A comprehensive literature review on ransomware detection using deep learning
The manifold rise in ransomware attacks noted highest in 2023 posing a serious trepidation for cyber professionals to be active watchdogs of the early detection techniques. Ransomware is a type of malware often used to encrypt the confidential user files and network and demanding a hefty ransome to...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-12-01
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| Series: | Cyber Security and Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772918424000444 |
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| Summary: | The manifold rise in ransomware attacks noted highest in 2023 posing a serious trepidation for cyber professionals to be active watchdogs of the early detection techniques. Ransomware is a type of malware often used to encrypt the confidential user files and network and demanding a hefty ransome to decrypt it. The emergence of modern day technologies like artificial intelligence making it unchallenging for the novice attackers to use service platform such as RaaS to conduct the ransomware attack and victimize gullible individuals and organisations often demanding ransom in millions and billions. There exists the need to mitigate strategies using frameworks to combat such threats like deep learning which uses neural network to process and learn new information and train models on preprocessed data. The paper delves into providing the literature review on ransomware detection using deep learning techniques. |
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| ISSN: | 2772-9184 |