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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| Format: | Article |
| Language: | English |
| Published: |
Indian Society for Education and Environment
2019
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| Online Access: | http://psasir.upm.edu.my/id/eprint/81447/ http://psasir.upm.edu.my/id/eprint/81447/1/NA%20and%20signature%20analysis%20for%20malwares%20detection%20and%20removal.pdf |
| _version_ | 1848859106431991808 |
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| author | Jawad, Ahmad Ridha Sharif, Khaironi Yatim Abdulsada, Ammar Khalel |
| author_facet | Jawad, Ahmad Ridha Sharif, Khaironi Yatim Abdulsada, Ammar Khalel |
| author_sort | Jawad, Ahmad Ridha |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T12:24:04Z |
| format | Article |
| id | upm-81447 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:24:04Z |
| publishDate | 2019 |
| publisher | Indian Society for Education and Environment |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| spellingShingle | Jawad, Ahmad Ridha Sharif, Khaironi Yatim Abdulsada, Ammar Khalel N/A and signature analysis for malwares detection and removal |
| title | 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_short | N/A and signature analysis for malwares detection and removal |
| title_sort | n/a and signature analysis for malwares detection and removal |
| url | http://psasir.upm.edu.my/id/eprint/81447/ http://psasir.upm.edu.my/id/eprint/81447/ http://psasir.upm.edu.my/id/eprint/81447/ http://psasir.upm.edu.my/id/eprint/81447/1/NA%20and%20signature%20analysis%20for%20malwares%20detection%20and%20removal.pdf |