Ransomware Mitigation in the Modern Era: A Comprehensive Review, Research Challenges, and Future Directions

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Ransomware Detection Considering User's Document Editing

Honda, T., Mukaiyama, K., Shirai, T., Ohki, T., & Nishigaki, M. (2018) · International Conference on Advanced Information Networking and Applications (AINA) · doi:10.1109/aina.2018.00133 · Cited by 17 · see citing works

An app based on static analysis for android ransomware

Kanwal, M., & Thakur, S. (2017) · International Conference on Computing, Communication and Automation · doi:10.1109/ccaa.2017.8229907 · Cited by 16 · see citing works

A Secure Container-based Backup Mechanism to Survive Destructive Ransomware Attacks

Jin, Y., Tomoishi, M., Matsuura, S., & Kitaguchi, Y. (2018) · 2012 International Conference on Computing, Networking and Communications (ICNC) · doi:10.1109/iccnc.2018.8390376 · Cited by 15 · see citing works

A Novel Structural-Entropy-based Classification Technique for Supporting Android Ransomware Detection and Analysis

Cuzzocrea, A., Martinelli, F., & Mercaldo, F. (2018) · Proceedings of ... IEEE International Conference on Fuzzy Systems · doi:10.1109/fuzz-ieee.2018.8491637 · Cited by 15 · see citing works

Dynamic Distributed Secure Storage Against Ransomware

Castiglione, J., & Pavlović, D. (2019) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2019.2924650 · Cited by 15 · see citing works

Analysing Indicator of Compromises for Ransomware: Leveraging IOCs with Machine Learning Techniques

Verma, M., Kumarguru, P., Deb, S. B., & Gupta, A. (2018) · IEEE International Conference on Intelligence and Security Informatics (ISI) · doi:10.1109/isi.2018.8587409 · Cited by 14 · see citing works

MimosaFTL

Wang, P., Jia, S., Chen, B., Xia, L., & Liu, P. (2019) · ACM Conference on Data and Application Security and Privacy (CODASPY) · doi:10.1145/3292006.3300041 · Cited by 14 · see citing works

An Empirical Study of Key Generation in Cryptographic Ransomware

Bajpai, P., & Enbody, R. J. (2020) · International Conference on Cyber Security and Protection of Digital Services (Cyber Security) · doi:10.1109/cybersecurity49315.2020.9138878 · Cited by 13 · see citing works

A Behaviour based Ransomware Detection using Neural Network Models

Ketzaki, E., Toupas, P., Giannoutakis, K. M., Drosou, A., & Tzovaras, D. K. (2020) · International Conference on Advanced Computer Information Technologies (ACIT) · doi:10.1109/acit49673.2020.9208974 · Cited by 9 · see citing works

Prevention of Ransomware Execution in Enterprise Environment on Windows OS: Assessment of Application Whitelisting Solutions

Turaev, H., Zavarsky, P., & Swar, B. (2018) · International Conference on Data Intelligence and Security (ICDIS) · doi:10.1109/icdis.2018.00024 · Cited by 8 · see citing works

Hardware based protection against malwares by PUF based access control mechanism

Siddiqui, A. S., Lee, C.-C., & Saqib, F. (2017) · Conference proceedings · doi:10.1109/mwscas.2017.8053172 · Cited by 6 · see citing works

Interactive Security of Ransomware with Heuristic Random Bit Generator

Rastogi, R. P., Agarwal, G., & Shukla, R. K. (2020) · Lecture notes in electrical engineering · doi:10.1007/978-981-15-7961-5_90 · Cited by 4 · see citing works

Ransomware Detection Using Machine Learning: A Survey

Alraizza, A., & Algarni, A. (2023) · Big Data and Cognitive Computing · doi:10.3390/bdcc7030143 · Cited by 113 · see citing works

Privacy Preservation of Electronic Health Records in the Modern Era: A Systematic Survey

Nowrozy, R., Ahmed, K. E. U., Kayes, A. S. M., Wang, H., & McIntosh, T. R. (2024) · ACM Computing Surveys · doi:10.1145/3653297 · Cited by 117 · see citing works

Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence

McIntosh, T. R., Susnjak, T., Arachchilage, N., Liu, T., Xu, D., Watters, P., & Halgamuge, M. N. (2026) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2025.3569516 · Cited by 104 · see citing works

From Google Gemini to OpenAI Q* (Q-Star): A Survey on Reshaping the Generative Artificial Intelligence (AI) Research Landscape

McIntosh, T. R., Susnjak, T., Liu, T., Watters, P., Xu, D., Liu, D., & Halgamuge, M. N. (2025) · Technologies · doi:10.3390/technologies13020051 · Cited by 102 · see citing works

Machine Learning in Precision Agriculture: A Survey on Trends, Applications and Evaluations Over Two Decades

Condran, S., Bewong, M., Islam, M. Z., Maphosa, L., & Zheng, L. (2022) · IEEE Access · doi:10.1109/access.2022.3188649 · Cited by 99 · see citing works

A review of state-of-the-art malware attack trends and defense mechanisms

Ferdous, J., Islam, R., Mahboubi, A., & Islam, M. Z. (2023) · IEEE Access · doi:10.1109/access.2023.3328351 · Cited by 98 · see citing works

Ransomware early detection: A survey

Cen, M., Jiang, F., Qin, X., Jiang, Q., & Doss, R. (2023) · Computer Networks · doi:10.1016/j.comnet.2023.110138 · Cited by 89 · see citing works

Harnessing GPT-4 for generation of cybersecurity GRC policies: A focus on ransomware attack mitigation

McIntosh, T. R., Liu, T., Sušnjak, T., Alavizadeh, H., Ng, A., Nowrozy, R., & Watters, P. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103424 · Cited by 84 · see citing works

A Survey on Semantic Communication Networks: Architecture, Security, and Privacy

Guo, S., Wang, Y., Zhang, N., Su, Z., Luan, T. H., Tian, Z., & Shen, X. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3516819 · Cited by 92 · see citing works

Ransomware Detection Using Machine Learning: A Review, Research Limitations and Future Directions

Ispahany, J., Islam, R., Islam, M. Z., & Khan, M. A. (2024) · IEEE Access · doi:10.1109/access.2024.3397921 · Cited by 77 · see citing works

Crypto-ransomware detection using machine learning models in file-sharing network scenarios with encrypted traffic

Berrueta, E., Morató, D., Magaña, E., & Izal, M. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.118299 · Cited by 63 · see citing works

AI-Based Ransomware Detection: A Comprehensive Review

Ferdous, J., Islam, R., Mahboubi, A., & Islam, M. Z. (2024) · IEEE Access · doi:10.1109/access.2024.3461965 · Cited by 57 · see citing works

Ransomware Reloaded: Re-examining Its Trend, Research and Mitigation in the Era of Data Exfiltration

McIntosh, T. R., Sušnjak, T., Liu, T., Xu, D., Watters, P., Liu, D., Hao, Y., Ng, A., & Halgamuge, M. N. (2024) · ACM Computing Surveys · doi:10.1145/3691340 · Cited by 55 · see citing works

Securing the Industrial Internet of Things against ransomware attacks: A comprehensive analysis of the emerging threat landscape and detection mechanisms

Al-Hawawreh, M. S., Alazab, M., Ferrag, M. A., & Hossain, M. S. (2023) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2023.103809 · Cited by 53 · see citing works

Zero-Ran Sniff: A zero-day ransomware early detection method based on zero-shot learning

Cen, M., Deng, X., Jiang, F., & Doss, R. (2024) · Computers & Security · doi:10.1016/j.cose.2024.103849 · Cited by 48 · see citing works

A framework for cyber-risk insurance against ransomware: A mixed-method approach

Mukhopadhyay, A., & Jain, S. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102724 · Cited by 38 · see citing works

A Game-Theoretic Approach to Containing Artificial General Intelligence: Insights From Highly Autonomous Aggressive Malware

