:books: Literature

• Scientific Research

  • Adversarial attacks against windows PE malware detection: A survey of the state-of-the-art
  • Adversarial malware binaries: Evading deep learning for malware detection in executables
  • Analysis of machine learning approaches to packing detection
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Birds of a feature: Intrafamily clustering for version identification of packed malware
  • Bypassing anti-analysis of commercial protector methods using DBI tools
  • A comprehensive solution for obfuscation detection and removal based on comparative analysis of deobfuscation tools
  • Detecting traditional packers, decisively
  • A dynamic heuristic method for detecting packed malware using naive bayes
  • Enhancing machine learning based malware detection model by reinforcement learning
  • Evading anti-malware engines with deep reinforcement learning
  • Experimental toolkit for manipulating executable packing
  • Feature selection for malware detection based on reinforcement learning
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Intriguing properties of neural networks
  • Learning to evade static PE machine learning malware models via reinforcement learning
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • MetaAware: Identifying metamorphic malware
  • Obfuscator-LLVM: Software protection for the masses
  • On the (Im)possibility of obfuscating programs
  • Packer identification method for multi-layer executables with k-Nearest neighbor of entropies
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • Practical attacks on machine learning: A case study on adversarial windows malware
  • RePEF — A system for restoring packed executable file for malware analysis
  • SoK: (state of) the art of war: Offensive techniques in binary analysis
  • A survey on machine learning-based detection and classification technology of malware
  • A survey on malware analysis techniques: Static, dynamic, hybrid and memory analysis
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • Towards static analysis of virtualization-obfuscated binaries
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • A close look at a daily dataset of malware samples
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Automatic analysis of malware behavior using machine learning
  • Detecting traditional packers, decisively
  • Experimental toolkit for manipulating executable packing
  • A fast flowgraph based classification system for packed and polymorphic malware on the endhost
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • PEzoNG: Advanced packer for automated evasion on Windows
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • BitBlaze: A new approach to computer security via binary analysis
  • Denial-of-service attacks on host-based generic unpackers
  • Detecting traditional packers, decisively
  • DexHunter: Toward extracting hidden code from packed Android applications
  • Efficient and automatic instrumentation for packed binaries
  • Experimental toolkit for manipulating executable packing
  • A fine-grained classification approach for the packed malicious code
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Generic unpacking method based on detecting original entry point
  • Information theoretic method for classification of packed and encoded files
  • A machine-learning-based framework for supporting malware detection and analysis
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • OPEM: A static-dynamic approach for machine-learning-based malware detection
  • Packer identification using byte plot and Markov plot
  • Packer identification using hidden Markov model
  • Pattern recognition techniques for the classification of malware packers
  • PE-Miner: Mining structural information to detect malicious executables in realtime
  • PEAL - Packed executable analysis
  • PEzoNG: Advanced packer for automated evasion on Windows
  • RAMBO: Run-Time packer analysis with multiple branch observation
  • Research of software information hiding algorithm based on packing technology
  • Semi-supervised learning for unknown malware detection
  • A static, packer-agnostic filter to detect similar malware samples
  • A study of the packer problem and its solutions
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • BitBlaze: A new approach to computer security via binary analysis
  • Denial-of-service attacks on host-based generic unpackers
  • Detecting traditional packers, decisively
  • DexHunter: Toward extracting hidden code from packed Android applications
  • Efficient and automatic instrumentation for packed binaries
  • Experimental toolkit for manipulating executable packing
  • A fine-grained classification approach for the packed malicious code
  • Generic black-box end-to-end attack against state of the art API call based malware classifiers
  • Generic unpacking method based on detecting original entry point
  • A machine-learning-based framework for supporting malware detection and analysis
  • Mal-XT: Higher accuracy hidden-code extraction of packed binary executable
  • Mal-xtract: Hidden code extraction using memory analysis
  • On the (Im)possibility of obfuscating programs
  • Packer identification using byte plot and Markov plot
  • Packer identification using hidden Markov model
  • Pattern recognition techniques for the classification of malware packers
  • PE-Miner: Mining structural information to detect malicious executables in realtime
  • PEAL - Packed executable analysis
  • PEzoNG: Advanced packer for automated evasion on Windows
  • RAMBO: Run-Time packer analysis with multiple branch observation
  • Research of software information hiding algorithm based on packing technology
  • Semi-supervised learning for unknown malware detection
  • A static, packer-agnostic filter to detect similar malware samples
  • A study of the packer problem and its solutions
  • A survey on run-time packers and mitigation techniques
  • Symbolic deobfuscation: From virtualized code back to the original
  • Symbolic execution of obfuscated code
  • 2-SPIFF: A 2-stage packer identification method based on function call graph and file attributes
  • Advanced feature engineering for static detection of executable packing
  • AppSpear: Bytecode decrypting and DEX reassembling for packed Android malware
  • Assessing static and dynamic features for packing detection
  • Assessing the impact of packing on machine learning-based malware detection and classification systems
  • Automated static analysis of virtual-machine packers
  • BitBlaze: A new approach to computer security via binary analysis
  • A compact multi-step framework for packing identification in portable executable files for malware analysis
  • Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE)
  • Control flow-based opcode behavior analysis for malware detection
  • Decoding the secrets of machine learning in malware classification: A deep dive into datasets, feature extraction, and model performance
  • Denial-of-service attacks on host-based generic unpackers
  • Detecting packed executables based on raw binary data
  • Detecting traditional packers, decisively
  • Detecting unknown malicious code by applying classification techniques on opcode patterns
  • Detection of metamorphic malware packers using multilayered LSTM networks
  • DexHunter: Toward extracting hidden code from packed Android applications
  • DroidPDF: The obfuscation resilient packer detection framework for Android Apps
  • An efficient algorithm to extract control flow-based features for ioT malware detection
  • Efficient and automatic instrumentation for packed binaries
  • Entropy analysis to classify unknown packing algorithms for malware detection
  • ERMDS: A obfuscation dataset for evaluating robustness of learning-based malware detection system