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

Authors:

Vipin Chaudhary,

Xusheng XiaoAuthors Info & Claims

CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Pages 4872 - 4876

https://doi.org/10.1145/3511808.3557185

Published: 17 October 2022 Publication History

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.

Supplementary Material

MP4 File (CIKM-demo090.mp4)

Video for presentation of paper «System-Auditing, Data Analysis and Characteristics of Cyber Attacks for Big Data Systems» and it's unexpected activity detection demo.

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Cited By

Suganya SSelvamuthukumaran S(2023)Auditing of hadoop log file for dynamic detection of threats using H-ISSM-MIM and convolutional neural networkJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23357945:4(6617-6628)Online publication date: 4-Oct-2023
https://doi.org/10.3233/JIFS-233579
Nihar ACiardi TChawla RAkanbi OChaudhary VWu YFrench R(2023)Accelerating Time to Science using CRADLE: A Framework for Materials Data Science2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC)10.1109/HiPC58850.2023.00041(234-245)Online publication date: 18-Dec-2023
https://doi.org/10.1109/HiPC58850.2023.00041

Index Terms

System-Auditing, Data Analysis and Characteristics of Cyber Attacks for Big Data Systems
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Parallel and distributed DBMSs
2. Security and privacy
  1. Systems security
    1. Distributed systems security

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Published In

cover image ACM Conferences

CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management

October 2022

5274 pages

ISBN:9781450392365

DOI:10.1145/3511808

General Chairs:
Mohammad Al Hasan
Indiana University Purdue University, Indianapolis, USA
,
Li Xiong
Emory University, Atlanta, USA

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 17 October 2022

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Short-paper

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Natural Science Foundation
DOE-NNSA-LLNS

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CIKM '22

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CIKM '22: The 31st ACM International Conference on Information and Knowledge Management

October 17 - 21, 2022

GA, Atlanta, USA

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CIKM '22 Paper Acceptance Rate 621 of 2,257 submissions, 28%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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CIKM '25

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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

Suganya SSelvamuthukumaran S(2023)Auditing of hadoop log file for dynamic detection of threats using H-ISSM-MIM and convolutional neural networkJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23357945:4(6617-6628)Online publication date: 4-Oct-2023
https://doi.org/10.3233/JIFS-233579
Nihar ACiardi TChawla RAkanbi OChaudhary VWu YFrench R(2023)Accelerating Time to Science using CRADLE: A Framework for Materials Data Science2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC)10.1109/HiPC58850.2023.00041(234-245)Online publication date: 18-Dec-2023
https://doi.org/10.1109/HiPC58850.2023.00041

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