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Rakshit Agrawal

3 accepted papers

2020

Detection of Malicious Vbscript Using Static and Dynamic Analysis with Recurrent Deep Learning

ICASSP 2020accepted

Attackers have used malicious VBScripts as an important computer infection vector. In this study, we explore a system that employs both static and dynamic analysis to detect malicious VBScripts. For the static analysis, we investigate two deep recurrent models, LaMP (LSTM and Max Pooling) and CPoLS…

Cited by 0SourceScholar
2019

Attention in Recurrent Neural Networks for Ransomware Detection

ICASSP 2019accepted

Ransomware, as a specialized form of malicious software, has recently emerged as a major threat in computer security. With an ability to lock out user access to their content, recent ransomware attacks have caused severe impact at an individual and organizational level. While research in malware det…

Cited by 0SourceScholar
2018

Neural Sequential Malware Detection with Parameters

ICASSP 2018accepted

Sequential models which analyze system API calls have shown promise for detecting unknown malware. Athiwaratkun and Stokes recently proposed a two-stage model which uses a long short-term memory (LSTM) model for learning a set of features which are then input to a second classifier. Kolosnjaji et al…

Cited by 0SourceScholar