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Malware Detection

Malware Detection is a significant part of endpoint security including workstations, servers, cloud instances, and mobile devices. Malware Detection is used to detect and identify malicious activities caused by malware. With the increase in the variety of malware activities on CMS based websites such as malicious malware redirects on WordPress site (Aka, WordPress Malware Redirect Hack) where the site redirects to spam, being the most widespread, the need for automatic detection and classifier amplifies as well. The signature-based Malware Detection system is commonly used for existing malware that has a signature but it is not suitable for unknown malware or zero-day malware

Source: The Threat of Adversarial Attacks on Machine Learning in Network Security - A Survey

Papers

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Showing 51–100 of 431 papers

TitleStatusHype
Adapting Novelty towards Generating Antigens for Antivirus systems—0
Malware families discovery via Open-Set Recognition on Android manifest permissions—0
On the Security Risks of ML-based Malware Detection Systems: A Survey—0
Analysing Safety Risks in LLMs Fine-Tuned with Pseudo-Malicious Cyber Security Data—0
Evaluating the Robustness of Adversarial Defenses in Malware Detection SystemsCode0
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced DatasetsCode0
Dual Explanations via Subgraph Matching for Malware Detection—0
Optimized Approaches to Malware Detection: A Study of Machine Learning and Deep Learning Techniques—0
On the Consistency of GNN Explanations for Malware Detection—0
OpCode-Based Malware Classification Using Machine Learning and Deep Learning Techniques—0
Large Language Model (LLM) for Software Security: Code Analysis, Malware Analysis, Reverse Engineering—0
Malware Detection in Docker Containers: An Image is Worth a Thousand Logs—0
Imbalanced malware classification: an approach based on dynamic classifier selectionCode0
Leveraging VAE-Derived Latent Spaces for Enhanced Malware Detection with Machine Learning Classifiers—0
BERTDetect: A Neural Topic Modelling Approach for Android Malware Detection—0
Trust Under Siege: Label Spoofing Attacks against Machine Learning for Android Malware Detection—0
Malware Detection at the Edge with Lightweight LLMs: A Performance Evaluation—0
LAMD: Context-driven Android Malware Detection and Classification with LLMs—0
Malware Detection based on API callsCode0
Recent Advances in Malware Detection: Graph Learning and Explainability—0
RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization—0
Learning Temporal Invariance in Android Malware Detectors—0
Defending against Adversarial Malware Attacks on ML-based Android Malware Detection Systems—0
Integrating Explainable AI for Effective Malware Detection in Encrypted Network Traffic—0
Predicting Vulnerability to Malware Using Machine Learning Models: A Study on Microsoft Windows Machines—0
Malware Classification using a Hybrid Hidden Markov Model-Convolutional Neural Network—0
Crystal ball: From innovative attacks to attack effectiveness classifierCode0
Comprehensive Survey on Adversarial Examples in Cybersecurity: Impacts, Challenges, and Mitigation Strategies—0
Image-Based Malware Classification Using QR and Aztec Codes—0
Applications of Positive Unlabeled (PU) and Negative Unlabeled (NU) Learning in Cybersecurity—0
Explainable Malware Detection through Integrated Graph Reduction and Learning Techniques—0
Living off the Analyst: Harvesting Features from Yara Rules for Malware Detection—0
XAI and Android Malware Models—0
On the Cost of Model-Serving Frameworks: An Experimental Evaluation—0
SCORE: Syntactic Code Representations for Static Script Malware Detection—0
Unmasking the Shadows: Pinpoint the Implementations of Anti-Dynamic Analysis Techniques in Malware Using LLM—0
Metamorphic Malware Evolution: The Potential and Peril of Large Language Models—0
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems—0
Classification under strategic adversary manipulation using pessimistic bilevel optimisation—0
A Novel Reinforcement Learning Model for Post-Incident Malware Investigations—0
Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges—0
A Novel Approach to Malicious Code Detection Using CNN-BiLSTM and Feature Fusion—0
Decoding Android Malware with a Fraction of Features: An Attention-Enhanced MLP-SVM Approach—0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection with Few Samples—0
A Visualized Malware Detection Framework with CNN and Conditional GAN—0
Towards Novel Malicious Packet Recognition: A Few-Shot Learning Approach—0
Revisiting Static Feature-Based Android Malware Detection—0
Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges—0
DetectBERT: Towards Full App-Level Representation Learning to Detect Android MalwareCode0
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