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Security

Ransomware Detection

  1. Travelling the Hypervisor and SSD: A Tag-Based Approach Against Crypto Ransomware with Fine-Grained Data Recovery [CCS'23]
  2. RøB: Ransomware over Modern Web Browsers [USENIX Security'23]
  3. A Survey on Ransomware: Evolution, Taxonomy, and Defense Solutions [ACM Computing Surveys'22]
  4. Poster: Data Recovery from Ransomware Attacks via File System Forensics and Flash Translation Layer Data Extraction [CCS'22]
  5. Poster: MUSTARD - Adaptive Behavioral Analysis for Ransomware Detection [CCS'22]
  6. Wake Up Digital Forensics’ Community and Help Combat Ransomware [IEEE Symposium on Security and Privacy'22]
  7. Behavior-based ransomware classification: A particle swarm optimization wrapper-based approach for feature selection [Applied Soft Computing'22]
  8. Peeler: Profiling Kernel-Level Events to Detect Ransomware [arXiv'21]
  9. BitcoinHeist: Topological Data Analysis for Ransomware Prediction on the Bitcoin Blockchain [IJCAI'20]
  10. Ransomware Detection techniques in the Dawn of Artificial Intelligence: A Survey[ICNCC '20]
  11. Ransomware protection in IoT using software defined networking [IJECE'20]
  12. Two Stage Ransomware Detection Using Dynamic Analysis and Machine Learning Techniques[Wireless Personal Communications: An International Journal Vol. 112, No. 4, '20]
  13. On the Effectiveness of Application Permissions for Android Ransomware Detection [CDMA'20]
  14. Optimizing Extreme Learning Machines Using Chains of Salps for Efficient Android Ransomware Detection [Applied Sciences 2020]
  15. Industrial Internet of Things Based Ransomware Detection using Stacked Variational Neural Network [BDIOT'19]
  16. Leveraging Deep Learning Models for Ransomware Detection in the Industrial Internet of Things Environment [MilCIS'19]
  17. Intelligent and Dynamic Ransomware Spread Detection and Mitigation in Integrated Clinical Environments [Sensors'19]
  18. Multilayer ransomware detection using grouped registry key operations,fileentropy and file signature monitoring [Journal of Computer Security. 2019]
  19. Crypto-ransomware early detection model using novel incremental bagging with enhanced semi-random subspace selection [Future Generation Computer Systems'19]
  20. Classification of ransomware families with machine learning based on N-gram of opcodes [Future Generation Computer Systems 90 (2019)]
  21. TEE-aided Write Protection Against Privileged Data Tampering [NDSS'19]
  22. Ransomware detection and mitigation using software-defined networking: The case of WannaCry [Computers & Electrical Engineering Volume76'19]
  23. RansomBlocker: a Low-Overhead Ransomware-Proof SSD [DAC'19]
  24. Hands Off my Database: Ransomware Detection in Databases through Dynamic Analysis of Query Sequences [arXiv'19]
  25. Ransomware Detection System for Android Applications [Electronics 2019]
  26. Ransomware Detection Based on an Improved Double-Layer Negative Selection Algorithm [Testbeds and Research Infrastructures for the Development of Networks and Communications'19]
  27. On the effectiveness of system API-related information for Android ransomware detection [Computers & Security 2019]
  28. The Case for Native Instructions in the Detection of Mobile Ransomware [IEEE Letters of the Computer Society 2019]
  29. An Intelligent Behavior-Based Ransomware Detection System For Android Platform [TPS-ISA'19]
  30. Ransomware Detection Using Limited Precision Deep Learning Structure in FPGA [NAECON'18]
  31. Extinguishing Ransomware - A Hybrid Approach to Android Ransomware Detection [International Symposium on Foundations and Practice of Security 2018]
  32. RWGuard: A Real-Time Detection System Against Cryptographic Ransomware [International Symposium on Research in Attacks, Intrusions, and Defenses. 2018]
  33. Zero-day aware decision fusion-based model for crypto-ransomware early detection [International Journal of Integrated Engineering'18]
  34. Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection [arXiv'18]
  35. Machine Learning-Based Detection of Ransomware Using SDN [SDN-NFV Sec'18]
  36. Trusted detection of ransomware in a private cloud using machine learning methods leveraging meta-features from volatile memory [Expert Systems with Applications 2018]
  37. SSD-Insider: Internal Defense of Solid-State Drive against Ransomware with Perfect Data Recovery [IEEE 38th International Conference on Distributed Computing Systems. 2018]
  38. Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware [Cyber Threat Intelligence 2018]
  39. A New Static-Based Framework for Ransomware Detection[DASC'18]
  40. The aftermath of a crypto-ransomware attack at a large academic institution [USENIX Security'18]
  41. Protecting against Ransomware: A New Line of Research or Restating Classic Ideas? [IEEE Symposium on Security and Privacy'18]
  42. A Storage-level Detection Mechanism against Crypto-Ransomware [CCS'18]
  43. Tracking Ransomware End-to-end [IEEE Symposium on Security and Privacy'18]
  44. Ransomware Prevention usng Application Authentication-Based File Access Control [Symposium on Applied Computing SAC'18]
  45. Amoeba: An Autonomous Backup and Recovery SSD for Ransomware Attack Defense [IEEE Computer Architecture Letters’18]
  46. Detecting Ransomware using Support Vector Machines [ICPP Workshops'18]
  47. RanDroid: Structural Similarity Approach for Detecting Ransomware Applications in Android Platform [EIT'18]
  48. Uncovering the Face of Android Ransomware: Characterization and Real-Time Detection [IEEE Transactions on Information Forensics and Security 2018]
  49. A Novel Structural-Entropy-based Classification Technique for Supporting Android Ransomware Detection and Analysis [FUZZ-IEEE'18]
  50. DNA-Droid: A Real-Time Android Ransomware Detection Framework [International Conference on Network and System Security'17]
  51. Detecting crypto-ransomware in IoT networks based on energy consumption footprint [Journal of Ambient Intelligence and Humanized Computing 2017]
  52. Android ransomware detection using reduced opcode sequence and image similarity [ICCKE'17]
  53. R-PackDroid: API package-based characterization and detection of mobile ransomware [SAC '17]
  54. Deep learning LSTM based ransomware detection [RDCAPE'17]
  55. Automatic Ransomware Detection and Analysis Based on Dynamic API Calls Flow Graph [RACS'17]
  56. Redemption: Real-Time Protection Against Ransomware at End-Hosts [International Symposium on Research in Attacks, Intrusions, and Defenses'17]
  57. Data Aware Defense (DaD): Towards a Generic and Practical Ransomware Countermeasure [NordSec'17]
  58. FlashGuard: Leveraging Intrinsic Flash Properties to Defend Against Encryption Ransomware [CCS'17]
  59. PayBreak: Defense Against Cryptographic Ransomware [ASIA CCS'17]
  60. Talos: No more ransomware victims with formal methods [International Journal of Information Security 2017]
  61. ShieldFS: a self-healing, ransomware-aware filesystem [ACSAC'16]
  62. CryptoLock (and Drop It): Stopping Ransomware Attacks on User Data [International Conference on Distributed Computing Systems’16]
  63. UNVEIL: A Large-Scale, Automated Approach to Detecting Ransomware [USENIX Security'16]
  64. The Effective Ransomware Prevention Technique Using Process Monitoring on Android Platform [Mobile Information Systems'16]
  65. Ransomware Steals Your Phone. Formal Methods Rescue It [International Conference on Formal Techniques for Distributed Objects, Components, and Systems 2016]

