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@article{194881,
        author = {Mr. B. Surya Narayana Reddy and G. Mamatha and P. Sindhu and B. Swathi and D. Manikanta},
        title = {Malware Signature Generation Framework for Threat Intelligence},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6471-6473},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194881},
        abstract = {Malware attacks have been increasing over time, making it difficult for traditional detection systems to handle new and unknown threats. Most existing methods depend on already available signatures, which may not work when malware is slightly modified. In this paper, a simple malware signature generation framework is presented to support threat intelligence. The system focuses on analyzing files, extracting useful patterns, and organizing them into structured signatures. These signatures can later be used by detection systems to identify similar malicious behavior. The approach was tested using sample files to observe how patterns differ between suspicious and normal files. The results show that the system is able to generate meaningful signatures that can help in understanding and detecting potential threats. This work mainly focuses on the basic idea of signature generation and can be extended further in future.},
        keywords = {Malware detection, signature generation, threat intelligence, cybersecurity, pattern extraction},
        month = {March},
        }