Paper Key : IRJ************747
Author: Khandavalli Surya,N Prasad,Basina Ramya Sruthi,Devadasu Srujana,Kalepu Vinod
Date Published: 11 Jul 2024
Abstract
The duration of time that passes between a new cyber vulnerability and its use by cybercriminals has been getting smaller and smaller over time. Within hours after the exploit was released, attackers started scanning the internet looking for vulnerable hosts to deploy threats like cryptocurrency miners and ransomware on vulnerable systems. Thus, it becomes imperative for the cybersecurity strategy to detect threats and their capabilities as early as possible to maximize the success of prevention actions. The framework comprises three main parts: identification of cyber threats and their names; profiling the identified threat in terms of its intentions or goals by employing two machine learning layers to filter and classify tweets; and alarm generation based on the threats risk. The main contribution of our work is the approach to characterizing or profiling the identified threats in terms of their intentions or goals, providing additional context on the threat and avenues for mitigation.
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