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Intelligent Fault Diagnosis of Rolling Bearing With Variable Speed Based on ASTFrFT and Time-Frequency BoTNet Model 认领 引用
1
作者 Jie Ma Jun Wei Xinyu Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第7期1761-1763,共3页
Dear Editor,This letter presents an intelligent fault diagnosis method for variable speed rolling bearings based on the adaptive short-time fractional Fourier transform(ASTFrFT)and the time-frequency BoTNet(TFB)to add... Dear Editor,This letter presents an intelligent fault diagnosis method for variable speed rolling bearings based on the adaptive short-time fractional Fourier transform(ASTFrFT)and the time-frequency BoTNet(TFB)to address the challenge of extracting fault characteristics of rolling bearings under variable speed conditions and the poor classification of classical deep learning models.Firstly,to address the limitations of FrFT in time-varying signal processing,the physical mechanism of traditional STFT is extended into the FrFT domain by minimizing fuzzy entropy values to construct the order matrix. 展开更多
关键词 variable speed rolling bearings time frequency botnet rolling bearings deep learning modelsfirstlyto variable speed adaptive short time fractional fourier transform extracting fault characteristics intelligent fault diagnosis
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Monitoring Peer-to-Peer Botnets:Requirements,Challenges,and Future Works 认领 引用 被引量：1
2
作者 Arkan Hammoodi Hasan Kabla Mohammed Anbar +2 位作者 Selvakumar Manickam Alwan Ahmed Abdulrahman Alwan Shankar Karuppayah 《Computers, Materials & Continua》 SCIE EI 2023年第5期3375-3398,共24页
The cyber-criminal compromises end-hosts(bots)to configure a network of bots(botnet).The cyber-criminals are also looking for an evolved architecture that makes their techniques more resilient and stealthier such as P... The cyber-criminal compromises end-hosts(bots)to configure a network of bots(botnet).The cyber-criminals are also looking for an evolved architecture that makes their techniques more resilient and stealthier such as Peer-to-Peer(P2P)networks.The P2P botnets leverage the privileges of the decentralized nature of P2P networks.Consequently,the P2P botnets exploit the resilience of this architecture to be arduous against take-down procedures.Some P2P botnets are smarter to be stealthy in their Commandand-Control mechanisms(C2)and elude the standard discovery mechanisms.Therefore,the other side of this cyberwar is the monitor.The P2P botnet monitoring is an exacting mission because the monitoring must care about many aspects simultaneously.Some aspects pertain to the existing monitoring approaches,some pertain to the nature of P2P networks,and some to counter the botnets,i.e.,the anti-monitoring mechanisms.All these challenges should be considered in P2P botnet monitoring.To begin with,this paper provides an anatomy of P2P botnets.Thereafter,this paper exhaustively reviews the existing monitoring approaches of P2P botnets and thoroughly discusses each to reveal its advantages and disadvantages.In addition,this paper groups the monitoring approaches into three groups:passive,active,and hybrid monitoring approaches.Furthermore,this paper also discusses the functional and non-functional requirements of advanced monitoring.In conclusion,this paper ends by epitomizing the challenges of various aspects and gives future avenues for better monitoring of P2P botnets. 展开更多
关键词 P2P networks botnet P2P botnet botnet monitoring honeypot crawlers
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Hybrid Detection and Tracking of Fast-Flux Botnet on Domain Name System Traffic 认领 引用 被引量：5
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作者 邹福泰 章思宇 饶卫雄 《China Communications》 SCIE CSCD 2013年第11期81-94,共14页
