Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers

No abstract is available for this paper.

• Publication year

  2016

• Venue

  Network and Distributed System Security Symposium

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.14722/NDSS.2016.23115
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Practical Evasion of a Learning-Based Classifier: A Case Study

  2014influential reference
• Deep neural networks are easily fooled: High confidence predictions for unrecognizable images

  2014cited by this paper
• Evasion Attacks against Machine Learning at Test Time

  2013cited by this paper
• Looking at the bag is not enough to find the bomb: an evasion of structural methods for malicious PDF files detection

  2013cited by this paper
• Detection of Malicious PDF Files Based on Hierarchical Document Structure

  2013influential reference
• Large-scale malware classification using random projections and neural networks

  2013cited by this paper
• Genetic programming for Reverse Engineering

  2013cited by this paper
• A Pattern Recognition System for Malicious PDF Files Detection

  2012cited by this paper
• GenProg: A Generic Method for Automatic Software Repair

  2012cited by this paper
• Malicious PDF detection using metadata and structural features

  2012influential reference
• Static detection of malicious JavaScript-bearing PDF documents

  2011cited by this paper
• Detection and analysis of drive-by-download attacks and malicious JavaScript code

  2010cited by this paper
• Ensembles in adversarial classification for spam

  2009cited by this paper
• Multiple Classifier Systems for Adversarial Classification Tasks

  2009cited by this paper
• Can machine learning be secure?

  2006cited by this paper
• Adversarial learning

  2005cited by this paper
• Adversarial classification

  2004cited by this paper
• Automatic Re-engineering of Software Using Genetic Programming

  1999cited by this paper
• Genetic algorithms: principles of natural selection applied to computation.

  1993cited by this paper
• Genetic Programming: On the Programming of Computers by Means of Natural Selection

  1992cited by this paper

• Adversarial Shadows in Digital Forensics: New Insights Into File Fragment Classification Vulnerabilities and Defenses

  2026cites this paper
• A Concave Matrix Generative Adversarial Network Model for Detecting and Enhancing Cyber-Security Threats and Awareness

  2025cites this paper
• On the Security Risks of ML-based Malware Detection Systems: A Survey

  2025cites this paper
• Attention-Guided SAT Solver Approach for Robust Adversarial Defense in Machine Learning

  2025cites this paper
• On the Efficiency of Training Robust Decision Trees

  2025cites this paper
• μGAN: A mutation-based cost optimal adversarial malware generation approach against evolving Android malware variants

  2025cites this paper
• Malware Detection with AI: A Comprehensive Review of Trends and Challenges with Future Directions

  2025cites this paper
• Algorithm Explainability for Malware Evolution with Search Trajectory Networks

  2025cites this paper
• Analyzing PDFs like Binaries: Adversarially Robust PDF Malware Analysis via Intermediate Representation and Language Model

  2025cites this paper
• Detecting Evasive PDF Malware: A Comparative Analysis of Advanced Machine Learning Approaches

  2025cites this paper
• An Efficient PDF Malware Detection Method Using Highly Compact Features

  2024cites this paper
• Camouflage is all you need: Evaluating and Enhancing Language Model Robustness Against Camouflage Adversarial Attacks

  2024cites this paper
• Securing ML Models: A Systematic Survey of Poisoning Attacks and Defense Mechanisms

  2024cites this paper
• XploitSQL: Advancing Adversarial SQL Injection Attack Generation with Language Models and Reinforcement Learning

  2024cites this paper
• A Survey on Offensive AI Within Cybersecurity

  2024cites this paper
• CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers

  2024cites this paper
• Exposing Vulnerabilities in PDF Malware Detectors to Evasion Attacks

  2024cites this paper
• Practical evasion attack against neural network-based macro-malware detection method

  2024cites this paper
• AIAS: AI-ASsisted cybersecurity platform to defend against adversarial AI attacks

  2024cites this paper
• Evaluating Representativeness in PDF Malware Datasets: A Comparative Study and a New Dataset

