Journal ArticleDOI
DTB-IDS: an intrusion detection system based on decision tree using behavior analysis for preventing APT attacks
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TLDR
An intrusion detection system based on the decision tree using analysis of behavior information to detect APT attacks that intellectually change after intrusion into a system is proposed.Abstract:
Due to rapid growth of communications and networks, a cyber-attack with malicious codes has been coming as a new paradigm in information security area since last few years. In particular, an advanced persistent threats (APT) attack is bringing out big social issues. The APT attack uses social engineering methods to target various systems for intrusions. It breaks down the security of the target system to leak information or to destroy the system by giving monetary damages on the target. APT attacks make relatively simple attacks such as spear phishing during initial intrusion but a back door is created by leaking the long-term information after initial intrusion, and it transmits the malicious code by analyzing the internal network. In this paper, we propose an intrusion detection system based on the decision tree using analysis of behavior information to detect APT attacks that intellectually change after intrusion into a system. Furthermore, it can detect the possibility on the initial intrusion and minimize the damage size by quickly responding to APT attacks.read more
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Journal ArticleDOI
Machine Learning and Deep Learning Methods for Cybersecurity
Yang Xin,Lingshuang Kong,Liu Zhi,Yuling Chen,Yanmiao Li,Hongliang Zhu,Mingcheng Gao,Haixia Hou,Chunhua Wang +8 more
TL;DR: This survey report describes key literature surveys on machine learning (ML) and deep learning (DL) methods for network analysis of intrusion detection and provides a brief tutorial description of each ML/DL method.
Journal ArticleDOI
Cybersecurity data science: an overview from machine learning perspective
Iqbal H. Sarker,Iqbal H. Sarker,A. S. M. Kayes,Shahriar Badsha,Hamed Alqahtani,Paul A. Watters,Alex Hay-Man Ng +6 more
TL;DR: This paper focuses and briefly discusses on cybersecurity data science, where the data is being gathered from relevant cybersecurity sources, and the analytics complement the latest data-driven patterns for providing more effective security solutions.
Journal ArticleDOI
A Survey on Machine Learning Techniques for Cyber Security in the Last Decade
TL;DR: This paper aims to provide a comprehensive overview of the challenges that ML techniques face in protecting cyberspace against attacks, by presenting a literature on ML techniques for cyber security including intrusion detection, spam detection, and malware detection on computer networks and mobile networks in the last decade.
Journal ArticleDOI
Cyber security meets artificial intelligence: a survey
TL;DR: This work summarizes existing research efforts in terms of combating cyber attacks using AI, including adopting traditional machine learning methods and existing deep learning solutions, and expatiates the existing research on how to build a secure AI system.
Journal ArticleDOI
IntruDTree: A Machine Learning Based Cyber Security Intrusion Detection Model
TL;DR: This paper presents an Intrusion Detection Tree (“IntruDTree”) machine-learning-based security model that first takes into account the ranking of security features according to their importance and then builds a tree-based generalized intrusion detection model based on the selected important features.
References
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Journal ArticleDOI
Review: Intrusion detection system: A comprehensive review
TL;DR: Through the extensive survey and sophisticated organization, this work proposes the taxonomy to outline modern IDSs and tries to give a more elaborate image for a comprehensive review.
Journal ArticleDOI
A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS
TL;DR: In this paper, three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) were compared for landslide susceptibility mapping at Penang Hill area, Malaysia.
Journal ArticleDOI
Review: A survey of intrusion detection techniques in Cloud
TL;DR: This paper surveys different intrusions affecting availability, confidentiality and integrity of Cloud resources and services and recommends IDS/IPS positioning in Cloud environment to achieve desired security in the next generation networks.
Proceedings ArticleDOI
IMDS: intelligent malware detection system
TL;DR: Promising experimental results demonstrate that the accuracy and efficiency of the IMDS system out perform popular anti-virus software such as Norton AntiVirus and McAfee VirusScan, as well as previous data mining based detection systems which employed Naive Bayes, Support Vector Machine and Decision Tree techniques.
Journal ArticleDOI
A novel approach to detect malware based on API call sequence analysis
TL;DR: A novel approach for dynamic analysis of malware is proposed that adopts DNA sequence alignment algorithms and extracts common API call sequence patterns of malicious function from malware in different categories and finds that certain malicious functions are commonly included in malware even inDifferent categories.
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