McIntosh, T. R., Sušnjak, T., Liu, T., Watters, P., Ng, A., & Halgamuge, M. N. (2024) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3394392 · Cited by 38 · see citing works

Machine Learning Algorithms and Frameworks in Ransomware Detection

Smith, D., Khorsandroo, S., & Roy, K. (2022) · IEEE Access · doi:10.1109/access.2022.3218779 · Cited by 35 · see citing works

Applying staged event-driven access control to combat ransomware

McIntosh, T. R., Kayes, A. S. M., Chen, Y. P., Ng, A., & Watters, P. (2023) · Computers & Security · doi:10.1016/j.cose.2023.103160 · Cited by 35 · see citing works

RanSMAP: Open dataset of Ransomware Storage and Memory Access Patterns for creating deep learning based ransomware detectors

Hirano, M., & Kobayashi, R. (2024) · Computers & Security · doi:10.1016/j.cose.2024.104202 · Cited by 34 · see citing works

SwiftR: Cross-platform ransomware fingerprinting using hierarchical neural networks on hybrid features

Karbab, E. B., Debbabi, M., & Derhab, A. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.120017 · Cited by 33 · see citing works

Safeguarding digital livestock farming - a comprehensive cybersecurity roadmap for dairy and poultry industries

Neethirajan, S. R. (2025) · Frontiers in Big Data · doi:10.3389/fdata.2025.1556157 · Cited by 32 · see citing works

A comprehensive literature review on ransomware detection using deep learning

Kritika, E. (2024) · Cyber Security and Applications · doi:10.1016/j.csa.2024.100078 · Cited by 31 · see citing works

Evaluating Large Language Models in Ransomware Negotiation: A Comparative Analysis of ChatGPT and ClaudePreprint

Kumamoto, T., Yoshida, Y., & Fujima, H. (2023) · Research Square · doi:10.21203/rs.3.rs-3719038/v1 · Cited by 28 · see citing works

A Survey on Ransomware Threats: Contrasting Static and Dynamic Analysis MethodsPreprint

Kang, Q., & Gu, Y. (2023) · Preprints.org · doi:10.20944/preprints202311.0798.v1 · Cited by 25 · see citing works

RansoGuard: A RNN-based framework leveraging pre-attack sensitive APIs for early ransomware detection

Cen, M., Jiang, F., & Doss, R. (2024) · Computers & Security · doi:10.1016/j.cose.2024.104293 · Cited by 24 · see citing works

Zero Trust VPN (ZT-VPN): A Systematic Literature Review and Cybersecurity Framework for Hybrid and Remote Work

Zohaib, S. M., Sajjad, S. M., Iqbal, Z., Yousaf, M., Haseeb, M., & Muhammad, Z. (2024) · Information · doi:10.3390/info15110734 · Cited by 23 · see citing works

Ransomware Detection on Linux Using Machine Learning with Random Forest AlgorithmPreprint

Wu, Y.-C., & Chang, Y.-L. (2024) · doi:10.36227/techrxiv.171778770.06550236/v1 · Cited by 23 · see citing works

The Evolution of Ransomware: Tactics, Techniques, and Mitigation Strategies

Nagar, G. (2024) · International Journal of Scientific Research and Management (IJSRM) · doi:10.18535/ijsrm/v12i06.ec09 · Cited by 22 · see citing works

Efficient Ransomware Detection via Portable Executable File Image Analysis By LLaMA-7bPreprint

Li, X., Zhu, T., & Zhang, W. (2023) · Research Square · doi:10.21203/rs.3.rs-3679775/v1 · Cited by 22 · see citing works

Trends and Future Directions in Automated Ransomware Detection

Jegede, A., Fadele, A., Onoja, M., Aimufua, G., & Mazadu, I. J. (2022) · Journal of Computing and Social Informatics · doi:10.33736/jcsi.4932.2022 · Cited by 21 · see citing works

Personality Types and Ransomware Victimisation

Yilmaz, Y., Çetin, O., Grigore, C., Arief, B., & Hernandez-Castro, J. C. (2022) · Digital Threats Research and Practice · doi:10.1145/3568994 · Cited by 20 · see citing works