  2023cites this paper
• A survey on the evolution of fileless attacks and detection techniques

  2023cites this paper
• MANDA: On Adversarial Example Detection for Network Intrusion Detection System

  2023influential citation
• An Evolutionary Algorithm for Adversarial SQL Injection Attack Generation

  2023cites this paper
• ELAMD: An ensemble learning framework for adversarial malware defense

  2023cites this paper
• A Survey on Cybersecurity Enhancing Malware Classification using Deep Learning Convolution Neural Networks

  2023cites this paper
• MPass: Bypassing Learning-based Static Malware Detectors

  2023cites this paper
• Machine Learning needs Better Randomness Standards: Randomised Smoothing and PRNG-based attacks

  2023cites this paper
• Detection of Network Intrusions Using Anomaly Detection

  2023cites this paper
• A Survey of Adversarial Attack and Defense Methods for Malware Classification in Cyber Security

  2023influential citation
• A Feasibility Study on Evasion Attacks Against NLP-Based Macro Malware Detection Algorithms

  2023cites this paper
• A Feature Set of Small Size for the PDF Malware Detection

  2023cites this paper
• A PDF Malware Detection Method Using Extremely Small Training Sample Size

  2023cites this paper
• An Evolutionary based Generative Adversarial Network Inspired Approach to Defeating Metamorphic Malware

  2023cites this paper
• Content Disarm and Reconstruction of PDF Files

  2023cites this paper
• "Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences

  2023cites this paper
• "Security is not my field, I'm a stats guy": A Qualitative Root Cause Analysis of Barriers to Adversarial Machine Learning Defenses in Industry

  2023cites this paper
• MAB-Malware: A Reinforcement Learning Framework for Blackbox Generation of Adversarial Malware

  2022cites this paper
• Measuring Machine Learning Robustness in front of Static and Dynamic Adversaries*

  2022cites this paper
• MMPD: A Novel Malicious PDF File Detector for Mobile Robots

  2022cites this paper
• Privacy against Real-Time Speech Emotion Detection via Acoustic Adversarial Evasion of Machine Learning

  2022influential citation
• Generating Content-Preserving and Semantics-Flipping Adversarial Text

  2022cites this paper
• Poster: Feasibility of Malware Visualization Techniques against Adversarial Machine Learning Attacks

  2022cites this paper
• Problem-Space Evasion Attacks in the Android OS: a Survey

  2022cites this paper
• Towards Robust Detection of PDF-based Malware

  2022cites this paper
• Do You Think You Can Hold Me? The Real Challenge of Problem-Space Evasion Attacks

  2022cites this paper
• Coverage-guided differential testing of TLS implementations based on syntax mutation

  2022cites this paper
• A novel detection technique based on benign samples and one-class algorithm for malicious PDF documents containing JavaScript

  2022cites this paper
• Evading behavioral classifiers: a comprehensive analysis on evading ransomware detection techniques

  2022cites this paper
• DualCF: Efficient Model Extraction Attack from Counterfactual Explanations

  2022cites this paper
• Secure machine learning against adversarial samples at test time

  2022cites this paper
• Adversarial Attacks for Intrusion Detection Based on Bus Traffic

  2022cites this paper
• NFDD: A Dynamic Malicious Document Detection Method Without Manual Feature Dictionary

  2021cites this paper
• Detection and robustness evaluation of android malware classifiers

  2021cites this paper
• Derin Öğrenme Tabanlı Antivirüs Modellerinin Açık Kaynak Kodlu Çekişmeli Atak Kütüphaneleri Kullanılarak Atlatılması

  2021cites this paper
• A3CMal: Generating adversarial samples to force targeted misclassification by reinforcement learning

  2021cites this paper
• PDF-Malware: An Overview on Threats, Detection and Evasion Attacks

  2021cites this paper
• Cognitive Covert Traffic Synthesis Method Based on Generative Adversarial Network

  2021cites this paper
• Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers

  2021cites this paper
• Explanation-Guided Diagnosis of Machine Learning Evasion Attacks

  2021cites this paper
• Attack Transferability Against Information-Theoretic Feature Selection

  2021cites this paper
• Exploring adversarial attacks against malware classifiers in the backdoor poisoning attack

  2021cites this paper
• Robust PDF Files Forensics Using Coding Style

  2021cites this paper
• Exploitation and Sanitization of Hidden Data in PDF Files: Do Security Agencies Sanitize Their PDF Files?

