Evolution of Ransomware Attacks: A Basic Review
DOI:
https://doi.org/10.32628/IJSRSET2512518Keywords:
Malware, Ransomware, Artificial Intelligence, Block chain, Cyber securityAbstract
Cybersecurity is emerging field now a days. Information Security is important issue in today’s world as everything is in online mode. Online information exchange leads to different types of cyber-attacks like malwares, ransomware, trojan horse etc. Ransomware is one of type of malwares. Ransomware is emerged in recent years as one of the significant cyber threats. It locks the file and data on victims’ machine and make it inaccessible. It denies individual user, corporate offices, government offices, Banks etc entities access to their files and computers. To safeguard data in various organizations, cyber security play’s vital role. Different cyber security techniques and Best Practices can help in maintaining safe cyber environment. Artificial Intelligence and Blockchain Technology together will be useful for safeguarding systems in future. This paper delves into Fundamental concept of ransomware attacks, detection techniques, challenges and future scope.
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References
2013 15th International Conference on Advanced Computing Technologies (ICACT) : New Boyanapalli, Rajampet, India, 21-22 September 2013. (2013). IEEE.
Alqahtani, A., & Sheldon, F. T. (2022). A Survey of Crypto Ransomware Attack Detection Methodologies: An Evolving Outlook. In Sensors (Vol. 22, Issue 5). MDPI. https://doi.org/10.3390/s22051837 DOI: https://doi.org/10.3390/s22051837
Barik, K., Misra, S., Konar, K., Fernandez-Sanz, L., & Koyuncu, M. (2022). Cybersecurity Deep: Approaches, Attacks Dataset, and Comparative Study. In Applied Artificial Intelligence (Vol. 36, Issue 1). Taylor and Francis Ltd. https://doi.org/10.1080/08839514.2022.2055399 DOI: https://doi.org/10.1080/08839514.2022.2055399
Beaman, C., Barkworth, A., Akande, T. D., Hakak, S., & Khan, M. K. (2021a). Ransomware: Recent advances, analysis, challenges and future research directions. Computers and Security, 111. https://doi.org/10.1016/j.cose.2021.102490
Beaman, C., Barkworth, A., Akande, T. D., Hakak, S., & Khan, M. K. (2021b). Ransomware: Recent advances, analysis, challenges and future research directions. Computers and Security, 111. https://doi.org/10.1016/j.cose.2021.102490 DOI: https://doi.org/10.1016/j.cose.2021.102490
Belal, M. M., & Sundaram, D. M. (2022). Comprehensive review on intelligent security defences in cloud: Taxonomy, security issues, ML/DL techniques, challenges and future trends. In Journal of King Saud University - Computer and Information Sciences (Vol. 34, Issue 10, pp. 9102–9131). King Saud bin Abdulaziz University. https://doi.org/10.1016/j.jksuci.2022.08.035 DOI: https://doi.org/10.1016/j.jksuci.2022.08.035
Benavides, E., Fuertes, W., Sanchez, S., & Sanchez, M. (2020). Classification of Phishing Attack Solutions by Employing Deep Learning Techniques: A Systematic Literature Review. Smart Innovation, Systems and Technologies, 152, 51–64. https://doi.org/10.1007/978-981-13-9155-2_5 DOI: https://doi.org/10.1007/978-981-13-9155-2_5
Bhalla, S., Kwan, P., Bedekar, M., Phalnikar, R., Sumedha, •, & Editors, S. (n.d.). Proceeding of International Conference on Computational Science and Applications Algorithms for Intelligent Systems Series Editors: Jagdish Chand Bansal • Kusum Deep • Atulya K. Nagar. http://www.springer.com/series/16171