Malware Detection

  1. Certified Robustness of Static Deep Learning-based Malware Detectors against Patch and Append Attacks [AISec'23]
  2. AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware Corpora [AISec'23]
  3. Drift Forensics of Malware Classifiers [AISec'23]
  4. Lookin' Out My Backdoor! Investigating Backdooring Attacks Against DL-driven Malware Detectors [AISec'23]
  5. Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis [NDSS'23]
  6. Fusion: Efficient and Secure Inference Resilient to Malicious Servers [NDSS'23]
  7. Deep Learning for Zero-day Malware Detection and Classification: A Survey [ACM Computing Surveys'23]
  8. Humans vs. Machines in Malware Classification [USENIX Security '23]
  9. FCGAT: Interpretable Malware Classification Method using Function Call Graph and Attention Mechanism [NDSS'23]
  10. Exposing the Rat in the Tunnel: Using Traffic Analysis for Tor-based Malware Detection [CCS'22]
  11. Quo Vadis: Hybrid Machine Learning Meta-Model Based on Contextual and Behavioral Malware Representations [AISec'22]
  12. Malware Makeover: Breaking ML-based Static Analysis by Modifying Executable Bytes [ASIA CCS'21]
  13. Investigating Labelless Drift Adaptation for Malware Detection [AISec'21]
  14. Forecasting Malware Capabilities From Cyber Attack Memory Images [USENIX Security'21]
  15. When Malware Changed Its Mind: An Empirical Study of Variable Program Behaviors in the Real World [USENIX Security'21]
  16. Differential Training: A Generic Framework to Reduce Label Noises for Android Malware Detection [NDSS'21]
  17. DeepReflect: Discovering Malicious Functionality through Binary Reconstruction [USENIX Security'21]
  18. Dynamic Malware Analysis with Feature Engineering and Feature Learning [AAAI'20]
  19. Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Malware Analysis [AISec'20]
  20. Flow-based Detection and Proxy-based Evasion of Encrypted Malware C2 Traffic [AISec'20]
  21. You Are What You Do: Hunting Stealthy Malware via Data Provenance Analysis [NDSS'20]
  22. Prevalence and Impact of Low-Entropy Packing Schemes in the Malware Ecosystem [NDSS'20]
  23. When Malware is Packin' Heat; Limits of Machine Learning Classifiers Based on Static Analysis Features [NDSS'20]
  24. ExSpectre: Hiding Malware in Speculative Execution [NDSS'19]
  25. Classification of Malware by Using Structural Entropy on Convolutional Neural Networks [AAAI'18]
  26. Monotonic models for real-time dynamic malware detection [ICLR'18]