  2021cites this paper
• Malware: The Never-Ending Arm Race

  2021cites this paper
• Adversarial Robustness with Non-uniform Perturbations

  2021influential citation
• Adversarial Machine Learning Attacks and Defense Methods in the Cyber Security Domain

  2021cites this paper
• A Framework for Enhancing Deep Neural Networks Against Adversarial Malware

  2021cites this paper
• A Deep-Learning Based Robust Framework Against Adversarial P.E. and Cryptojacking Malware

  2021cites this paper
• Detecting Malicious PDF Documents Using Semi-Supervised Machine Learning

  2021cites this paper
• De-CAPTCHA: A novel DFS based approach to solve CAPTCHA schemes

  2021cites this paper
• Vulnerability Evaluation of Android Malware Detectors against Adversarial Examples

  2021cites this paper
• Improving the Robustness of AI-Based Malware Detection Using Adversarial Machine Learning

  2021cites this paper
• International Journal of Electrical and Computer Engineering (IJECE)

  2021cites this paper
• Toward an Effective Black-Box Adversarial Attack on Functional JavaScript Malware against Commercial Anti-Virus

  2021cites this paper
• Toward Robust Classifiers for PDF Malware Detection

  2021cites this paper
• Jadeite: A Novel Image-Behavior-based Approach for Java Malware Detection using Deep Learning.

  2021cites this paper
• A Survey on Adversarial Attacks for Malware Analysis

  2021cites this paper
• TSS: Transformation-Specific Smoothing for Robustness Certification

  2020cites this paper
• Arms Race in Adversarial Malware Detection: A Survey

  2020influential citation
• Model Evasion Attack on Intrusion Detection Systems using Adversarial Machine Learning

  2020cites this paper
• A feature-vector generative adversarial network for evading PDF malware classifiers

  2020cites this paper
• Adversarial Machine Learning in Network Intrusion Detection Systems

  2020cites this paper
• Advanced evasion attacks and mitigations on practical ML‐based phishing website classifiers

  2020influential citation
• Protecting Decision Boundary of Machine Learning Model With Differentially Private Perturbation

  2020cites this paper
• Enhancing Deep Neural Networks Against Adversarial Malware Examples

  2020cites this paper
• Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites

  2020cites this paper
• SoK: Arms Race in Adversarial Malware Detection

  2020influential citation
• Simple Black-Box Adversarial Examples Generation with Very Few Queries

  2020cites this paper
• Mind control attack: Undermining deep learning with GPU memory exploitation

  2020cites this paper
• Adversarial Machine Learning Applied to Intrusion and Malware Scenarios: A Systematic Review

  2020cites this paper
• The Cybersecurity Dynamics Way of Thinking and Landscape

  2020cites this paper
• Virtual Sample Generation for Retraining the Malicious PDF Detection Model

  2020cites this paper
• NEURODIFF: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation

  2020cites this paper
• Incentivizing Truthfulness Through Audits in Strategic Classification

  2020cites this paper
• Black-Box Adversarial Attacks Against Deep Learning Based Malware Binaries Detection with GAN

  2020cites this paper
• The Robust Malware Detection Challenge and Greedy Random Accelerated Multi-Bit Search

  2020cites this paper
• ReluDiff: Differential Verification of Deep Neural Networks

  2020cites this paper
• Deceiving Portable Executable Malware Classifiers into Targeted Misclassification with Practical Adversarial Examples

  2020cites this paper
• Against All Odds: Winning the Defense Challenge in an Evasion Competition with Diversification

  2020cites this paper
• Machine learning in cybersecurity: a comprehensive survey

  2020cites this paper