Fast-flux is a Domain Name System(DNS)technique used by botnets to organise compromised hosts into a high-availability,loadbalancing network that is similar to Content Delivery Networks(CDNs).Fast-Flux Service Network... Fast-flux is a Domain Name System(DNS)technique used by botnets to organise compromised hosts into a high-availability,loadbalancing network that is similar to Content Delivery Networks(CDNs).Fast-Flux Service Networks(FFSNs)are usually used as proxies of phishing websites and malwares,and hide upstream servers that host actual content.In this paper,by analysing recursive DNS traffic,we develop a fast-flux domain detection method which combines both real-time detection and long-term monitoring.Experimental results demonstrate that our solution can achieve significantly higher detection accuracy values than previous flux-score based algorithms,and is light-weight in terms of resource consumption.We evaluate the performance of the proposed fast-flux detection and tracking solution during a 180-day period of deployment on our university’s DNS servers.Based on the tracking results,we successfully identify the changes in the distribution of FFSN and their roles in recent Internet attacks. 展开更多
关键词 domain name system botnet fast-flux
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DNNBoT: Deep Neural Network-Based Botnet Detection and Classification 认领 引用 被引量：9
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作者 Mohd Anul Haq Mohd Abdul Rahim Khan 《Computers, Materials & Continua》 SCIE EI 2022年第4期1729-1750,共22页
The evolution and expansion of IoT devices reduced human efforts,increased resource utilization, and saved time;however, IoT devices createsignificant challenges such as lack of security and privacy, making them morev... The evolution and expansion of IoT devices reduced human efforts,increased resource utilization, and saved time;however, IoT devices createsignificant challenges such as lack of security and privacy, making them morevulnerable to IoT-based botnet attacks. There is a need to develop efficientand faster models which can work in real-time with efficiency and stability. The present investigation developed two novels, Deep Neural Network(DNN) models, DNNBoT1 and DNNBoT2, to detect and classify well-knownIoT botnet attacks such as Mirai and BASHLITE from nine compromisedindustrial-grade IoT devices. The utilization of PCA was made to featureextraction and improve effectual and accurate Botnet classification in IoTenvironments. The models were designed based on rigorous hyperparameterstuning with GridsearchCV. Early stopping was utilized to avoid the effects ofoverfitting and underfitting for both DNN models. The in-depth assessmentand evaluation of the developed models demonstrated that accuracy andefficiency are some of the best-performed models. The novelty of the presentinvestigation, with developed models, bridge the gaps by using a real datasetwith high accuracy and a significantly lower false alarm rate. The results wereevaluated based on earlier studies and deemed efficient at detecting botnetattacks using the real dataset. 展开更多
关键词 Botnet network monitoring machine learning deep neural network IoT threat
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Detecting Encrypted Botnet Traffic Using Spatial-Temporal Correlation 认领 引用 被引量：3
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作者 Chen Wei Yu Le Yang Geng 《China Communications》 SCIE CSCD 2012年第10期49-59,共11页
