Implementation of Portable Antivirus System using Signature-based Detection and Heuristic Analysis

Chavan, Akshay; Kerakalamatti, Keerti; Srivastva, Snigdha

doi:10.1109/icoei51242.2021.9452909

Cited by 2 publications

(3 citation statements)

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“…They also explained the advantages and disadvantages of each when making this classification. Anti-virus applications installed on computer systems usually use a Signature-based detection technique and form the basis of security software [11]. Rohith et al shared how an anti-virus program detects a suspicious file, how to prevent the proliferation of malware on computer systems, and methods for detecting the identity of suspicious files [30].…”

Section: Related Workmentioning

confidence: 99%

“…It is necessary to install a separate anti-virus application on each computer, and also, anti-virus applications have periodic needs, such as updating and license renewal. Akshay Chavan and his colleagues have designed an anti-virus that can be found on any portable device and scan the computer system for signature-based and heuristic analysis when connected [11]. Considering that a portable anti-virus program uses a static database and thousands of brand-new viruses are developed customary, it includes the various risks.…”

Section: Related Workmentioning

confidence: 99%

“…The Figure 1 depicts the process's flow. On Github, malicious files and Python script are shared 11 .…”

Section: Control Applicationmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of Malicious Files Gathering via Honeypot Trap System and Benchmark of Anti-Virus Software

BASER,

GUVEN,

AYDIN

2023

Preprint

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In an era dominated by the pervasive integration of digital technologies, the surge in cyber threats is increasingly conspicuous. Cyber attackers employ malicious software (Malware) to compromise data integrity and exploit system resources. Tactics include transforming devices into remotely controlled assets or extorting ransom through data encryption. While end users commonly resort to antivirus software with signature-based detection, the protracted and dangered of malware detection necessitates alternative approaches. This study addresses this need by utilizing a honeypot trap system on Google Cloud to analyze suspicious files uploaded by attackers. Evaluated through a signature-based method, these files using 64 antivirus programs underscore the inadequacy of relying solely on this approach, with only three exhibiting success rates exceeding 90%. The majority, 61 antivirus programs, showed success rates predominantly below 70%. This underscores a crucial conclusion: sole reliance on signature-based security falls short in combating contemporary cyber threats. The study advocates for diverse detection techniques, independent or concurrent with signature-based methods, to fortify cybersecurity. The repository containing the honeypot-collected malicious files and Python script is publicly available on Github, serving as a valuable research resource.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%