Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods
This paper proposes a novel malware detection methodology that leverages unreliable Indicators of Compromise to enhance the identification of latent malware. The core contribution lies in introducing a sequence-based detection method that contextualizes unreliable IoCs to improve accuracy and reduce...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Croatian Communications and Information Society (CCIS)
2024-12-01
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| Series: | Journal of Communications Software and Systems |
| Subjects: | |
| Online Access: | https://jcoms.fesb.unist.hr/10.24138/jcomss-2024-0098/ |
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| _version_ | 1841550076310192128 |
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| author | Pavel Novak Vaclav Oujezsky |
| author_facet | Pavel Novak Vaclav Oujezsky |
| author_sort | Pavel Novak |
| collection | DOAJ |
| description | This paper proposes a novel malware detection methodology that leverages unreliable Indicators of Compromise to enhance the identification of latent malware. The core contribution lies in introducing a sequence-based detection method that contextualizes unreliable IoCs to improve accuracy and reduce false positives. Unlike traditional methods reliant on predefined signatures or behavior analysis, this approach dynamically assesses system behaviors, focusing on suspicious actions and interaction patterns. Key contributions include a novel combination of unreliable IoCs with sequence alignment methods, an extensive mapping study of detection techniques, and initial experiments on a dataset of over 19,000 malware samples. Results demonstrate the method’s ability to cluster and identify malware families based on their behavioral signatures, even in its early developmental stage. This innovative approach shows promise for detecting previously unknown threats, establishing a foundation for advanced research in malware detection. |
| format | Article |
| id | doaj-art-e52a2c6f0c0b4522a78fe320d6f50f22 |
| institution | Kabale University |
| issn | 1845-6421 1846-6079 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Croatian Communications and Information Society (CCIS) |
| record_format | Article |
| series | Journal of Communications Software and Systems |
| spelling | doaj-art-e52a2c6f0c0b4522a78fe320d6f50f222025-01-10T09:36:31ZengCroatian Communications and Information Society (CCIS)Journal of Communications Software and Systems1845-64211846-60792024-12-0120431732810.24138/jcomss-2024-0098Transforming Weakness into Strength: Improving Unreliable Malware Detection MethodsPavel NovakVaclav OujezskyThis paper proposes a novel malware detection methodology that leverages unreliable Indicators of Compromise to enhance the identification of latent malware. The core contribution lies in introducing a sequence-based detection method that contextualizes unreliable IoCs to improve accuracy and reduce false positives. Unlike traditional methods reliant on predefined signatures or behavior analysis, this approach dynamically assesses system behaviors, focusing on suspicious actions and interaction patterns. Key contributions include a novel combination of unreliable IoCs with sequence alignment methods, an extensive mapping study of detection techniques, and initial experiments on a dataset of over 19,000 malware samples. Results demonstrate the method’s ability to cluster and identify malware families based on their behavioral signatures, even in its early developmental stage. This innovative approach shows promise for detecting previously unknown threats, establishing a foundation for advanced research in malware detection.https://jcoms.fesb.unist.hr/10.24138/jcomss-2024-0098/behavioral analysiscybersecuritymalware detectionsequence similarity |
| spellingShingle | Pavel Novak Vaclav Oujezsky Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods Journal of Communications Software and Systems behavioral analysis cybersecurity malware detection sequence similarity |
| title | Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods |
| title_full | Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods |
| title_fullStr | Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods |
| title_full_unstemmed | Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods |
| title_short | Transforming Weakness into Strength: Improving Unreliable Malware Detection Methods |
| title_sort | transforming weakness into strength improving unreliable malware detection methods |
| topic | behavioral analysis cybersecurity malware detection sequence similarity |
| url | https://jcoms.fesb.unist.hr/10.24138/jcomss-2024-0098/ |
| work_keys_str_mv | AT pavelnovak transformingweaknessintostrengthimprovingunreliablemalwaredetectionmethods AT vaclavoujezsky transformingweaknessintostrengthimprovingunreliablemalwaredetectionmethods |