Analyzing Data Theft Ransomware Traffic Patterns Using BERTPreprint

Almeida, G., & Vasconcelos, F. (2023) · Preprints.org · doi:10.20944/preprints202312.0158.v1 · Cited by 19 · see citing works

Early prediction of ransomware API calls behaviour based on GRU-TCN in healthcare IoT

Jeon, J., Baek, S., Jeong, B., & Jeong, Y. (2023) · Connection Science · doi:10.1080/09540091.2023.2233716 · Cited by 17 · see citing works

Enhancing Ransomware Detection: A Windows API Min Max Relevance Refinement ApproachPreprint

Kang, Q., & Gu, Y. (2023) · Preprints.org · doi:10.20944/preprints202311.1004.v1 · Cited by 17 · see citing works

Dynamic Behavioural Analysis of Privacy-Breaching and Data Theft RansomwarePreprint

Ozturk, M., Demir, A., Arslan, Z., & Caliskan, O. (2024) · Research Square · doi:10.21203/rs.3.rs-4097219/v1 · Cited by 17 · see citing works

Enhanced Ransomware Detection Using Dual-Layer Random Forest on Opcode SequencesPreprint

Moritaka, H., & Komuro, D. (2024) · doi:10.22541/au.172193050.02354794/v1 · Cited by 17 · see citing works

Ransomware Detection and Classification Using Generative Adversarial Networks with Dynamic Weight AdaptationPreprint

Gong, W., Zha, Y., & Tang, J. (2024) · doi:10.31219/osf.io/5vju7 · Cited by 16 · see citing works

Know Thy Ransomware Response: A Detailed Framework for Devising Effective Ransomware Response Strategies

Bajpai, P., & Enbody, R. J. (2023) · Digital Threats Research and Practice · doi:10.1145/3606022 · Cited by 15 · see citing works

Similarity Analysis of Ransomware Attacks Based on ATT&CK Matrix

Song, Z., Tian, Y., & Zhang, J. (2023) · IEEE Access · doi:10.1109/access.2023.3322427 · Cited by 15 · see citing works

Ransomware Detection with a 2-Tier Machine Learning Approach Using a Novel Clustering AlgorithmPreprint

Zhang, R., & Liu, Y. (2024) · Research Square · doi:10.21203/rs.3.rs-4567706/v1 · Cited by 15 · see citing works

Securing the internet of things: A comprehensive review of ransomware attacks, detection, countermeasures, and future prospects

Yan, P., & Khoei, T. T. (2025) · Franklin Open · doi:10.1016/j.fraope.2025.100256 · Cited by 14 · see citing works

RansomCillin: Leveraging NTFS Spare Space to Recover from Ransomware AttacksPreprint

Takeuchi, K., Fujima, H., Kumamoto, T., & Yoshida, Y. (2023) · doi:10.36227/techrxiv.24596754.v1 · Cited by 14 · see citing works

Applying ChatGPT-Powered Game Theory in Ransomware NegotiationsPreprint

Zhu, T., Li, X., & Zhang, W. (2023) · doi:10.36227/techrxiv.170244324.48846520/v1 · Cited by 14 · see citing works

Multimodal Deep Learning for Android Malware Classification

Arrowsmith, J., Sušnjak, T., & Jang‐Jaccard, J. (2025) · Machine Learning and Knowledge Extraction · doi:10.3390/make7010023 · Cited by 13 · see citing works

Applying Moving Target Defense Against Data Theft Ransomware on Windows OSPreprint

Liu, S., & Chen, X. (2023) · Preprints.org · doi:10.20944/preprints202312.0948.v1 · Cited by 13 · see citing works

Ransomware Detection with Machine Learning by Applying the Lapranove Function on BytecodePreprint

Zhong, T., & Li, J. (2024) · doi:10.31219/osf.io/zk3sw · Cited by 13 · see citing works

The Erosion of Cybersecurity Zero-Trust Principles Through Generative AI: A Survey on the Challenges and Future Directions

