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Ransomware Detection Using Machine Learning: A Survey
Big Data and Cognitive Computing, 2023 Ransomware attacks pose significant security threats to personal and corporate data and information. The owners of computer-based resources suffer from verification and privacy violations, monetary losses, and reputational damage due to successful ...
Abdulmohsen Algarni, Amjad Alraizza
exaly +4 more sources
KRDroid: Ransomware-Oriented Detector for Mobile Devices Based on Behaviors
Applied Sciences, 2021 Ransomware has become a serious threat on Android and new cases of ransomware are continuously growing. Most existing ransomware detectors use sensitive text or APIs to detect ransomware.
Senmiao Wang +6 more
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Ransomware on Cyber-Physical Systems: Taxonomies, Case Studies, Security Gaps, and Open Challenges
Internet of Things and Cyber-physical SystemsRansomware attacks have emerged as one of the most significant cyberthreats faced by organizations worldwide. In recent years, ransomware has also started to target critical infrastructure and Cyber-Physical Systems (CPS) such as industrial control ...
Mourad Benmalek
exaly +3 more sources
On the classification of Microsoft-Windows ransomware using hardware profile [PDF]
PeerJ Computer Science, 2021 Due to the expeditious inclination of online services usage, the incidents of ransomware proliferation being reported are on the rise. Ransomware is a more hazardous threat than other malware as the victim of ransomware cannot regain access to the ...
Sana Aurangzeb +4 more
doaj +2 more sources
The Effect of the Ransomware Dataset Age on the Detection Accuracy of Machine Learning Models
Information, 2023 Several supervised machine learning models have been proposed and used to detect Android ransomware. These models were trained using different datasets from different sources.
Qussai M. Yaseen
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Detection of Ransomware Attacks Using Processor and Disk Usage Data
IEEE Access, 2023 Ransomware often evades antivirus tools, encrypts files, and renders the target computer and its data unusable. The current approaches to detect such ransomware include monitoring processes, system calls, and file activities on the target system and ...
Kumar Thummapudi +2 more
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Entropy, 2022 Ransomware consists of malicious codes that restrict users from accessing their own files while demanding a ransom payment. Since the advent of ransomware, new and variant ransomwares have caused critical damage around the world, thus prompting the study
Jaehyuk Lee, Kyungroul Lee
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A Multi-Tier Streaming Analytics Model of 0-Day Ransomware Detection Using Machine Learning
Applied Sciences, 2020 Desktop and portable platform-based information systems become the most tempting target of crypto and locker ransomware attacks during the last decades.
Hiba Zuhair, Ali Selamat, Ondrej Krejcar
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Analysis of Crypto-Ransomware Using Network Traffic
Journal of Information Security and Cybercrimes Research, 2022 Ransomware is a form of malware attack that makes use of encryption to make information inaccessible for the motive of gathering a specified amount of payment.
Otasowie Owolafe, Aderonke F. Thompson
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Ransomware Early Detection Method Based on Deep Learning [PDF]
Jisuanji kexue, 2023 In recent years,ransomware is becoming increasingly prevalent,causing serious economic losses.Since files encrypted by ransomware are difficult to recover,how to timely and accurately detect ransomware is a hot point nowadays.To improve the timeliness ...
LIU Wenjing, GUO Chun, SHEN Guowei, XIE Bo, LYU Xiaodan
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