Works matching Ransomware
Results: 898
SEGURANÇA DA INFORMAÇÃO COM FOCO NA PROPAGAÇÃO IMINENTE DE RANSOMWARE NAS CORPORAÇÕES.
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- Revista Foco (Interdisciplinary Studies Journal), 2023, v. 16, n. 5, p. 1, doi. 10.54751/revistafoco.v16n5-024
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A SOCIEDADE DA INFORMAÇÃO E SEUS DESAFIOS: A NECESSIDADE DE EFETIVAÇÃO DE UMA POLÍTICA PÚBLICA DE COMBATE AO RANSOMWARE NO BRASIL.
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- Revista da Faculdade de Direito da Uerj, 2019, n. 36, p. 23
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RANSOMWARE E CIBERSEGURANÇA: A INFORMAÇÃO AMEAÇADA POR ATAQUES A DADOS.
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- Revista Thesis Juris, 2020, v. 9, n. 1, p. 208, doi. 10.5585/rtj.v9i1.16739
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Ransomware Detection System Based on Machine Learning.
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- Journal of Education & Science, 2021, v. 30, n. 5, p. 86, doi. 10.33899/edusj.2021.130760.1173
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基于熵图像静态分析技术的勒索软件分类研究.
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- Journal of Guangxi Normal University - Natural Science Edition, 2023, v. 41, n. 3, p. 91, doi. 10.16088/j.issn.1001-6600.2022100805
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An Enhanced Minimax Loss Function Technique in Generative Adversarial Network for Ransomware Behavior Prediction.
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- Future Internet, 2023, v. 15, n. 10, p. 318, doi. 10.3390/fi15100318
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Opportunities for Early Detection and Prediction of Ransomware Attacks against Industrial Control Systems.
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- Future Internet, 2023, v. 15, n. 4, p. 144, doi. 10.3390/fi15040144
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Ransomware Detection, Avoidance, and Mitigation Scheme: A Review and Future Directions.
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- Sustainability (2071-1050), 2022, v. 14, n. 1, p. 8, doi. 10.3390/su14010008
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Ransomware Detection Based on PE Header Using Convolutional Neural Networks.
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- ISeCure, 2022, v. 14, n. 2, p. 181, doi. 10.22042/ISECURE.2021.262846.595
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Zsarolóvírusok és a No More Ransom projekt.
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- Belügyi Szemle / Academic Journal of Internal Affairs, 2022, v. 70, n. 9, p. 1887, doi. 10.38146/BSZ.2022.9.9
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Understanding the Influence of Ransomware: An Investigation on its Development, Mitigation and Avoidance Techniques.
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- Grenze International Journal of Engineering & Technology (GIJET), 2018, v. 4, n. 3, p. 123
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Ransomware protection in loT using software defined networking.
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- International Journal of Electrical & Computer Engineering (2088-8708), 2020, v. 10, n. 3, p. 3166, doi. 10.11591/ijece.v10i3.pp3166-3175
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Ransomware Detection Service: Execution and Analysis Using Machine Learning Techniques.
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- Wireless Personal Communications, 2023, v. 133, n. 2, p. 995, doi. 10.1007/s11277-023-10801-w
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The Legal Corner (TLC): Ransomware Attacks Against Health Care IT.
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- Journal of Informatics Nursing, 2017, v. 2, n. 4, p. 30
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How to Circumvent and Beat the Ransomware in Android Operating System—A Case Study of Locker.CB!tr.
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- Electronics (2079-9292), 2024, v. 13, n. 11, p. 2212, doi. 10.3390/electronics13112212
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Adaptive Ransomware Detection Using Similarity-Preserving Hashing.
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- Applied Sciences (2076-3417), 2024, v. 14, n. 20, p. 9548, doi. 10.3390/app14209548
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Ransomware Detection Using the Dynamic Analysis and Machine Learning: A Survey and Research Directions.
