A Comprehensive survey of Machine Learning for Intrusion Detection
نویسندگان
چکیده
منابع مشابه
A Hybrid Machine Learning Method for Intrusion Detection
Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...
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Detection of unknown attacks in network traffic is gaining increasing importance as modern attacks are characterized by high variabilities and mutation rates. Traditional signature-based intrusion detection systems (IDS) are not able to detect unknown attacks due to failing availability of appropriate signatures. We present an alternative approach based on machine learning techniques which enab...
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In today’s world, almost everybody is affluent with computers and network based technology is growing by leaps and bounds. So, network security has become very important, rather an inevitable part of computer system. An Intrusion Detection System (IDS) is designed to detect system attacks and classify system activities into normal and abnormal form. Machine learning techniques have been applied...
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Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher de...
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Cyber security is an important and growing area of data mining and machine learning applications. We address the problem of distinguishing benign network traffic from malicious network-based attacks. Given a labeled dataset of some 5M network connection traces, we have implemented both supervised (Decision Trees, Random Forests) and unsupervised (Local Outlier Factor) learning algorithms to sol...
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ژورنال
عنوان ژورنال: International Journal of Research in Advent Technology
سال: 2019
ISSN: 2321-9637
DOI: 10.32622/ijrat.72201941