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@article{191663,
        author = {SUNIL KUMAR and ZAHRA JABEEN and KHUSHBOO MISHRA and Binay Kumar Mishra},
        title = {Enhancing Ransomware Defence: Models and Techniques},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {7514-7516},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191663},
        abstract = {Ransomware has emerged as one of the most significant cybersecurity threats, affecting individuals, enterprises, and critical infrastructure worldwide. Modern ransomware attacks have evolved from simple file encryption malware into complex, multi-stage campaigns involving stealthy infiltration, lateral movement, data exfiltration, and double or triple extortion. This research article explores contemporary ransomware defence mechanisms by analysing detection models, prevention techniques, mitigation strategies, and recovery frameworks. Emphasis is placed on machine-learning-based detection, behaviour-based analysis, zero-trust architectures, and hybrid defence models. The paper highlights current challenges and proposes future research directions for enhancing ransomware resilience.},
        keywords = {Ransomware, Cybersecurity, Intrusion Detection, Machine Learning, Behavioural Analysis, Zero Trust},
        month = {January},
        }