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N/A and signature analysis for malwares detection and removal

Objectives: This study aimed to design an application that effectively scans, detects, and removes malware based on their signatures and behaviours. Methods/Statistical analysis: The rapid growth in the number and types of malware poses high security risks despite the numerous antivirus softwares wi...

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Main Authors: Jawad, Ahmad Ridha, Sharif, Khaironi Yatim, Abdulsada, Ammar Khalel
Format: Article
Language:English
Published: Indian Society for Education and Environment 2019
Online Access:http://psasir.upm.edu.my/id/eprint/81447/1/NA%20and%20signature%20analysis%20for%20malwares%20detection%20and%20removal.pdf
http://psasir.upm.edu.my/id/eprint/81447/
https://www.researchgate.net/publication/335649376_NA_and_Signature_Analysis_for_Malwares_Detection_and_Removal
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spelling my.upm.eprints.814472021-01-31T16:03:13Z http://psasir.upm.edu.my/id/eprint/81447/ N/A and signature analysis for malwares detection and removal Jawad, Ahmad Ridha Sharif, Khaironi Yatim Abdulsada, Ammar Khalel Objectives: This study aimed to design an application that effectively scans, detects, and removes malware based on their signatures and behaviours. Methods/Statistical analysis: The rapid growth in the number and types of malware poses high security risks despite the numerous antivirus softwares with Signature-Based Detection (SBD) method. The SBD method depends on the signatures or malware names that are available in the algorithm database. Findings: Malware is a type of malicious software that poses security threats to the targeted system, resulting in information loss, resource abuse, or system damage. The antivirus software is one of the most commonly used security tools to detect and remove malware. However, the malware defences should focus on the malware signatures since there is no universal way of recognising all malware. Therefore, this study suggested N/A detection technique as the dynamic method (behaviour-based detection method) that depends on the Windows Registry (system database). Both static and dynamic detection methods were assessed in this study. Based on the experimental outcomes, SBD method detected and removed most of malware (only known viruses). Application/Improvements: Meanwhile, the N/A detection method detected and removed all injected malware (known and unknown Trojan horse) within a relatively low running time. Indian Society for Education and Environment 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81447/1/NA%20and%20signature%20analysis%20for%20malwares%20detection%20and%20removal.pdf Jawad, Ahmad Ridha and Sharif, Khaironi Yatim and Abdulsada, Ammar Khalel (2019) N/A and signature analysis for malwares detection and removal. Indian Journal of Science & Technology, 12 (25). pp. 1-7. ISSN 0974-6846; ESSN: 0974-5645 https://www.researchgate.net/publication/335649376_NA_and_Signature_Analysis_for_Malwares_Detection_and_Removal 10.17485/ijst/2019/v12i25/146005
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Objectives: This study aimed to design an application that effectively scans, detects, and removes malware based on their signatures and behaviours. Methods/Statistical analysis: The rapid growth in the number and types of malware poses high security risks despite the numerous antivirus softwares with Signature-Based Detection (SBD) method. The SBD method depends on the signatures or malware names that are available in the algorithm database. Findings: Malware is a type of malicious software that poses security threats to the targeted system, resulting in information loss, resource abuse, or system damage. The antivirus software is one of the most commonly used security tools to detect and remove malware. However, the malware defences should focus on the malware signatures since there is no universal way of recognising all malware. Therefore, this study suggested N/A detection technique as the dynamic method (behaviour-based detection method) that depends on the Windows Registry (system database). Both static and dynamic detection methods were assessed in this study. Based on the experimental outcomes, SBD method detected and removed most of malware (only known viruses). Application/Improvements: Meanwhile, the N/A detection method detected and removed all injected malware (known and unknown Trojan horse) within a relatively low running time.
format Article
author Jawad, Ahmad Ridha
Sharif, Khaironi Yatim
Abdulsada, Ammar Khalel
spellingShingle Jawad, Ahmad Ridha
Sharif, Khaironi Yatim
Abdulsada, Ammar Khalel
N/A and signature analysis for malwares detection and removal
author_facet Jawad, Ahmad Ridha
Sharif, Khaironi Yatim
Abdulsada, Ammar Khalel
author_sort Jawad, Ahmad Ridha
title N/A and signature analysis for malwares detection and removal
title_short N/A and signature analysis for malwares detection and removal
title_full N/A and signature analysis for malwares detection and removal
title_fullStr N/A and signature analysis for malwares detection and removal
title_full_unstemmed N/A and signature analysis for malwares detection and removal
title_sort n/a and signature analysis for malwares detection and removal
publisher Indian Society for Education and Environment
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/81447/1/NA%20and%20signature%20analysis%20for%20malwares%20detection%20and%20removal.pdf
http://psasir.upm.edu.my/id/eprint/81447/
https://www.researchgate.net/publication/335649376_NA_and_Signature_Analysis_for_Malwares_Detection_and_Removal
_version_ 1691734455900700672
score 13.239859

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