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20172026
most citedPythia: A Suite for Analyzing Large Language Models Across Training and Scaling

165 citations · 454 across the 46 of their papers we have counts for

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16 papers · 1 filter

cs.CR20253 cited

ClarAVy: A Tool for Scalable and Accurate Malware Family Labeling

Robert J. Joyce, Derek Everett, Maya Fuchs +2

Determining the family to which a malicious file belongs is an essential component of cyberattack investigation, attribution, and remediation. Performing this task manually is time…

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.CR2024

Assemblage: Automatic Binary Dataset Construction for Machine Learning

Chang Liu, Rebecca Saul, Yihao Sun +5

Binary code is pervasive, and binary analysis is a key task in reverse engineering, malware classification, and vulnerability discovery. Unfortunately, while there exist large corp…

cs.CR2024

Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection

Mohammad Mahmudul Alam, Edward Raff, Stella Biderman +2

Malware detection is an interesting and valuable domain to work in because it has significant real-world impact and unique machine-learning challenges. We investigate existing long…

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…