Xu, D., Gondal, I., Yi, X., Sušnjak, T., Watters, P., & McIntosh, T. R. (2025) · Journal of Cybersecurity and Privacy · doi:10.3390/jcp5040087 · Cited by 12 · see citing works

An Innovative Real-Time Recursive Framework for Techno-Economical Self-Healing in Large Power Microgrids Against Cyber–Physical Attacks Using Large Change Sensitivity Analysis

Jahromi, M. Z., Yaghoubi, E., Yaghoubi, E., Maghami, M. R., & Chamorro, H. R. (2025) · Energies · doi:10.3390/en18010190 · Cited by 12 · see citing works

Analyzing Reporting on Ransomware Incidents: A Case Study

Greubel, A., Andres, D., & Hennecke, M. (2023) · Social Sciences · doi:10.3390/socsci12050265 · Cited by 12 · see citing works

Federated Learning-Based Ransomware Detection via Indicators of CompromisePreprint

Koike, S., Tanaka, H., & Maeda, M. (2024) · Research Square · doi:10.21203/rs.3.rs-4585988/v1 · Cited by 12 · see citing works

Travelling the Hypervisor and SSD: A Tag-Based Approach Against Crypto Ransomware with Fine-Grained Data Recovery

Ma, B., Yang, Y., Li, J., Zhang, F., Shen, W., Zhou, Y., & Ma, J. (2023) · ACM SIGSAC Conference on Computer and Communications Security (CCS) · doi:10.1145/3576915.3616665 · Cited by 11 · see citing works

Ransomware and the Robin Hood effect?: Experimental evidence on Americans’ willingness to support cyber-extortion

Haner, M., Sloan, M. M., Graham, A., Pickett, J. T., & Cullen, F. T. (2022) · Journal of Experimental Criminology · doi:10.1007/s11292-022-09515-z · Cited by 11 · see citing works

Using ChatGPT to Analyze Ransomware Messages and to Predict Ransomware ThreatsPreprint

Fujima, H., Kumamoto, T., & Yoshida, Y. (2023) · Research Square · doi:10.21203/rs.3.rs-3645967/v1 · Cited by 11 · see citing works

LLaMa Assisted Reverse Engineering of Modern Ransomware: A Comparative Analysis with Early Crypto-RansomwarePreprint

Vasconcelos, F. E., & Almeida, G. (2023) · Research Square · doi:10.21203/rs.3.rs-3689581/v1 · Cited by 12 · see citing works

NTFS+: An Enhanced NTFS File System Against Ransomware InvasionsPreprint

Gu, Y., & Kang, Q. (2023) · Research Square · doi:10.21203/rs.3.rs-3742731/v1 · Cited by 11 · see citing works

How to punish cyber criminals: A study to investigate the target and consequence based punishments for malware attacks in UK, USA, China, Ethiopia & Pakistan

Khadam, N., Anjum, N., Alam, A., Mirza, Q. K. A., Assam, M., Ismail, E. A. A., & Abonazel, M. R. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e22823 · Cited by 10 · see citing works

Decentralized Identity Verification System for Data Access to Prevent Data Exfiltration RansomwarePreprint

Takeuchi, K., Kumamoto, T., Yoshida, Y., & Fujima, H. (2023) · doi:10.36227/techrxiv.24732729.v1 · Cited by 10 · see citing works

Enhancing Ransomware Classification with Multi-stage Feature Selection and Data Imbalance Correction

Onwuegbuche, F. C., Jurcut, A. D., & Pasquale, L. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-34671-2_20 · Cited by 9 · see citing works

Evaluation of live forensic techniques, towards Salsa20-Based cryptographic ransomware mitigation

Babiano, L. F. D. L., Macfarlane, R., & Davies, S. R. H. (2023) · Forensic Science International Digital Investigation · doi:10.1016/j.fsidi.2023.301572 · Cited by 9 · see citing works

GPT, ontology, and CAABAC: A tripartite personalized access control model anchored by compliance, context and attribute

