Conversation Based P2P Botnet Detection with Decision Fusion PDF Download
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Author: Shaojun Zhang
Publisher:
ISBN:
Category : Computer networks
Languages : en
Pages : 122
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Book Description
"Botnets have been identified as one of the most dangerous threats through the Internet. A botnet is a collection of compromised computers called zombies or bots controlled by malicious machines called botmasters through the command and control (C&C) channel. Botnets can be used for plenty of malicious behaviours, including DDOS, Spam, stealing sensitive information to name a few, all of which could be very serious threats to parts of the Internet. In this thesis, we propose a peer-to-peer (P2P) botnet detection approach based on 30-second conversation. To the best of our knowledge, this is the first time conversation-based features are used to detect P2P botnets. The features extracted from conversations can differentiate P2P botnet conversations from normal conversations by applying machine learning techniques. Also, feature selection processes are carried out in order to reduce the dimension of the feature vectors. Decision tree (DT) and support vector machine (SVM) are applied to classify the normal conversations and the P2P botnet conversations. Finally, the results from different classifiers are combined based on the probability models in order to get a better result."--Page ii.
Author: Shaojun Zhang
Publisher:
ISBN:
Category : Computer networks
Languages : en
Pages : 122
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Book Description
"Botnets have been identified as one of the most dangerous threats through the Internet. A botnet is a collection of compromised computers called zombies or bots controlled by malicious machines called botmasters through the command and control (C&C) channel. Botnets can be used for plenty of malicious behaviours, including DDOS, Spam, stealing sensitive information to name a few, all of which could be very serious threats to parts of the Internet. In this thesis, we propose a peer-to-peer (P2P) botnet detection approach based on 30-second conversation. To the best of our knowledge, this is the first time conversation-based features are used to detect P2P botnets. The features extracted from conversations can differentiate P2P botnet conversations from normal conversations by applying machine learning techniques. Also, feature selection processes are carried out in order to reduce the dimension of the feature vectors. Decision tree (DT) and support vector machine (SVM) are applied to classify the normal conversations and the P2P botnet conversations. Finally, the results from different classifiers are combined based on the probability models in order to get a better result."--Page ii.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
Author: Suyu Gu
Publisher:
ISBN:
Category : Computer networks
Languages : en
Pages : 174
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Book Description
A botnet, which is created to conduct large-scale illegal activities, has become a serious threat to the Internet. Recently, botnets started to utilize a decentralized structure in their command and control channel, which is a more robust and resilient communication infrastructure. P2P botnets, created based on a variety of P2P protocols, are the most representative decentralized botnets and have caused great loss to Internet users. Although a lot of botnet detection techniques have been developed, the existing P2P botnet detection methods are still limited. In this thesis, we present a novel P2P botnet detection system based on an analysis of network behavior. The proposed detection system consists of three main components: Network Packets Capturing, Node Feature Extraction, and Online Classifier. In this thesis, we explain the proposed algorithms and implementation methods for each component in detail. Moreover, in this thesis we also present two novel combined classifiers that integrate supervised machine learning and unsupervised machine learning techniques. One, called Sequential Combined Classifier aims at further enhancing the detection rate; the other one, called Parallel Combined Classifier aims at detecting unknown P2P botnet traffic. Based on three real-world network traffic trace sets (i.e. Storm trace, Waledac trace, and normal traffic trace), a series of evaluation experiments are conducted and their results are reported in this thesis. Several contributions from the evaluation results include (1) identification of an appropriate time window size that allows to provide a better detection performance when used in system's packets capturing module; (2) optimized configuration for system's online classifier in each time window size; and (3) evaluated the effectiveness of two proposed combined classifiers and verified their ability to improve detection rate or detect unknown botnet traffic. According experimental results, we obtain the detection accuracy of 99.0% and the false positive rate of 0.1%.
Author: 陳品豪
Publisher:
ISBN:
Category :
Languages : en
Pages : 28
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Book Description
Author: 吳偉誠
Publisher:
ISBN:
Category :
Languages : en
Pages : 47
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Book Description
Author: Ciza Thomas
Publisher: BoD – Books on Demand
ISBN: 1838802398
Category : Computers
Languages : en
Pages : 132
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Book Description
This book on computer security threats explores the computer security threats and includes a broad set of solutions to defend the computer systems from these threats. The book is triggered by the understanding that digitalization and growing dependence on the Internet poses an increased risk of computer security threats in the modern world. The chapters discuss different research frontiers in computer security with algorithms and implementation details for use in the real world. Researchers and practitioners in areas such as statistics, pattern recognition, machine learning, artificial intelligence, deep learning, data mining, data analytics and visualization are contributing to the field of computer security. The intended audience of this book will mainly consist of researchers, research students, practitioners, data analysts, and business professionals who seek information on computer security threats and its defensive measures.
Author: Mamoun Alazab
Publisher: Springer
ISBN: 3030130576
Category : Computers
Languages : en
Pages : 246
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Book Description
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Author: Lorraine Goeuriot
Publisher: Springer Nature
ISBN: 3031717368
Category :
Languages : en
Pages : 286
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Book Description
Author: Clay Wilson
Publisher:
ISBN: 9781606923375
Category : Computer networks
Languages : en
Pages : 0
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Book Description
Many international terrorist groups now actively use computers and the Internet to communicate, and several may develop or acquire the necessary technical skills to direct a co-ordinated attack against computers in the United States. A cyberattack intended to harm the U.S. economy would likely target computers that operate the civilian critical infrastructure and government agencies. However, there is disagreement among some observers about whether a co-ordinated cyberattack against the U.S. critical infrastructure could be extremely harmful, or even whether computers operating the civilian critical infrastructure actually offer an effective target for furthering terrorists' goals. While there is no published evidence that terrorist organisations are currently planning a co-ordinated attack against computers, computer system vulnerabilities persist world-wide, and initiators of the random cyberattacks that plague computers on the Internet remain largely unknown. Reports from security organisations show that random attacks are now increasingly implemented through use of automated tools, called "bots", that direct large numbers of compromised computers to launch attacks through the Internet as swarms. The growing trend toward the use of more automated attack tools has also overwhelmed some of the current methodologies used for tracking Internet cyberattacks. This book provides background information for three types of attacks against computers (cyberattack, physical attack, and electromagnetic attack), and discusses related vulnerabilities for each type of attack. The book also describes the possible effects of a co-ordinated cyberattack, or computer network attack (CNA), against U.S. infrastructure computers, along with possible technical capabilities of international terrorists. Issues for Congress may include how could trends in cyberattacks be measured more effectively; what is appropriate guidance for DOD use of cyberweapons; should cybersecurity be combined with, or remain separate from, the physical security organization within DHS; how can commercial vendors be encouraged to improve the security of their products; and what are options to encourage U.S. citizens to follow better cybersecurity practices? Appendices to this book describe computer viruses, spyware, and "bot networks", and how malicious programs are used to enable cybercrime and cyberespionage. Also, similarities are drawn between planning tactics currently used by computer hackers and those used by terrorists groups for conventional attacks.
Author: Mayank Dave
Publisher: Springer Nature
ISBN: 9811575339
Category : Technology & Engineering
Languages : en
Pages : 1001
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Book Description
This book presents best selected papers presented at the International Conference on Paradigms of Computing, Communication and Data Sciences (PCCDS 2020), organized by National Institute of Technology, Kurukshetra, India, during 1–3 May 2020. It discusses high-quality and cutting-edge research in the areas of advanced computing, communications and data science techniques. The book is a collection of latest research articles in computation algorithm, communication and data sciences, intertwined with each other for efficiency.
