Threat Hunting in Windows Using Big Security Log Data

Author:

Fatemi Mohammad Rasool1,Ghorbani Ali A.1

Affiliation:

1. University of New Brunswick, Canada

Abstract

System logs are one of the most important sources of information for anomaly and intrusion detection systems. In a general log-based anomaly detection system, network, devices, and host logs are all collected and used together for analysis and the detection of anomalies. However, the ever-increasing volume of logs remains as one of the main challenges that anomaly detection tools face. Based on Sysmon, this chapter proposes a host-based log analysis system that detects anomalies without using network logs to reduce the volume and to show the importance of host-based logs. The authors implement a Sysmon parser to parse and extract features from the logs and use them to perform detection methods on the data. The valuable information is successfully retained after two extensive volume reduction steps. An anomaly detection system is proposed and performed on five different datasets with up to 55,000 events which detects the attacks using the preserved logs. The analysis results demonstrate the significance of host-based logs in auditing, security monitoring, and intrusion detection systems.

Publisher

IGI Global

Reference30 articles.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Survey on Threat Hunting in Enterprise Networks;IEEE Communications Surveys & Tutorials;2023

2. An Analysis of Insider Attack Detection Using Machine Learning Algorithms;2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC);2022-12-02

3. Evaluation of Local Security Event Management System vs. Standard Antivirus Software;Applied Sciences;2022-01-20

4. Handling Insider Threat Through Supervised Machine Learning Techniques;Procedia Computer Science;2020

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