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20212024
most citedFedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation

8 citations · 13 across the 5 of their papers we have counts for

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7 papers · 1 filter

cs.CR2024

Living off the Analyst: Harvesting Features from Yara Rules for Malware Detection

Siddhant Gupta, Fred Lu, Andrew Barlow +5

A strategy used by malicious actors is to "live off the land," where benign systems and tools already available on a victim's systems are used and repurposed for the malicious acto…

cs.CR20231 cited

MalDICT: Benchmark Datasets on Malware Behaviors, Platforms, Exploitation, and Packers

Robert J. Joyce, Edward Raff, Charles Nicholas +1

Existing research on malware classification focuses almost exclusively on two tasks: distinguishing between malicious and benign files and classifying malware by family. However, m…

cs.CR2023

Semi-supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection

Maksim E. Eren, Manish Bhattarai, Robert J. Joyce +3

Identification of the family to which a malware specimen belongs is essential in understanding the behavior of the malware and developing mitigation strategies. Solutions proposed…

cs.CR20231 cited

A Feature Set of Small Size for the PDF Malware Detection

Ran Liu, Charles Nicholas

Machine learning (ML)-based malware detection systems are becoming increasingly important as malware threats increase and get more sophisticated. PDF files are often used as vector…

cs.CR2023

AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware Corpora

Robert J. Joyce, Tirth Patel, Charles Nicholas +1

When investigating a malicious file, searching for related files is a common task that malware analysts must perform. Given that production malware corpora may contain over a billi…

cs.CR2023

IMCDCF: An Incremental Malware Detection Approach Using Hidden Markov Models

Ran Liu, Charles Nicholas

The popularity of dynamic malware analysis has grown significantly, as it enables analysts to observe the behavior of executing samples, thereby enhancing malware detection and cla…