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- Applied Sciences (2076-3417), 2022, v. 12, n. 1, p. 172, doi. 10.3390/app12010172
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KRDroid: Ransomware-Oriented Detector for Mobile Devices Based on Behaviors.
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- Applied Sciences (2076-3417), 2021, v. 11, n. 14, p. 6557, doi. 10.3390/app11146557
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Introduction of the ARDS—Anti-Ransomware Defense System Model—Based on the Systematic Review of Worldwide Ransomware Attacks.
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- Applied Sciences (2076-3417), 2021, v. 11, n. 13, p. 6070, doi. 10.3390/app11136070
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A Multi-Tier Streaming Analytics Model of 0-Day Ransomware Detection Using Machine Learning.
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- Applied Sciences (2076-3417), 2020, v. 10, n. 9, p. 3210, doi. 10.3390/app10093210
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e MIFS: A Normalized Hyperbolic Ransomware Deterrence Model Yielding Greater Accuracy and Overall Performance.
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- Sensors (14248220), 2024, v. 24, n. 6, p. 1728, doi. 10.3390/s24061728
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Trends in Mobile Ransomware and Incident Response from a Digital Forensics Perspective.
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- Journal of Information & Communication Convergence Engineering, 2022, v. 20, n. 4, p. 280, doi. 10.56977/jicce.2022.20.4.280
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Ransomware through the lens of state crime: Conceptualizing ransomware groups as cyber proxies, pirates, and privateers.
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- State Crime Journal, 2023, v. 12, n. 1, p. 1, doi. 10.13169/statecrime.12.1.0004
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Securing IoT Devices Running PureOS from Ransomware Attacks: Leveraging Hybrid Machine Learning Techniques.
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- Mathematics (2227-7390), 2023, v. 11, n. 11, p. 2481, doi. 10.3390/math11112481
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Retaliation against Ransomware in Cloud-Enabled PureOS System.
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- Mathematics (2227-7390), 2023, v. 11, n. 1, p. 249, doi. 10.3390/math11010249
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Analyzing Reporting on Ransomware Incidents: A Case Study.
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- Social Sciences (2076-0760), 2023, v. 12, n. 5, p. 265, doi. 10.3390/socsci12050265
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Analyzing TorrentLocker Ransomware Attacks: A Real Case Study.
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- Sakarya University Journal of Science (SAUJS) / Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2024, v. 28, n. 4, p. 774, doi. 10.16984/saufenbilder.1442756
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Deterrence, Backup, or Insurance: Game-Theoretic Modeling of Ransomware.
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- Games (20734336), 2023, v. 14, n. 2, p. 20, doi. 10.3390/g14020020
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Ransomware and Reputation.
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- Games (20734336), 2019, v. 10, n. 2, p. 26, doi. 10.3390/g10020026
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Early Ransomware Detection with Deep Learning Models.
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- Future Internet, 2024, v. 16, n. 8, p. 291, doi. 10.3390/fi16080291
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Ransomware-Resilient Self-Healing XML Documents.
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- Future Internet, 2022, v. 14, n. 4, p. 115, doi. 10.3390/fi14040115
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KRRecover: An Auto-Recovery Tool for Hijacked Devices and Encrypted Files by Ransomwares on Android.
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- Symmetry (20738994), 2021, v. 13, n. 5, p. 861, doi. 10.3390/sym13050861
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Leveraging Contractive Autoencoder with Fuzzy Lattice Reasoning and Resilient KNN for Detection of multi-level Bitcoin Ransomware.
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- Journal of Information Assurance & Security, 2022, v. 17, n. 4, p. 165
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Windows-based Ransomware: A Survey.
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- Journal of Information Assurance & Security, 2020, v. 15, n. 3, p. 107
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A Study of Android-based Ransomware: Discovery, Methods, and Impacts.
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- Journal of Information Assurance & Security, 2018, v. 13, n. 3, p. 109
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Ransomware: A Survey and Trends.