In this paper, we to detect encrypted botnet propose a novel method traffic. During the traffic preprocessing stage, the proposed payload extraction method can identify a large amount of encrypted applications traffic... In this paper, we to detect encrypted botnet propose a novel method traffic. During the traffic preprocessing stage, the proposed payload extraction method can identify a large amount of encrypted applications traffic. It can filter out a large amount of non-malicious traffic, greatly in, roving the detection efficiency. A Sequential Probability Ratio Test （SPRT）-based method can find spatialtemporal correlations in suspicious botnet traffic and make an accurate judgment. Experimental resuks show that the false positive and false nega- tive rates can be controlled within a certain range. 展开更多
关键词 botnet encrypted traffic spatial-tenmporal correlation
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A Learning Evasive Email-Based P2P-Like Botnet 认领 引用 被引量：1
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作者 Zhi Wang Meilin Qin +2 位作者 Mengqi Chen Chunfu Jia Yong Ma 《China Communications》 SCIE CSCD 2018年第2期15-24,共10页
Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution... Nowadays, machine learning is widely used in malware detection system as a core component. The machine learning algorithm is designed under the assumption that all datasets follow the same underlying data distribution. But the real-world malware data distribution is not stable and changes with time. By exploiting the knowledge of the machine learning algorithm and malware data concept drift problem, we show a novel learning evasive botnet architecture and a stealthy and secure C&C mechanism. Based on the email communication channel, we construct a stealthy email-based P2 P-like botnet that exploit the excellent reputation of email servers and a huge amount of benign email communication in the same channel. The experiment results show horizontal correlation learning algorithm is difficult to separate malicious email traffic from normal email traffic based on the volume features and time-related features with enough confidence. We discuss the malware data concept drift and possible defense strategies. 展开更多
关键词 malware botnet learning evasion command and control
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Detection of P2P botnet based on network behavior features and Dezert-Smarandache theory 认领 引用 被引量：1
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作者 Song Yuanzhang Chen Yuan +2 位作者 Wang Junjie Wang Anbang Li Hongyu 《Journal of Southeast University(English Edition)》 EI CAS 2018年第2期191-198,共8页
In order to improve the accuracy of detecting the new P2P(peer-to-peer)botnet,a novel P2P botnet detection method based on the network behavior features and Dezert-Smarandache theory is proposed.It focuses on the netw... In order to improve the accuracy of detecting the new P2P(peer-to-peer)botnet,a novel P2P botnet detection method based on the network behavior features and Dezert-Smarandache theory is proposed.It focuses on the network behavior features,which are the essential abnormal features of the P2P botnet and do not change with the network topology,the network protocol or the network attack type launched by the P2P botnet.First,the network behavior features are accurately described by the local singularity and the information entropy theory.Then,two detection results are acquired by using the Kalman filter to detect the anomalies of the above two features.Finally,the above two detection results are fused with the Dezert-Smarandache theory to obtain the final detection results.The experimental results demonstrate that the proposed method can effectively detect the new P2P botnet and that it considerably outperforms other methods at a lower degree of false negative rate and false positive rate,and the false negative rate and the false positive rate can reach 0.09 and 0.12,respectively. 展开更多
关键词 P2P(peer-to-peer)botnet local singularity entropy Kalman filter Dezert-Smarandache theory
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利用多维观测序列的KCFM混合模型检测新型P2P botnet 认领 引用 被引量：3
