧城市出租车调度优化

Secur. Commun. Networks Pub Date : 2022-01-28 DOI: 10.1155/2022/7213633

A. Abid, Naeem A. Nawaz, M. Farooq, U. Farooq, Irfan Abid, Iqra Obaid

{"title":"Taxi Dispatch Optimization in Smart Cities Using TOPSIS","authors":"A. Abid, Naeem A. Nawaz, M. Farooq, U. Farooq, Irfan Abid, Iqra Obaid","doi":"10.1155/2022/7213633","DOIUrl":"https://doi.org/10.1155/2022/7213633","url":null,"abstract":"The modern smart cities demand an efficient taxi dispatch system to satisfy the expectations of the passengers while giving justified rides to the drivers. Many a time, the customers have to wait too long for a taxi and the taxi driver wastes a lot of his time and the fuel in finding customers. Furthermore, some customers cancel the ride for not finding suitable category of taxi. Though there exist some algorithms that aim to optimize the assignment of taxis to appropriate customers, yet most of these approaches focus on the positioning of the taxi drivers. This research aims to address the problem of taxi dispatching while keeping in view the preferences of the customer. To this end, this research models taxi dispatch system as a multicriteria decision-making problem where not only is the distance between the passenger and the taxi a parameter, but other user preferences are also incorporated in finalizing a taxi for a given passenger travel request. The proposed method has been compared with the traditional taxi dispatching system. The results reveal more satisfactory taxi dispatching based on the users’ preferences. Furthermore, the precision of the proposed approach has been proven with lesser cancellation, improved driver rating, and reduction in complaints.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132345448","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

Machine Learning and Applied Cryptography 机器学习和应用密码学

Secur. Commun. Networks Pub Date : 2022-01-27 DOI: 10.1155/2022/9797604

Amir Anees, I. Hussain, U. Khokhar, Fawad Ahmed, Sajjad Shaukat Jamal

引用次数: 2

Detecting User Behavior in Cyber Threat Intelligence: Development of Honeypsy System 网络威胁情报中的用户行为检测:honeyypsy系统的开发

Secur. Commun. Networks Pub Date : 2022-01-27 DOI: 10.1155/2022/7620125

Murat Odemis, Cagatay Yucel, A. Koltuksuz

{"title":"Detecting User Behavior in Cyber Threat Intelligence: Development of Honeypsy System","authors":"Murat Odemis, Cagatay Yucel, A. Koltuksuz","doi":"10.1155/2022/7620125","DOIUrl":"https://doi.org/10.1155/2022/7620125","url":null,"abstract":"This research demonstrates a design of an experiment of a hacker infiltrating a server where it is assumed that the communication between the hacker and the target server is established, and the hacker also escalated his rights on the server. Therefore, the honeypot server setup has been designed to reveal the correlation of a hacker’s actions with that of the hacker’s experience, personality, expertise, and psychology. To the best of our knowledge, such a design of experiment has never been tested rigorously on a honeypot implementation except for self-reporting tests applied to hackers in the literature. However, no study evaluates the actual data of these hackers and these tests. This study also provides a honeypot design to understand the personality and expertise of the hacker and displays the correlation of these data with the tests. Our Honeypsy system is composed of a Big-5 personality test, a cyber expertise test, and a capture-the-flag (CTF) event to collect logs with honeypot applied in this sequence. These three steps generate data on the expertise and psychology of known cyber hackers. The logs of the known hacker activities on honeypots are obtained through the CTF event that they have participated in. The design and deployment of a honeypot, as well as the CTF event, were specifically prepared for this research. Our aim is to predict an unknown hacker's expertise and personality by analyzing these data. By examining/analyzing the data of the known hackers, it is now possible to make predictions about the expertise and personality of the unknown hackers. The same logic applies when one tries to predict the next move of the unknown hackers attacking the server. We have aimed to underline the details of the personalities and expertise of hackers and thus help the defense experts of victimized institutions to develop their cyber defense strategies in accordance with the modus operandi of the hackers.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"348 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126679233","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

Invested Costs and Risk Control Model of Social Governance Based on Fuzzy Algorithm 基于模糊算法的社会治理投资成本与风险控制模型