Nowrozy, R., Ahmed, K. E. U., & Wang, H. (2025) · PLoS ONE · doi:10.1371/journal.pone.0310553 · Cited by 12 · see citing works

Entropy and Memory Forensics in Ransomware Analysis: Utilizing LLaMA-7B for Advanced Pattern RecognitionPreprint

Zhang, W., Li, X., & Zhu, T. (2023) · doi:10.36227/techrxiv.24742389.v1 · Cited by 9 · see citing works

How to Circumvent and Beat the Ransomware in Android Operating System—A Case Study of Locker.CB!tr

Drabent, K., Janowski, R., & Batalla, J. M. (2024) · Electronics · doi:10.3390/electronics13112212 · Cited by 8 · see citing works

A Threat-Led Approach to Mitigating Ransomware Attacks: Insights from a Comprehensive Analysis of the Ransomware Ecosystem

Lawall, A., & Beenken, P. (2024) · European Interdisciplinary Cybersecurity Conference (EICC) · doi:10.1145/3655693.3661321 · Cited by 8 · see citing works

A Few-Shot Learning Approach with a Twin Neural Network Utilizing Entropy Features for Ransomware ClassificationPreprint

Wang, F. (2023) · Preprints.org · doi:10.20944/preprints202311.1286.v1 · Cited by 8 · see citing works

Self-Healing Networks: Adaptive Responses to Ransomware AttacksPreprint

Almeida, G., & Vasconcelos, F. (2023) · Preprints.org · doi:10.20944/preprints202312.1538.v1 · Cited by 8 · see citing works

MLRan: A behavioural dataset for ransomware analysis and detection

Onwuegbuche, F. C., Olaoluwa, A., Jurcut, A. D., & Pasquale, L. (2026) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2026.104475 · Cited by 14 · see citing works

Dissecting MacOS Ransomware: A Comparative Analysis and Mitigation StrategiesPreprint

Kowalczyk, H., Zieliński, P., & Nowak, A. (2024) · Research Square · doi:10.21203/rs.3.rs-4385485/v1 · Cited by 7 · see citing works

Federated RNN-Based Detection of Ransomware Attacks: A Privacy-Preserving ApproachPreprint

Zhang, X., Wang, C., Liu, R., & Yang, S. (2024) · doi:10.31219/osf.io/szjkw · Cited by 7 · see citing works

Inside ransomware groups: An analysis of their origins, structures, and dynamics

Phipps, A., & Nurse, J. R. C. (2025) · Computers & Security · doi:10.1016/j.cose.2025.104705 · Cited by 6 · see citing works

Trends and challenges in research into the human aspects of ransomware: a systematic mapping study

Murray, G., Falkeling, M., & Gao, S. H. (2024) · Information and Computer Security · doi:10.1108/ics-12-2022-0195 · Cited by 6 · see citing works

Safeguarding Individuals and Organizations From Privacy Breaches: A Comprehensive Review of Problem Domains, Solution Strategies, and Prospective Research Directions

Kayes, A. S. M., Rahayu, W. J., Dillon, T. S., Shahraki, A. S., & Alavizadeh, H. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3481316 · Cited by 11 · see citing works

An Effective Strategy for Ransomware Mitigation on Android Devices via Android OS File System APIPreprint

Ozturk, M., Yilmaz, B., Arslan, Z., & Demirbas, A. (2024) · Research Square · doi:10.21203/rs.3.rs-4299415/v1 · Cited by 6 · see citing works

Multi-View Feature Fusion for Ransomware Detection in Executable Files: Dynamic, Static, and Image Features

Li, Y., Yang, Y. Z., Yan, L., Ma, W., & Hou, Y. (2023) · IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC) · doi:10.1109/itaic58329.2023.10408811 · Cited by 5 · see citing works

WannaLaugh: A Configurable Ransomware Emulator - Learning to Mimic Malicious Storage Traces

Diamantopoulos, D., Pletka, R. A., Sarafijanović, S., Reddy, N., & Pozidis, H. (2024) · ACM International Systems and Storage Conference (SYSTOR) · doi:10.1145/3688351.3689163 · Cited by 5 · see citing works

