Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System

Stuart Laing; Robert Ludwiniak; Brahim El Boudani; Christos Chrysoulas; George Ubakanma; Nikolaos Pitropakis

doi:10.1109/DRCN57075.2023.10108330

Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System

Stuart Laing^*
, Robert Ludwiniak
, Brahim El Boudani
, Christos Chrysoulas
, George Ubakanma
, Nikolaos Pitropakis

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

The usage of cloud systems is at an all-time high, and with more organizations reaching for Big Data the forensic implications must be analyzed. The Hadoop Distributed File System is widely used both as a cloud service and with organizations implementing it themselves. This paper analyzed the forensic viability of a RAM analysis method for Hadoop based investigations and compared it against targeted process data dumping through the Java heap information. The RAM analysis was done through string searching and the use of the RAM analysis tool Volatility. This work found that RAM analysis can be a valuable tool for discovering artefacts of deleted resources from a Hadoop cluster but was unable to discover further information such as the block to node mapping. The targeted process analysis managed to provide some partial information about deleted resources and produce important metadata on the current state of the file system.

Original language	English
Title of host publication	2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023
Publisher	IEEE
ISBN (Electronic)	9781665475983
ISBN (Print)	9781665475990
DOIs	https://doi.org/10.1109/DRCN57075.2023.10108330
Publication status	Published - 26 Apr 2023
Event	19th International Conference on the Design of Reliable Communication Networks 2023 - Vilanova i la Geltru, Spain Duration: 17 Apr 2023 → 20 Apr 2023

Conference

Conference	19th International Conference on the Design of Reliable Communication Networks 2023
Abbreviated title	DRCN 2023
Country/Territory	Spain
City	Vilanova i la Geltru
Period	17/04/23 → 20/04/23

Keywords

cloud systems
forensic analysis
Hadoop
HDFS
Java Heap Analysis
RAM Analysis

ASJC Scopus subject areas

Hardware and Architecture
Safety, Risk, Reliability and Quality
Computer Networks and Communications

Access to Document

10.1109/DRCN57075.2023.10108330

Cite this

@inproceedings{a76ed9ea68664b4a9af2c223588db6a6,

title = "Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System",

abstract = "The usage of cloud systems is at an all-time high, and with more organizations reaching for Big Data the forensic implications must be analyzed. The Hadoop Distributed File System is widely used both as a cloud service and with organizations implementing it themselves. This paper analyzed the forensic viability of a RAM analysis method for Hadoop based investigations and compared it against targeted process data dumping through the Java heap information. The RAM analysis was done through string searching and the use of the RAM analysis tool Volatility. This work found that RAM analysis can be a valuable tool for discovering artefacts of deleted resources from a Hadoop cluster but was unable to discover further information such as the block to node mapping. The targeted process analysis managed to provide some partial information about deleted resources and produce important metadata on the current state of the file system.",

keywords = "cloud systems, forensic analysis, Hadoop, HDFS, Java Heap Analysis, RAM Analysis",

author = "Stuart Laing and Robert Ludwiniak and Boudani, \{Brahim El\} and Christos Chrysoulas and George Ubakanma and Nikolaos Pitropakis",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 19th International Conference on the Design of Reliable Communication Networks 2023, DRCN 2023 ; Conference date: 17-04-2023 Through 20-04-2023",

year = "2023",

month = apr,

day = "26",

doi = "10.1109/DRCN57075.2023.10108330",

language = "English",

isbn = "9781665475990",

booktitle = "2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023",

publisher = "IEEE",

address = "United States",

}

Laing, S, Ludwiniak, R, Boudani, BE, Chrysoulas, C, Ubakanma, G & Pitropakis, N 2023, Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System. in 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023., 10108330, IEEE, 19th International Conference on the Design of Reliable Communication Networks 2023, Vilanova i la Geltru, Spain, 17/04/23. https://doi.org/10.1109/DRCN57075.2023.10108330

TY - GEN

T1 - Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System

AU - Laing, Stuart

AU - Ludwiniak, Robert

AU - Boudani, Brahim El

AU - Chrysoulas, Christos

AU - Ubakanma, George

AU - Pitropakis, Nikolaos

PY - 2023/4/26

Y1 - 2023/4/26

N2 - The usage of cloud systems is at an all-time high, and with more organizations reaching for Big Data the forensic implications must be analyzed. The Hadoop Distributed File System is widely used both as a cloud service and with organizations implementing it themselves. This paper analyzed the forensic viability of a RAM analysis method for Hadoop based investigations and compared it against targeted process data dumping through the Java heap information. The RAM analysis was done through string searching and the use of the RAM analysis tool Volatility. This work found that RAM analysis can be a valuable tool for discovering artefacts of deleted resources from a Hadoop cluster but was unable to discover further information such as the block to node mapping. The targeted process analysis managed to provide some partial information about deleted resources and produce important metadata on the current state of the file system.

AB - The usage of cloud systems is at an all-time high, and with more organizations reaching for Big Data the forensic implications must be analyzed. The Hadoop Distributed File System is widely used both as a cloud service and with organizations implementing it themselves. This paper analyzed the forensic viability of a RAM analysis method for Hadoop based investigations and compared it against targeted process data dumping through the Java heap information. The RAM analysis was done through string searching and the use of the RAM analysis tool Volatility. This work found that RAM analysis can be a valuable tool for discovering artefacts of deleted resources from a Hadoop cluster but was unable to discover further information such as the block to node mapping. The targeted process analysis managed to provide some partial information about deleted resources and produce important metadata on the current state of the file system.

KW - cloud systems

KW - forensic analysis

KW - Hadoop

KW - HDFS

KW - Java Heap Analysis

KW - RAM Analysis

UR - https://www.scopus.com/pages/publications/85159108670

U2 - 10.1109/DRCN57075.2023.10108330

DO - 10.1109/DRCN57075.2023.10108330

M3 - Conference contribution

AN - SCOPUS:85159108670

SN - 9781665475990

BT - 2023 19th International Conference on the Design of Reliable Communication Networks, DRCN 2023

PB - IEEE

T2 - 19th International Conference on the Design of Reliable Communication Networks 2023

Y2 - 17 April 2023 through 20 April 2023

ER -

Forensic Investigation Using RAM Analysis on the Hadoop Distributed File System

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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