System-Auditing, Data Analysis and Characteristics of Cyber Attacks for Big Data Systems

Liangyi Huang, Sophia Hall, Fei Shao, Arafath Nihar, Vipin Chaudhary, Yinghui Wu, Roger French, Xusheng Xiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Using big data, distributed computing systems such as Apache Hadoop requires processing massive amount of data to support business and research applications. Thus, it is critical to ensure the cyber security of such systems. To better defend from advanced cyber attacks that pose threats to even well-protected enterprises, system-auditing based techniques have been adopted for monitoring system activities and assisting attack investigation. In this demo, we are building a system that collects system auditing logs from a big data system and performs data analysis to understand how system auditing can be used more effectively to assist attack investigation on big systems. We also built a demo application that detects unexpected file deletion and presents root causes for the deletion.

Original languageEnglish (US)
Title of host publicationCIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages4872-4876
Number of pages5
ISBN (Electronic)9781450392365
DOIs
StatePublished - Oct 17 2022
Event31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States
Duration: Oct 17 2022Oct 21 2022

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings
ISSN (Print)2155-0751

Conference

Conference31st ACM International Conference on Information and Knowledge Management, CIKM 2022
Country/TerritoryUnited States
CityAtlanta
Period10/17/2210/21/22

Keywords

  • big data systems
  • cyber attack investigation
  • system auditing

ASJC Scopus subject areas

  • General Business, Management and Accounting
  • General Decision Sciences

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