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Advancements in Ransomware Detection and Prevention Techniques

Advancements in Ransomware Detection and Prevention Techniques
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Author(s): Jayant Verma (VIT Bhopal University, India)and D. Lakshmi (VIT Bhopal University, India)
Copyright: 2024
Pages: 32
Source title: Risks and Challenges of AI-Driven Finance: Bias, Ethics, and Security
Source Author(s)/Editor(s): Siraj Kariyilaparambu Kunjumuhammed (Modern College of Business and Science, Oman), Hisham Madi (Modern College of Business and Science, Oman)and Mahmoud Abouraia (Modern College of Business and Science, Oman)
DOI: 10.4018/979-8-3693-2185-0.ch009

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Abstract

In today's world of ubiquitous sensors and intelligent devices, cyber incidents and crime have peaked. Ransomware poses a danger to the security of a computer system. Ransomware attacks have significantly increased over the past ten years. Inevitably, this has become the talk of the town quite extortionate due to considerable consequential damages and obstruction in sectors such as healthcare, insurance, business, and education. Automatic detection and prevention of ransomware attacks is a crucial aspect of cybersecurity. Various malware detection methods have still been unturned as new parts of malware emerge. In the last two decades, several machine-learning algorithms and behavior-based techniques have been developed to identify ransomware anomalies. This chapter provides a long-term understanding of ransomware and discusses current methods and advancements in ransomware detection and the phases of a ransomware attack. The authors also highlighted the brief history of ransomware from 1989 when the first ransomware was discovered to the recent year 2023.

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