Ransomware and Malware Database/Datasets

  1. RanSAP: An Open Dataset of Ransomware Storage Access Patterns [Ransomware]
  2. Ransomware in the Bitcoin Ecosystem | Dataset Extraction [Ransomware]
  3. VirusTotal [Ransomware and Malware]
  4. OPEN REPOSITORY FOR THE EVALUATION OF RANSOMWARE DETECTION TOOLS [Ransomware]
  5. MalwareBazaar [Malware]
  6. National Vulnerability Database (NVD) [Ransomware and Malware]
  7. Android Ransomware Detection [Ransomware]
  8. Ransomware PE Header Feature Dataset [Ransomware]
  9. Dataset of "Extinguishing Ransomware - A Hybrid Approach to Android Ransomware Detection" [Ransomware]
  10. Bitcoin Heist Ransomware Address Dataset [Ransomware]
  11. Awesome-Cybersecurity-Datasets [Ransomware and Malware]
  12. Ransomware PCAP repository [Ransomware]
  13. HelDroid [Android ransomware]
  14. vx-underground [APT Attack / Malware]
  15. DikeDataset [Malware]
  16. PE Malware Machine Learning Dataset [Malware]
  17. Malware Detection PE-Based Analysis Using Deep Learning Algorithm Dataset [Malware]
  18. virusshare [Malware]
  19. SHIELDFS [A Self-healing, Ransomware-aware Filesystem]
  20. Ransomware Attacks [Ransomware Datasets]
  21. Ransomware Dataset
  22. ISOT Ransomware Detection Dataset
  23. BODMAS Malware Dataset [Malware]
  24. Maldatabase (Malware)
  25. vizsec (Malware / APT)
  26. Machine Learning-Based NIDS Datasets

Network Traffic Datasets (Malicious Traffic, DDoS Attack, etc)

  1. DDoS Evaluation Dataset (CIC-DDoS2019) [DDoS Attack]
  2. MAWI Working Group Traffic Archive [Malicious Traffic]
  3. CSE-CIC-IDS2018 on AWS [Malicious Traffic]

eBPF

  1. Cross Container Attacks: The Bewildered eBPF on Clouds [USENIX Security'23]
  2. Electrode: Accelerating Distributed Protocols with eBPF [NSDI'23]
  3. Fast In-kernel Traffic Sketching in eBPF [SIGCOMM'23]
  4. Comparing Security in eBPF and WebAssembly [eBPF'23]
  5. Seeing the Invisible: Auditing eBPF Programs in Hypervisor with HyperBee [eBPF'23]
  6. Enabling BPF Runtime policies for better BPF management [eBPF'23]
  7. Network Profiles for Detecting Application-Characteristic Behavior Using Linux eBPF [eBPF'23]
  8. RingGuard: Guard io_uring with eBPF [eBPF'23]
  9. Unleashing Unprivileged eBPF Potential with Dynamic Sandboxing [eBPF'23]
  10. Practical and Flexible Kernel CFI Enforcement using eBPF [eBPF'23]
  11. Understanding the Security of Linux eBPF Subsystem [APSys'23]
  12. Unleashing Unprivileged eBPF Potential with Dynamic Sandboxing [arXiv'23]
  13. SPRIGHT:ExtractingtheServerfromServerlessComputing! High-performanceeBPF-basedEvent-driven,Shared-memory Processing [SIGCOMM'22]
  14. XRP: In-Kernel Storage Functions with eBPF [OSDI'22]
  15. A flow-based IDS using Machine Learning in eBPF [Arxiv'22]
  16. BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack Processing [NSDI'21]
  17. Specification and verification in the field: applying formal methods to BPF just-in-time compilers in the Linux kernel [OSDI'20]
  18. bpfbox: Simple Precise Process Confinement with eBPF [CCSW'20]
  19. Simple and precise static analysis of untrusted Linux kernel extensions [PLDI'19]
  20. PeriScope: An Effective Probing and Fuzzing Framework for the Hardware-OS Boundary [NDSS'19]