A Comprehensive Framework for Early Detection and Mitigation of Ransomware in Enterprise Networks Sai Charan Madugula University of Central Missouri

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Sai Charan Madugula

Abstract

Ransomware has evolved as one of the most widespread and devastating cybersecurity threats to organisational networks. It frequently results in serious disruptions to business operations, the loss of data, and financial harm. When it comes to the continually developing strategies employed by ransomware perpetrators, traditional security techniques that are based on signatures and use reactive protection measures are usually insufficient. The purpose of this study is to present a complete architecture for the early identification and mitigation of ransomware attacks in business contexts. Real-time behavioural monitoring, anomaly detection based on machine learning, and deception technologies are all incorporated into the system in order to uncover early signs of penetration. In addition to this, it utilises a multi-layered response strategy, which includes automatic isolation, backup verification, and threat intelligence exchange, in order to limit ransomware and reduce its damage. Using modern ransomware samples, a prototype of the proposed system was tested on a simulated business network. The results showed that the system had a high detection accuracy and a low false positive rate. The findings provide further evidence that proactive and adaptive defence mechanisms are more effective than traditional reactive methods. Through the establishment of a solid basis for business cybersecurity architecture, this framework intends to strengthen the organization's resistance against potential ransomware attacks in the future.

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Sai Charan Madugula. (2023). A Comprehensive Framework for Early Detection and Mitigation of Ransomware in Enterprise Networks Sai Charan Madugula University of Central Missouri. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9), 3487–3493. Retrieved from https://ijritcc.org/index.php/ijritcc/article/view/9560
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