Decentralized Malware Attacks Detection using Blockchain
This research introduces an approach to detect malware attacks using blockchain technology that integrates signature-based and behavioralbased methods. The proposed system uses a decentralized blockchain network to share and store malware signatures and behavioral patterns. This enables faster and m...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2023/03/itmconf_icdsia2023_03002.pdf |
| _version_ | 1797807642145456128 |
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| author | Sheela S. Shalini S. Harsha D. Chandrashekar V.T. Goyal Ayush |
| author_facet | Sheela S. Shalini S. Harsha D. Chandrashekar V.T. Goyal Ayush |
| author_sort | Sheela S. |
| collection | DOAJ |
| description | This research introduces an approach to detect malware attacks using blockchain technology that integrates signature-based and behavioralbased methods. The proposed system uses a decentralized blockchain network to share and store malware signatures and behavioral patterns. This enables faster and more efficient detection of new malware files. The signature-based method involves storing the signatures in the blockchain and the sharing of the signature of malware files among the user nodes of the p2p blockchain network, while the behavioral-based approach analyzes the behavior and actions of files in a separate virtualized environment to identify suspicious patterns. This system addresses the limitations of conventional signature-based methods, which can be evaded by polymorphic malware, and behavioral-based methods, which may generate false positives. The results of the evaluation indicate that the proposed system achieves high detection rates while maintaining low false positives. Overall, the proposed system offers an effective and efficient approach to malware detection by utilizing the strengths of both signature-based and behavioral-based methods and utilizing the security and transparency benefits of blockchain technology. |
| first_indexed | 2024-03-13T06:25:42Z |
| format | Article |
| id | doaj.art-5ab4d7665944440d82cb92287d73ef28 |
| institution | Directory Open Access Journal |
| issn | 2271-2097 |
| language | English |
| last_indexed | 2024-03-13T06:25:42Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj.art-5ab4d7665944440d82cb92287d73ef282023-06-09T09:24:03ZengEDP SciencesITM Web of Conferences2271-20972023-01-01530300210.1051/itmconf/20235303002itmconf_icdsia2023_03002Decentralized Malware Attacks Detection using BlockchainSheela S.0Shalini S.1Harsha D.2Chandrashekar V.T.3Goyal Ayush4Assistant Professor, Global Academy of Technology, Department of Computer Science and EngineeringAssociate Professor, Global Academy of Technology, Department of Computer Science and EngineeringGlobal Academy of Technology, Department of Computer Science and EngineeringGlobal Academy of Technology, Department of Computer Science and EngineeringGlobal Academy of Technology, Department of Computer Science and EngineeringThis research introduces an approach to detect malware attacks using blockchain technology that integrates signature-based and behavioralbased methods. The proposed system uses a decentralized blockchain network to share and store malware signatures and behavioral patterns. This enables faster and more efficient detection of new malware files. The signature-based method involves storing the signatures in the blockchain and the sharing of the signature of malware files among the user nodes of the p2p blockchain network, while the behavioral-based approach analyzes the behavior and actions of files in a separate virtualized environment to identify suspicious patterns. This system addresses the limitations of conventional signature-based methods, which can be evaded by polymorphic malware, and behavioral-based methods, which may generate false positives. The results of the evaluation indicate that the proposed system achieves high detection rates while maintaining low false positives. Overall, the proposed system offers an effective and efficient approach to malware detection by utilizing the strengths of both signature-based and behavioral-based methods and utilizing the security and transparency benefits of blockchain technology.https://www.itm-conferences.org/articles/itmconf/pdf/2023/03/itmconf_icdsia2023_03002.pdf |
| spellingShingle | Sheela S. Shalini S. Harsha D. Chandrashekar V.T. Goyal Ayush Decentralized Malware Attacks Detection using Blockchain ITM Web of Conferences |
| title | Decentralized Malware Attacks Detection using Blockchain |
| title_full | Decentralized Malware Attacks Detection using Blockchain |
| title_fullStr | Decentralized Malware Attacks Detection using Blockchain |
| title_full_unstemmed | Decentralized Malware Attacks Detection using Blockchain |
| title_short | Decentralized Malware Attacks Detection using Blockchain |
| title_sort | decentralized malware attacks detection using blockchain |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2023/03/itmconf_icdsia2023_03002.pdf |
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