BRĂNESCU, I., & SIMION, E. (2023). Mac-OS Ransomware Protection: Prevention and Detection Mechanisms. Romanian Cyber Security Journal, 5(1), 87–95. https://doi.org/10.54851/v5i1y202308 DOI: https://doi.org/10.54851/v5i1y202308
Das, R., & Patel, M. (n.d.). Cyber Security for Social Networking Sites: Issues, Challenges and Solutions. www.ijraset.com
Dutta, V., Choraś, M., Pawlicki, M., & Kozik, R. (2020). A deep learning ensemble for network anomaly and cyber-attack detection. Sensors (Switzerland), 20(16), 1–20. https://doi.org/10.3390/s20164583 DOI: https://doi.org/10.3390/s20164583
Ekta, & Bansal, U. (2021). A Review on Ransomware Attack. ICSCCC 2021 - International Conference on Secure Cyber Computing and Communications, 221–226. https://doi.org/10.1109/ICSCCC51823.2021.9478148 DOI: https://doi.org/10.1109/ICSCCC51823.2021.9478148
Fernando, D. W., Komninos, N., & Chen, T. (2020). A Study on the Evolution of Ransomware Detection Using Machine Learning and Deep Learning Techniques. In Internet of Things (Vol. 1, Issue 2, pp. 551–604). MDPI. https://doi.org/10.3390/iot1020030 DOI: https://doi.org/10.3390/iot1020030
Ferrag, M. A., Maglaras, L., Moschoyiannis, S., & Janicke, H. (n.d.). Deep Learning for Cyber Security Intrusion Detection: Approaches, Datasets, and Comparative Study.
Ferrag, M. A., Maglaras, L., Moschoyiannis, S., & Janicke, H. (2020). Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study. Journal of Information Security and Applications, 50. https://doi.org/10.1016/j.jisa.2019.102419 DOI: https://doi.org/10.1016/j.jisa.2019.102419
Hocosaj, A., Pendleton, C., & Stoddard, J. (2024). Detection of Stealthy Encryption in Ransomware Using AI-Driven Anomaly Detection Models. https://doi.org/10.21203/rs.3.rs-4955370/v1 DOI: https://doi.org/10.21203/rs.3.rs-4955370/v1
Kamil, S., Siti Norul, H. S. A., Firdaus, A., & Usman, O. L. (2022). The Rise of Ransomware: A Review of Attacks, Detection Techniques, and Future Challenges. 2022 International Conference on Business Analytics for Technology and Security, ICBATS 2022. https://doi.org/10.1109/ICBATS54253.2022.9759000 DOI: https://doi.org/10.1109/ICBATS54253.2022.9759000
Kaur, B., Dadkhah, S., Shoeleh, F., Neto, E. C. P., Xiong, P., Iqbal, S., Lamontagne, P., Ray, S., & Ghorbani, A. A. (2023). Internet of Things (IoT) security dataset evolution: Challenges and future directions. In Internet of Things (Netherlands) (Vol. 22). Elsevier B.V. https://doi.org/10.1016/j.iot.2023.100780 DOI: https://doi.org/10.1016/j.iot.2023.100780
Kowalczyk, H., Zieliński, P., & Nowak, A. (2024). Dissecting MacOS Ransomware: A Comparative Analysis and Mitigation Strategies. https://doi.org/10.21203/rs.3.rs-4385485/v1 DOI: https://doi.org/10.21203/rs.3.rs-4385485/v1
Li, Z., & Liao, Q. (2022). Preventive portfolio against data-selling ransomware—A game theory of encryption and deception. Computers and Security, 116. https://doi.org/10.1016/j.cose.2022.102644 DOI: https://doi.org/10.1016/j.cose.2022.102644
Tariq Banday, M. (2011). From the SelectedWorks of M. Tariq Banday Emerging Challenges of Cybercrimes to Cyber Security Emerging Challenges of Cyber Crimes to Cyber Security. 17. https://doi.org/10.13140/RG.2.1.1503.7524
Tushkanova, O., Levshun, D., Branitskiy, A., Fedorchenko, E., Novikova, E., & Kotenko, I. (2023). Detection of Cyberattacks and Anomalies in Cyber-Physical Systems: Approaches, Data Sources, Evaluation. Algorithms, 16(2). https://doi.org/10.3390/a16020085 DOI: https://doi.org/10.3390/a16020085
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