Secur. Commun. Networks Pub Date : 2022-01-27 DOI: 10.1155/2022/8797798

Shan-Yun Teng, Huajun Li, Desheng Zhang

{"title":"Invested Costs and Risk Control Model of Social Governance Based on Fuzzy Algorithm","authors":"Shan-Yun Teng, Huajun Li, Desheng Zhang","doi":"10.1155/2022/8797798","DOIUrl":"https://doi.org/10.1155/2022/8797798","url":null,"abstract":"In view of the fact that the current methods cannot effectively and correctly control the invested costs and risk of social governance, resulting in a higher risk rate in the invested costs, a fuzzy algorithm-based invested costs and risk control model for social governance is proposed. This paper analyzes the classification and causes of risk, expounds the methods of risk identification and risk assessment, constructs and studies the invested costs and risk control model of social governance, establishes the fuzzy judgment matrix of risk control, calculates the single-layer ranking weight vector of risk fuzzy judgment matrix, and determines the fuzzy judgment matrix. The membership degree of risk influencing factors to the risk level is input into the social governance invested cost and risk control model to obtain the corresponding risk assessment results and predict the invested cost. According to the comparison of experimental results, through the test of risk degree and risk rate, it is verified that the maximum risk level value of the model is 20, which can minimize the risk degree; the risk control coefficient of the model is between 0.6 and 1.0, which can effectively reduce the probability of risk and achieve the purpose of design.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125948506","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

Attacker Traceability on Ethereum through Graph Analysis 通过图分析在以太坊上追踪攻击者

Secur. Commun. Networks Pub Date : 2022-01-27 DOI: 10.1155/2022/3448950

Hang Zhu, Weina Niu, Xuhan Liao, Xiaosong Zhang, Xiaofen Wang, Beibei Li, Zheyuan He

引用次数: 3

Economic Evaluation Method of Incremental Distribution Network Project Based on Value Theory 基于价值理论的增量配电网项目经济评价方法

Secur. Commun. Networks Pub Date : 2022-01-27 DOI: 10.1155/2022/1937177

Weiming Xie, Linda Qiu

引用次数: 0

FLOM: Toward Efficient Task Processing in Big Data with Federated Learning 基于联邦学习的大数据高效任务处理

Secur. Commun. Networks Pub Date : 2022-01-27 DOI: 10.1155/2022/5277362

Chunyi Wu, Ya Li

引用次数: 3

5G-EECC: Energy-Efficient Collaboration-Based Content Sharing Strategy in Device-to-Device Communication 5G-EECC:基于高效协同的设备间通信内容共享策略

Secur. Commun. Networks Pub Date : 2022-01-25 DOI: 10.1155/2022/1354238

Nauman Khan, I. Khan, Jawad Usman Arshed, Mehtab Afzal, Mohammad Masroor Ahmed, Muhammad Arif

{"title":"5G-EECC: Energy-Efficient Collaboration-Based Content Sharing Strategy in Device-to-Device Communication","authors":"Nauman Khan, I. Khan, Jawad Usman Arshed, Mehtab Afzal, Mohammad Masroor Ahmed, Muhammad Arif","doi":"10.1155/2022/1354238","DOIUrl":"https://doi.org/10.1155/2022/1354238","url":null,"abstract":"In the past few years, mobile data traffic has seen exponential growth due to the emergence of smart applications. Although throughput enhancement techniques such as macro- and femtocells reduce cell size, they are relatively expensive to implement. Mobile device-to-device (D2D) communication has emerged as a solution to support the growing popularity of multimedia content for local service in next-generation 5G cellular networks. Content sharing is the prominent feature, which helps D2D communication in reducing offload traffic on the network, improving the energy efficiency of the device, and reducing backhaul connectivity costs. In traditional mapping approaches such as one to one or one to many, a massive amount of traffic is distributed among the devices resulting in high-energy consumption. In this paper, we propose a novel energy-efficient content sharing scheme called Energy-Efficient Collaboration-based Content (EECC) sharing strategy in D2D communication that shares content equally across devices based on their capacities and battery life under mobility. The proposed work includes cluster formation, cluster head selection, and helper node selection. In addition, we relied on a cooperative caching policy to ensure that content is distributed efficiently. The simulation results indicate a 12.05% reduction in energy compared to the state-of-the-art technique with a 2-gigabyte video file. To evaluate scalability, we increased the file size from 3 to 4 gigabytes, yet the performance in terms of energy consumption remained the same.","PeriodicalId":167643,"journal":{"name":"Secur. Commun. Networks","volume":"348 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115282992","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: 5