11 citations · 39 across the 8 of their papers we have counts for
9 papers
ScriptNet: Neural Static Analysis for Malicious JavaScript Detection
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald +1
Malicious scripts are an important computer infection threat vector in the wild. For web-scale processing, static analysis offers substantial computing efficiencies. We propose the…
Learning Edge Properties in Graphs from Path Aggregations
Rakshit Agrawal, Luca de Alfaro
Graph edges, along with their labels, can represent information of fundamental importance, such as links between web pages, friendship between users, the rating given by users to o…
Identifying Fake News from Twitter Sharing Data: A Large-Scale Study
Rakshit Agrawal, Luca de Alfaro, Gabriele Ballarin +4
Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applie…
A New Family of Neural Networks Provably Resistant to Adversarial Attacks
Rakshit Agrawal, Luca de Alfaro, David Helmbold
Adversarial attacks add perturbations to the input features with the intent of changing the classification produced by a machine learning system. Small perturbations can yield adve…
Robust Neural Malware Detection Models for Emulation Sequence Learning
Rakshit Agrawal, Jack W. Stokes, Mady Marinescu +1
Malicious software, or malware, presents a continuously evolving challenge in computer security. These embedded snippets of code in the form of malicious files or hidden within leg…
Neural Classification of Malicious Scripts: A study with JavaScript and VBScript
Jack W. Stokes, Rakshit Agrawal, Geoff McDonald
Malicious scripts are an important computer infection threat vector. Our analysis reveals that the two most prevalent types of malicious scripts include JavaScript and VBScript. Th…
Reputation Systems for News on Twitter: A Large-Scale Study
Luca de Alfaro, Massimo Di Pierro, Rakshit Agrawal +4
Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applie…
Learning User Intent from Action Sequences on Interactive Systems
Rakshit Agrawal, Anwar Habeeb, Chih-Hsin Hsueh
Interactive systems have taken over the web and mobile space with increasing participation from users. Applications across every marketing domain can now be accessed through mobile…
Learning From Graph Neighborhoods Using LSTMs
Rakshit Agrawal, Luca de Alfaro, Vassilis Polychronopoulos
Many prediction problems can be phrased as inferences over local neighborhoods of graphs. The graph represents the interaction between entities, and the neighborhood of each entity…