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 7180 of 431 papers

TitleStatusHype
DeepXplore: Automated Whitebox Testing of Deep Learning SystemsCode0
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced DatasetsCode0
Adversarially Robust Learning with Optimal Transport Regularized DivergencesCode0
Arhuaco: Deep Learning and Isolation Based Security for Distributed High-Throughput ComputingCode0
DetectBERT: Towards Full App-Level Representation Learning to Detect Android MalwareCode0
Deep learning at the shallow end: Malware classification for non-domain expertsCode0
Classification with Costly Features in Hierarchical Deep SetsCode0
DeepSign: Deep Learning for Automatic Malware Signature Generation and ClassificationCode0
Convolutional Neural Network for Classification of Malware Assembly CodeCode0
Black-Box Attacks against RNN based Malware Detection AlgorithmsCode0
Show:102550
← PrevPage 8 of 44Next →

No leaderboard results yet.