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作者 康健 宋元章 《武汉大学学报（信息科学版）》 EI CAS 北大核心 2010年第5期520-523,共4页
提出了一种新颖的综合考虑多维观测序列的实时检测模型——KCFM。通过抽取新型分散式P2Pbotnet的多个特征构成多维观测序列,使用离散Kalman滤波算法发现流量异常变化,将Multi-chart CUSUM作为差异放大器提高检测精度。实验表明,基于多... 提出了一种新颖的综合考虑多维观测序列的实时检测模型——KCFM。通过抽取新型分散式P2Pbotnet的多个特征构成多维观测序列,使用离散Kalman滤波算法发现流量异常变化,将Multi-chart CUSUM作为差异放大器提高检测精度。实验表明,基于多维观测序列的KCFM模型能够有效地检测新型P2Pbotnet。 展开更多
关键词 P2Pbotnet 离散Kalman滤波 Multi-chartCUSUM
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网络恶意程序“Botnet”的检测技术的分析 认领 引用 被引量：1
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作者 倪红彪 《煤炭技术》 CAS 北大核心 2011年第12期172-173,共2页
目前Botnet技术发展最为快速,不论是对网络安全运行还是用户数据安全的保护来说,Botnet都是极具威胁的隐患。介绍了Botnet技术的同时也对Botnet检测技术进行了研究,对几种主要的Botnet检测技术进行了深入分析。
关键词 Botnet 安全 检测技术
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BotGuard: Lightweight Real-Time Botnet Detection in Software Defined Networks 认领 引用
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作者 CHEN Jing CHENG Xi +2 位作者 DU Ruiying HU Li WANG Chiheng 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2017年第2期103-113,共11页
The distributed detection of botnets may induce heavy computation and communication costs to network devices. Each device in related scheme only has a regional view of Internet, so it is hard to detect botnet comprehe... The distributed detection of botnets may induce heavy computation and communication costs to network devices. Each device in related scheme only has a regional view of Internet, so it is hard to detect botnet comprehensively. In this paper, we propose a lightweight real-time botnet detection framework called Bot-Guard, which uses the global landscape and flexible configurability of software defined network （SDN） to identify botnets promptly. SDN, as a new network framework, can make centralized control in botnet detection, but there are still some challenges in such detections. We give a convex lens imaging graph （CLI-graph） to depict the topology characteristics of botnet, which allows SDN controller to locate attacks separately and mitigate the burden of network devices. The theoretical and experimental resuits prove that our scheme is capable of timely botnet detecting in SDNs with the accuracy higher than 90% and the delay less than 56 ms. 展开更多
关键词 botnet detection software defined network graph theory
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蜜罐先知型半分布式P2P Botnet的构建及检测方法 认领 引用
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作者 谢静 谭良 周明天 《计算机工程与应用》 CSCD 北大核心 2011年第7期89-92,共4页
蜜罐技术在僵尸网络(botnet)的防御和检测中扮演着重要的角色。攻击者可能会利用已有的基于蜜罐防御技术的漏洞,即防御者配置蜜罐要担当一定的责任,不允许蜜罐参与真实的攻击,进而构建出可以躲避蜜罐的botnet。针对这一问题,提出了攻击... 蜜罐技术在僵尸网络(botnet)的防御和检测中扮演着重要的角色。攻击者可能会利用已有的基于蜜罐防御技术的漏洞,即防御者配置蜜罐要担当一定的责任,不允许蜜罐参与真实的攻击,进而构建出可以躲避蜜罐的botnet。针对这一问题,提出了攻击者利用认证sensor组建的蜜罐先知型半分布式P2P botnet,针对此类botnet,提出了用高交互性蜜罐和低交互性蜜罐相结合的双重蜜罐检测技术,并与传统蜜罐技术做了比较。理论分析表明,该检测方法能够有效地弥补蜜罐防御技术的漏洞,提高了蜜罐先知型半分布式P2P botnet的检出率。 展开更多
关键词 半分布式P2P botnet 蜜罐先知 双重蜜罐 检测模型
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半分布式P2P Botnet的检测方法研究 认领 引用
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作者 谢静 谭良 《计算机应用研究》 北大核心 2009年第10期3925-3928,共4页
Botnet近来已经是网络安全中最为严重的威胁之一,过去出现的Botnet大多数是基于IRC机制,检测方法也大都是针对这种类型的。随着P2P技术的广泛应用,半分布式P2P Botnet已经成为一种新的网络攻击手段。由于半分布式P2P Botnet的servent bo... Botnet近来已经是网络安全中最为严重的威胁之一,过去出现的Botnet大多数是基于IRC机制,检测方法也大都是针对这种类型的。随着P2P技术的广泛应用,半分布式P2P Botnet已经成为一种新的网络攻击手段。由于半分布式P2P Botnet的servent bot的分布范围大、网络直径宽而冗余度小,造成的危害已越来越大,对半分布式的Botnet的检测研究具有现实意义。阐述了半分布式P2P Botnet的定义、功能结构与工作机制,重点分析了目前半分布式P2P Botnet几种流行的检测方法,并进行了对比;最后,对半分布式P2P Botnet检测方法的发展趋势进行了展望。 展开更多
关键词 半分布P2P Botnet 检测模型 蜜罐 流量分析 钩子
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Botnet技术现状及发展趋势探讨 认领 引用 被引量：1
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作者 傅务谨 《襄樊学院学报》 2009年第8期42-45,共4页
Botnet(僵尸网络)是对互联网安全最严重的威胁之一.分析了目前Botnet的结构及其技术现状,阐述了Botnet分类、检测方法,最后对Botnet的发展趋势进行了概述并提出相应的应对策略.