A Chronological Evolution Model for Crypto-Ransomware Detection Based on Encrypted File-Sharing TrafficPreprint

Morató, D., Berrueta, E., Magaña, E., & Izal, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4074557 · Cited by 4 · see citing works

RansomCillin: Leveraging NTFS Spare Space to Recover from Ransomware AttacksPreprint

Takeuchi, K., Fujima, H., Kumamoto, T., & Yoshida, Y. (2023) · Research Square · doi:10.21203/rs.3.rs-3648063/v1 · Cited by 4 · see citing works

DECEPTION BASED TECHNIQUES AGAINST RANSOMWARES: A SYSTEMATIC REVIEW

Georgina, C. S., Sakinah, F., Fadholi, M. R., Yazid, S., & Syafitri, W. (2023) · Jurnal Teknik Informatika (Jutif) · doi:10.52436/1.jutif.2023.4.3.886 · Cited by 3 · see citing works

Static-RWArmor: A Static Analysis Approach for Prevention of Cryptographic Windows Ransomware

Ayub, M. A., Siraj, A., Filar, B., & Gupta, M. (2023) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom60117.2023.00228 · Cited by 3 · see citing works

SAFARI: A Scalable Air-Gapped Framework for Automated Ransomware Investigation

Compagnucci, T., Callegati, F., Giallorenzo, S., Melis, A., Melloni, S., & Vannini, A. (2025) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-92882-6_15 · Cited by 3 · see citing works

Crypto Mining Attacks on Cyber Security

Kara, İ., & Hasgul, E. (2022) · Advances in finance, accounting, and economics book series · doi:10.4018/978-1-6684-6247-8.ch005 · Cited by 3 · see citing works

LockBit Black Ransomware On Reverse Shell: Analysis of Infection

Eliando, E., & Warsito, A. B. (2023) · CogITo Smart Journal · doi:10.31154/cogito.v9i2.494.228-240 · Cited by 3 · see citing works

Radial Spike and Slab Bayesian Neural Networks for Sparse Data in Ransomware Attacks

Nazarovs, J., Stokes, J. W., Turcotte, M., Carroll, J., & Grady, I. (2024) · Advances in information security · doi:10.1007/978-3-031-66245-4_2 · Cited by 4 · see citing works

Recommending Similar Devices in Close Proximity for Network Security Management

Bouček, V., & Husák, M. (2023) · IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) · doi:10.1109/wimob58348.2023.10187729 · Cited by 4 · see citing works

Applying Markov Decision Processes to Evaluate Ransomware Data Theft RisksPreprint

Zhu, T., Li, X., & Zhang, W. (2023) · Research Square · doi:10.21203/rs.3.rs-3736872/v1 · Cited by 3 · see citing works

Mapping Generative Artificial Intelligence (GAI's) Exciting Future: From Gemini to Q* and Beyond

Akhtar, Z. B. (2024) · EAI Endorsed Transactions on AI and Robotics · doi:10.4108/airo.5962 · Cited by 3 · see citing works

A conceptual framework to mitigate ransomware attacks on IoMT devices using threat intelligence: a systematic literature review

Selvaraj, K., Singh, M. M., & Zaaba, Z. F. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100801 · Cited by 2 · see citing works

Exploring the ransomware ecosystem and the active defense concept: Review of attacks and defense

Zhao, L., Wang, Z., Wang, S., Zhang, Y., Hou, R., & Meng, D. (2025) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2025.104171 · Cited by 2 · see citing works

Generative AI for Ransomware Identification and Mitigation: Taxonomy, Challenges, and Future Directions

Ramirez-Martinez, E. D., Pérez-Díaz, J. A., & Yungaicela-Naula, N. M. (2026) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2026.3690970 · Cited by 2 · see citing works

Applying Neutralisation Theory to Better Understand Ransomware Offenders

Connolly, L. Y., Borrion, H., Arief, B., & Kaddoura, S. (2023) · IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) · doi:10.1109/eurospw59978.2023.00025 · Cited by 2 · see citing works

