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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 431 papers

TitleStatusHype
EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware ClassifiersCode2
Continuous Learning for Android Malware DetectionCode1
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-ArtCode1
Against All Odds: Winning the Defense Challenge in an Evasion Competition with DiversificationCode1
Can We Leverage Predictive Uncertainty to Detect Dataset Shift and Adversarial Examples in Android Malware Detection?Code1
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware DetectionCode1
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware DetectionCode1
Adversarial Deep Ensemble: Evasion Attacks and Defenses for Malware DetectionCode1
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified RobustnessCode1
Avast-CTU Public CAPE DatasetCode1
Show:102550
← PrevPage 1 of 44Next →

No leaderboard results yet.