关键词 Botnet 网络安全 P2P
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基于Light-BotNet的激光点云分类研究 认领 引用 被引量：5
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作者 雷根华 王蕾 张志勇 《电子技术应用》 2022年第6期84-88,97,共5页
三维点云在机器人与自动驾驶中都有着普遍的应用,深度学习在二维图像上的研究成果显著,但是如何利用深度学习识别不规则的三维点云,仍然是一个开放性的问题。目前大场景点云自身数据的复杂性,点云扫描距离的变化造成点的分布不均匀,噪... 三维点云在机器人与自动驾驶中都有着普遍的应用,深度学习在二维图像上的研究成果显著,但是如何利用深度学习识别不规则的三维点云,仍然是一个开放性的问题。目前大场景点云自身数据的复杂性,点云扫描距离的变化造成点的分布不均匀,噪声和异常点引起的挑战性依然存在。针对于现有的深度学习网络框架对于激光点云数据的分类效率不高以及分类精度低的问题,提出一种基于激光点云特征图像与Light-BotNet相结合的CNN-Transform框架。该框架在于通过对点云数据进行特征提取,以相邻的特征点构造点云特征图像作为网络框架的输入,最后以Light-BotNet为网络框架模型进行点云分类训练。实验结果表明,该方法与现有的多数点云分类方法相比,能够较好地提升激光点云的分类效率以及分类精度。 展开更多
关键词 点云特征图像 BotNet Transform CNN 激光点云分类
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An Adaptive Push-Styled Command and Control Mechanism in Mobile Botnets 认领 引用 被引量：6
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作者 CHEN Wei GONG Peihua +1 位作者 YU Le YANG Geng 《Wuhan University Journal of Natural Sciences》 CAS 2013年第5期427-434,共8页
The mobile botnet, developed from the traditional PC-based botnets, has become a practical underlying trend. In this paper, we design a mobile botnet, which exploits a novel command and control （CC） strategy named P... The mobile botnet, developed from the traditional PC-based botnets, has become a practical underlying trend. In this paper, we design a mobile botnet, which exploits a novel command and control （CC） strategy named Push-Styled CC. It utilizes Google cloud messaging （GCM） service as the botnet channel. Compared with traditional botnet, Push-Styled CC avoids direct communications between botmasters and bots, which makes mobile botnets more stealthy and resilient. Since mobile devices users are sensitive to battery power and traffic consumption, Push- Styled botnet also applies adaptive network connection strategy to reduce traffic consumption and cost. To prove the efficacy of our design, we implemented the prototype of Push-Style CC in Android. The experiment results show that botnet traffic can be concealed in legal GCM traffic with low traffic cost. 展开更多
关键词 mobile botnet push style Google cloud messaging （GCM） adaptive connection
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Securing Consumer Internet of Things for Botnet Attacks: Deep Learning Approach 认领 引用 被引量：1
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作者 Tariq Ahamed Ahanger Abdulaziz Aldaej +2 位作者 Mohammed Atiquzzaman Imdad Ullah Mohammed Yousuf Uddin 《Computers, Materials & Continua》 SCIE EI 2022年第11期3199-3217,共19页
DDoS attacks in the Internet of Things(IoT)technology have increased significantly due to its spread adoption in different industrial domains.The purpose of the current research is to propose a novel technique for det... DDoS attacks in the Internet of Things(IoT)technology have increased significantly due to its spread adoption in different industrial domains.The purpose of the current research is to propose a novel technique for detecting botnet attacks in user-oriented IoT environments.Conspicuously,an attack identification technique inspired by Recurrent Neural networks and Bidirectional Long Short Term Memory(BLRNN)is presented using a unique Deep Learning(DL)technique.For text identification and translation of attack data segments into tokenized form,word embedding is employed.The performance analysis of the presented technique is performed in comparison to the state-of-the-art DL techniques.Specifically,Accuracy(98.4%),Specificity(98.7%),Sensitivity(99.0%),F-measure(99.0%)and Data loss(92.36%)of the presented BLRNN detection model are determined for identifying 4 attacks over Botnet(Mirai).The results show that,although adding cost to each epoch and increasing computation delay,the bidirectional strategy is more superior technique model over different data instances. 展开更多
关键词 Internet of Things deep learning security DDoS attack botnet
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Design the IoT Botnet Defense Process for Cybersecurity in Smart City 认领 引用 被引量：1
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作者 Donghyun Kim Seungho Jeon +1 位作者 Jiho Shin Jung Taek Seo 《Intelligent Automation & Soft Computing》 SCIE 2023年第9期2979-2997,共19页
