SOTAVerified

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

Showing 151200 of 431 papers

TitleStatusHype
Android Malware Detection Using Machine Learning on Image Patterns0
Adversary Resistant Deep Neural Networks with an Application to Malware Detection0
Adapting Novelty towards Generating Antigens for Antivirus systems0
A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms0
Machine Learning for Detecting Malware in PE Files0
Explaining Black-box Android Malware Detection0
Traffic Refinery: Cost-Aware Data Representation for Machine Learning on Network Traffic0
Android Malware Detection using Feature Ranking of Permissions0
BERTDetect: A Neural Topic Modelling Approach for Android Malware Detection0
Being Single Has Benefits. Instance Poisoning to Deceive Malware Classifiers0
Android Malware Detection using Deep Learning on API Method Sequences0
Adversarial Samples on Android Malware Detection Systems for IoT Systems0
Behavioral Malware Classification using Convolutional Recurrent Neural Networks0
Android Malware Detection Using Autoencoder0
Enhancing Malware Detection by Integrating Machine Learning with Cuckoo Sandbox0
Enhancing Enterprise Network Security: Comparing Machine-Level and Process-Level Analysis for Dynamic Malware Detection0
A Visualized Malware Detection Framework with CNN and Conditional GAN0
Android Malware Detection Based on RGB Images and Multi-feature Fusion0
ActDroid: An active learning framework for Android malware detection0
Enhanced Attacks on Defensively Distilled Deep Neural Networks0
EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning0
Empirical Quantification of Spurious Correlations in Malware Detection0
A two-steps approach to improve the performance of Android malware detectors0
A Natural Language Processing Approach to Malware Classification0
Efficient Malware Detection with Optimized Learning on High-Dimensional Features0
ATWM: Defense against adversarial malware based on adversarial training0
Efficient Malware Analysis Using Metric Embeddings0
Enhancing Robustness of Neural Networks through Fourier Stabilization0
A Transformer-Based Framework for Payload Malware Detection and Classification0
Evading Deep Learning-Based Malware Detectors via Obfuscation: A Deep Reinforcement Learning Approach0
A Natural Language Processing Approach for Instruction Set Architecture Identification0
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective0
Efficient Attack Detection in IoT Devices using Feature Engineering-Less Machine Learning0
Examining Adversarial Learning against Graph-based IoT Malware Detection Systems0
Explainable AI-based Intrusion Detection System for Industry 5.0: An Overview of the Literature, associated Challenges, the existing Solutions, and Potential Research Directions0
Explainable Artificial Intelligence (XAI) for Malware Analysis: A Survey of Techniques, Applications, and Open Challenges0
Explainable Malware Detection through Integrated Graph Reduction and Learning Techniques0
Explainable Malware Detection with Tailored Logic Explained Networks0
A Survey on the Application of Generative Adversarial Networks in Cybersecurity: Prospective, Direction and Open Research Scopes0
Explaining high-dimensional text classifiers0
Efficient and Robust Classification for Sparse Attacks0
GLSearch: Maximum Common Subgraph Detection via Learning to Search0
Effectiveness of Moving Target Defenses for Adversarial Attacks in ML-based Malware Detection0
Feature Cross-Substitution in Adversarial Classification0
A survey on practical adversarial examples for malware classifiers0
FGAM:Fast Adversarial Malware Generation Method Based on Gradient Sign0
Flexible Android Malware Detection Model based on Generative Adversarial Networks with Code Tensor0
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking0
From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy0
Analyzing Machine Learning Approaches for Online Malware Detection in Cloud0
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