Benchmark: Neural Network Malware Classification

Robinette, P. K., Lopez, D. M., & Johnson, T. T. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-46002-9_17 · Cited by 2 · see citing works

EPPMRRS: An Efficient and Privacy-Preserving Medical Record Retrieval Scheme in WBAN

Peng, S., Xiong, L., & Tang, X. (2024) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2024.109997 · Cited by 2 · see citing works

The business of ransomware and its effects on business

Warkentin, N., Zhang, Y., & Frank, R. W. (2025) · Journal of Cyber Security Technology · doi:10.1080/23742917.2025.2454620 · Cited by 2 · see citing works

Decentralized Identity Verification System for Data Access to Prevent Data Exfiltration RansomwarePreprint

Takeuchi, K., Kumamoto, T., Yoshida, Y., & Fujima, H. (2023) · doi:10.36227/techrxiv.24732729 · Cited by 2 · see citing works

Forensic Analysis of Live Ransomware Attacks on Linux-Based Laptop Systems: Techniques and EvaluationPreprint

Neweva, W., Fitzwilliam, O., & Waterbridge, J. (2024) · Research Square · doi:10.21203/rs.3.rs-4900486/v1 · Cited by 2 · see citing works

Detection of Stealthy Encryption in Ransomware Using AI-Driven Anomaly Detection ModelsPreprint

Hocosaj, A., Pendleton, C., & Stoddard, J. C. (2024) · Research Square · doi:10.21203/rs.3.rs-4955370/v1 · Cited by 2 · see citing works

RANSOMWARE: A PRIMER, SUGGESTED DETERRENCE AND A SYSTEMS THINKING APPROACH

(2022) · Issues in Information Systems · doi:10.48009/4_iis_2022_120 · Cited by 1 · see citing works

VR Headset Ransomware Attack Vulnerability

Tahat, M. Z., Glisson, W. B., & Smadi, B. A. (2024) · Conference proceedings - Canadian Conference on Electrical and Computer Engineering · doi:10.1109/ccece59415.2024.10667339 · Cited by 1 · see citing works

Data security challenges in medical records: A comparative analysis of digital and paper systems

Alsanad, I. S., Aldarbi, S. A., Aljohani, M. A., Alhejaili, M. A. M., Aldhahri, A. M., & Alarfi, M. D. M. (2023) · International Journal of Health Sciences · doi:10.53730/ijhs.v7ns1.15402 · Cited by 1 · see citing works

Lessons learned by a company facing a ransomware cyber-attack: A case study

Václavík, L., Špatenka, J., Petrová, K., & Zwilling, M. (2025) · Journal of Information Technology Teaching Cases · doi:10.1177/20438869251337096 · Cited by 1 · see citing works

Learning From the Past: Examining Ransomware Mitigations through a Systematic Literature Review

Tröster, N., Pissa, K., Paulus, B., & Schramm, R. C. (2026) · Gesellschaft für Informatik (GI) · doi:10.18420/sicherheit2026_07

The Age of Ransomware: A Survey on the Evolution, Taxonomy, and Research Directions

Razaulla, S., Fachkha, C., Markarian, C., Gawanmeh, A., Mansoor, W., Fung, B. C. M., & Assi, C. M. (2023) · IEEE Access · doi:10.1109/access.2023.3268535 · Cited by 131 · see citing works

Evolving Trends In Ransomware: An Analysis of Attack Vectors, Mitigation Strategies, and Future Trends

Dosumu, R. (2023) · doi:10.13140/rg.2.2.25305.49765

Navigating the Landscape of Ransomware Detection Methods: A Review

Benito, N., Martial, O., Banda, T., & Sahana, S. (2024) · Lecture notes in networks and systems · doi:10.1007/978-981-97-1961-7_28

A Survey on Ransomware: Evolution, Taxonomy, and Defense Solutions

Oz, H., Aris, A., Levi, A., & Uluagac, A. S. (2022) · ACM Computing Surveys · doi:10.1145/3514229 · Cited by 297 · see citing works