NETWORK TRAFFIC BASED RANSOMWARE DETECTION
Journal: International Education and Research Journal (Vol.10, No. 3)Publication Date: 2024-03-15
Authors : Sivaguru R. Srinath R. Sathiya Rubha M. Yasmin Banu R. Sathish Kumar K.;
Page : 154-160
Keywords : Ransomware Detection; Cybersecurity; Wireshark; Tshark; Intrusion Prevention System;
Abstract
Introduces a novel framework designed to bolster cybersecurity defenses against ransomware attacks. This system integrates an advanced Intrusion Detection and Prevention System (IDPS) with cutting-edge machine learning algorithms to efficiently identify and neutralize ransomware threats in real-time. By analyzing network traffic and system behavior, the IPS identifies patterns and anomalies that signify a potential ransomware attack, leveraging a comprehensive database of known ransomware signatures and behavior profiles. Upon detecting a threat, the system not only alerts the network administrators but also takes preemptive actions to isolate the attack, preventing the ransomware from spreading and encrypting files. This proactive approach significantly reduces the risk of data loss and operational downtime, enhancing the overall security posture of organizations. The deployment of this IDPS represents a crucial advancement in the fight against ransomware, offering a dynamic and adaptive solution to a rapidly evolving cyber threat landscape.
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Last modified: 2024-06-05 22:11:08