Kellect: A Kernel-based efficient and lossless event log collector for windows security

IF 4.8 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Computers & Security Pub Date : 2024-12-05 DOI:10.1016/j.cose.2024.104203
Tieming Chen, Qijie Song, Tiantian Zhu, Xuebo Qiu, Zhiling Zhu, Mingqi Lv
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Abstract

Recently, APT attacks have frequently happened, which are increasingly complicated. Research on dynamic detection and tracing of APT via audit logs has been widely of concern. For Windows, ETW(events tracing for Windows) is a well-known built-in kernel-level logs collection framework. However, existing log collection tools built on ETW suffer from working shortages, including data loss, high overhead, and weak real-time performance. Therefore, It is still challenging to directly apply ETW-based Windows tools to analyze APT attack scenarios. To address these challenges, this paper proposes an efficient and lossless kernel log collector based on ETW called Kellect. The collector dynamically optimizes the number of cache and processing threads through a multi-level cache for lossless collecting and significantly enhances analysis performance by replacing the native TDH library with a sliding pointer. Furthermore, Kellect enhances log semantics understanding by maintaining event mappings and application callstacks which provide more comprehensive characteristics for security event behavior analysis. Additionally, Kellect has compatibility with different OS versions.
With plenty of experiments, Kellect demonstrates its capability to achieve non-destructive, real-time, and full collection of kernel log data generated from events with a comprehensive efficiency of 9 times greater than existing tools. It only takes extra CPU usage with approximately 2%–3% and about 40MB memory consumption. As a killer illustration to show how Kellect can work for APT, full data logs have been collected as a dataset Kellect4APT, generated by implementing diversity TTPs from the latest ATT&CK. To our best knowledge, it is the first open benchmark dataset representing ATT&CK technique-specific behaviors, which could be highly expected to improve more extensive research on APT studies.
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来源期刊
Computers & Security
Computers & Security 工程技术-计算机:信息系统
CiteScore
12.40
自引率
7.10%
发文量
365
审稿时长
10.7 months
期刊介绍: Computers & Security is the most respected technical journal in the IT security field. With its high-profile editorial board and informative regular features and columns, the journal is essential reading for IT security professionals around the world. Computers & Security provides you with a unique blend of leading edge research and sound practical management advice. It is aimed at the professional involved with computer security, audit, control and data integrity in all sectors - industry, commerce and academia. Recognized worldwide as THE primary source of reference for applied research and technical expertise it is your first step to fully secure systems.
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