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- Journal of Information Assurance & Security, 2017, v. 6, n. 2, p. 48
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A Weighted Minimum Redundancy Maximum Relevance Technique for Ransomware Early Detection in Industrial IoT.
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- Sustainability (2071-1050), 2022, v. 14, n. 3, p. 1231, doi. 10.3390/su14031231
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The business case for ransomware exercises for business and technology teams.
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- Journal of Business Continuity & Emergency Planning, 2023, v. 16, n. 4, p. 294, doi. 10.69554/lesx9272
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Examining Personal and Altruistic Fear of Ransomware.
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- Victims & Offenders, 2023, v. 18, n. 7, p. 1236, doi. 10.1080/15564886.2022.2159597
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Interrelationship between Bitcoin, Ransomware, and Terrorist Activities: Criminal Opportunity Assessment via Cyber-Routine Activities Theoretical Framework.
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- Victims & Offenders, 2021, v. 16, n. 3, p. 363, doi. 10.1080/15564886.2020.1835764
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Android ransomware detection using binary Jaya optimization algorithm.
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- Expert Systems, 2024, v. 41, n. 1, p. 1, doi. 10.1111/exsy.13479
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KYBERNETICKÁ BEZPEČNOST VE ZDRAVOTNICTVÍ: Poučení z případu benešovské nemocnice napadené ransomwarem Ryuk.
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- Defense & Strategy / Obrana a strategie, 2021, v. 21, n. 1, p. 27, doi. 10.3849/1802-7199.21.2021.01.027-052
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RANSOMWARE: A RESEARCH AND A PERSONAL CASE STUDY OF DEALING WITH THIS NASTY MALWARE.
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- Issues in Informing Science & Information Technology, 2017, v. 14, p. 87, doi. 10.28945/3707
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Dynamic Analysis-Based Early-stage Ransomware Detection Using Deep Learning.
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- International Journal of Intelligent Engineering & Systems, 2024, v. 17, n. 6, p. 663, doi. 10.22266/ijies2024.1231.51
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Deep Ensemble Classifier for Ransomware Identification Using Digitalized DNA Genotyping System.
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- International Journal of Intelligent Engineering & Systems, 2022, v. 15, n. 6, p. 503, doi. 10.22266/ijies2022.1231.45
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МОНІТОРИНГ ВІРУСІВ-ВИМАГАЧІВ ЗА ДОПОМОГОЮ РОЗШИРЕНОГО БЕРКЛІЙСЬКОГО ПАКЕТНОГО ФІЛЬТРА (EBPF) ТА МАШИННОГО НАВЧАННЯ.
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- Science-Based Technologies, 2024, v. 64, n. 4, p. 352, doi. 10.18372/2310-5461.60.18029
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МОНІТОРИНГ ВІРУСІВ-ВИМАГАЧІВ ЗА ДОПОМОГОЮ РОЗШИРЕНОГО БЕРКЛІЙСЬКОГО ПАКЕТНОГО ФІЛЬТРА (EBPF) ТА МАШИННОГО НАВЧАННЯ.
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- Science-Based Technologies, 2023, v. 60, n. 4, p. 352, doi. 10.18372/2310-5461.60.18029
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Observing, Measuring and Collecting HDD Performance Metrics on a Physical Machine During Ransomware Attack.
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- Information & Security, 2020, v. 47, n. 3, p. 317, doi. 10.11610/isij.4723
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Earlier Decision on Detection of Ransomware Identification: A Comprehensive Systematic Literature Review.
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- Information (2078-2489), 2024, v. 15, n. 8, p. 484, doi. 10.3390/info15080484
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Novel Ransomware Detection Exploiting Uncertainty and Calibration Quality Measures Using Deep Learning.
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- Information (2078-2489), 2024, v. 15, n. 5, p. 262, doi. 10.3390/info15050262
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