The smart city comprises various infrastructures,including health-care,transportation,manufacturing,and energy.A smart city’s Internet of Things(IoT)environment constitutes a massive IoT environment encom-passing num... The smart city comprises various infrastructures,including health-care,transportation,manufacturing,and energy.A smart city’s Internet of Things(IoT)environment constitutes a massive IoT environment encom-passing numerous devices.As many devices are installed,managing security for the entire IoT device ecosystem becomes challenging,and attack vectors accessible to attackers increase.However,these devices often have low power and specifications,lacking the same security features as general Information Technology(IT)systems,making them susceptible to cyberattacks.This vulnerability is particularly concerning in smart cities,where IoT devices are connected to essential support systems such as healthcare and transportation.Disruptions can lead to significant human and property damage.One rep-resentative attack that exploits IoT device vulnerabilities is the Distributed Denial of Service(DDoS)attack by forming an IoT botnet.In a smart city environment,the formation of IoT botnets can lead to extensive denial-of-service attacks,compromising the availability of services rendered by the city.Moreover,the same IoT devices are typically employed across various infrastructures within a smart city,making them potentially vulnerable to similar attacks.This paper addresses this problem by designing a defense process to effectively respond to IoT botnet attacks in smart city environ-ments.The proposed defense process leverages the defense techniques of the MITRE D3FEND framework to mitigate the propagation of IoT botnets and support rapid and integrated decision-making by security personnel,enabling an immediate response. 展开更多
关键词 Smart city IoT botnet cybersecurity
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The Machine Learning Ensemble for Analyzing Internet of Things Networks:Botnet Detection and Device Identification 认领 引用 被引量：1
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作者 Seung-Ju Han Seong-Su Yoon Ieck-Chae Euom 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第11期1495-1518,共24页
The rapid proliferation of Internet of Things(IoT)technology has facilitated automation across various sectors.Nevertheless,this advancement has also resulted in a notable surge in cyberattacks,notably botnets.As a re... The rapid proliferation of Internet of Things(IoT)technology has facilitated automation across various sectors.Nevertheless,this advancement has also resulted in a notable surge in cyberattacks,notably botnets.As a result,research on network analysis has become vital.Machine learning-based techniques for network analysis provide a more extensive and adaptable approach in comparison to traditional rule-based methods.In this paper,we propose a framework for analyzing communications between IoT devices using supervised learning and ensemble techniques and present experimental results that validate the efficacy of the proposed framework.The results indicate that using the proposed ensemble techniques improves accuracy by up to 1.7%compared to single-algorithm approaches.These results also suggest that the proposed framework can flexibly adapt to general IoT network analysis scenarios.Unlike existing frameworks,which only exhibit high performance in specific situations,the proposed framework can serve as a fundamental approach for addressing a wide range of issues. 展开更多
关键词 Internet of Things machine learning traffic analysis botnet detection device identification
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A novel mathematical model on Peer-to-Peer botnet 认领 引用 被引量：1
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作者 任玮 宋礼鹏 冯丽萍 《Journal of Measurement Science and Instrumentation》 CAS 2014年第4期62-67,共6页
Peer-to-Peer （P2P） botnet has emerged as one of the most serious threats to lnternet security. To effectively elimi- nate P2P botnet, a delayed SEIR model is proposed,which can portray the formation process of P2P b... Peer-to-Peer （P2P） botnet has emerged as one of the most serious threats to lnternet security. To effectively elimi- nate P2P botnet, a delayed SEIR model is proposed,which can portray the formation process of P2P botnet. Then, the local stability at equilibria is carefully analyzed by considering the eigenvalues＇ distributed ranges of characteristic equations. Both mathematical analysis and numerical simulations show that the dynamical features of the proposed model rely on the basic re- production number and time delay r. The results can help us to better understand the propagation behaviors of P2P botnet and design effective counter-botnet methods. 展开更多
关键词 Peer-to-Peer （P2P） botnet stability SEIR model time delay
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一种p2p Botnet在线检测方法研究 认领 引用 被引量：10
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作者 柴胜 胡亮 梁波 《电子学报》 EI CAS CSCD 北大核心 2011年第4期906-912,共7页
文章详细分析了p2p僵尸网络的生命周期以及网络特征,利用改进的SPRINT决策树和相似度度量函数,提出了一种新的在线综合检测方法,并论述了虚拟机环境搭建、原型系统设计和实验结果分析.实验结果表明,检测方法是可行的,具有较高的效率和... 文章详细分析了p2p僵尸网络的生命周期以及网络特征,利用改进的SPRINT决策树和相似度度量函数,提出了一种新的在线综合检测方法,并论述了虚拟机环境搭建、原型系统设计和实验结果分析.实验结果表明,检测方法是可行的,具有较高的效率和可靠性. 展开更多
关键词 僵尸网络 对等网络 检测
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