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The Evolution of Volatile Memory Forensics

Journal Article · · Journal of Cybersecurity and Privacy
DOI:https://doi.org/10.3390/jcp2030028· OSTI ID:1876935

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1876935
Alternate ID(s):
OSTI ID: 1884642
OSTI ID: 1885656
Journal Information:
Journal of Cybersecurity and Privacy, Journal Name: Journal of Cybersecurity and Privacy Journal Issue: 3 Vol. 2; ISSN 2624-800X
Publisher:
MDPI AGCopyright Statement
Country of Publication:
Country unknown/Code not available
Language:
English

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