A Method for Neutralizing Entropy Measurement-Based Ransomware Detection Technologies Using Encoding Algorithms [PDF]
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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E2E-RDS: Efficient End-to-End Ransomware Detection System Based on Static-Based ML and Vision-Based DL Approaches [PDF]
Sensors, 2023 Nowadays, ransomware is considered one of the most critical cyber-malware categories. In recent years various malware detection and classification approaches have been proposed to analyze and explore malicious software precisely.
Iman Almomani +2 more
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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 ...
Amjad Alraizza, Abdulmohsen Algarni
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A Machine Learning-Based Ransomware Detection Method for Attackers’ Neutralization Techniques Using Format-Preserving Encryption [PDF]
SensorsRansomware, a type of malware that first appeared in 1989, encrypts user files and demands money for decryption, causing increasing global damage. To reduce the impact of ransomware, various file-based detection technologies are being developed; however,
Jaehyuk Lee +3 more
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Neutralization Method of Ransomware Detection Technology Using Format Preserving Encryption [PDF]
Sensors, 2023 Ransomware is one type of malware that involves restricting access to files by encrypting files stored on the victim’s system and demanding money in return for file recovery.
Jaehyuk Lee +3 more
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Ransomware detection using deep learning based unsupervised feature extraction and a cost sensitive Pareto Ensemble classifier [PDF]
Scientific Reports, 2022 Ransomware attacks pose a serious threat to Internet resources due to their far-reaching effects. It’s Zero-day variants are even more hazardous, as less is known about them. In this regard, when used for ransomware attack detection, conventional machine
Umme Zahoora +5 more
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An intelligent ransomware based cyberthreat detection model using multi head attention-based recurrent neural networks with optimization algorithm in IoT environment [PDF]
Scientific ReportsThe rapid growth of the Internet of Things (IoT) and its extensive use in many regions, such as smart homes, healthcare, and vehicles, have made IoT security increasingly critical.
Sarah A. Alzakari +7 more
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Enhancing ransomware defense: deep learning-based detection and family-wise classification of evolving threats [PDF]
PeerJ Computer ScienceRansomware is a type of malware that locks access to or encrypts its victim’s files for a ransom to be paid to get back locked or encrypted data. With the invention of obfuscation techniques, it became difficult to detect its new variants.
Amjad Hussain +4 more
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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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Applied Sciences, 2021 Ransomware is an ill-famed malware that has received recognition because of its lethal and irrevocable effects on its victims. The irreparable loss caused due to ransomware requires the timely detection of these attacks. Several studies including surveys
Umara Urooj +4 more
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