Výsledky vyhledávání - "JOYCE, ROBERT A."

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

Autor: Joyce, Robert J., Raff, Edward, Nicholas, Charles, Holt, James

Existing research on malware classification focuses almost exclusively on two tasks: distinguishing between malicious and benign files and classifying malware by family. However, malware can be categorized according to many other types of attributes,

Externí odkaz: http://arxiv.org/abs/2310.11706

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

Autor: Eren, Maksim E., Bhattarai, Manish, Joyce, Robert J., Raff, Edward, Nicholas, Charles, Alexandrov, Boian S.

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 by prior work, however, are often not practicable due to the lack of r

Externí odkaz: http://arxiv.org/abs/2309.06643

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

Autor: Joyce, Robert J., Patel, Tirth, Nicholas, Charles, Raff, Edward

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 billion files and consume petabytes of storage, many feature extraction and

Externí odkaz: http://arxiv.org/abs/2306.06228

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Akademický článek

Evaluating public and patient involvement in interventional research–A newly developed checklist (EPPIIC).

Autor: Pyne, Elise¹ (AUTHOR), Joyce, Robert² (AUTHOR), Dwyer, Christopher P.³ (AUTHOR), Hynes, Sinéad M.² (AUTHOR) sinead.hynes@universityofgalway.ie

Publikováno v: PLoS ONE. 11/5/2024, Vol. 19 Issue 11, p1-12. 12p.

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Autor: Joyce, Robert J., Raff, Edward, Nicholas, Charles

Although groups of strongly correlated antivirus engines are known to exist, at present there is limited understanding of how or why these correlations came to be. Using a corpus of 25 million VirusTotal reports representing over a decade of antiviru

Externí odkaz: http://arxiv.org/abs/2201.00757

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MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels

Autor: Joyce, Robert J., Amlani, Dev, Nicholas, Charles, Raff, Edward

Malware family classification is a significant issue with public safety and research implications that has been hindered by the high cost of expert labels. The vast majority of corpora use noisy labeling approaches that obstruct definitive quantifica

Externí odkaz: http://arxiv.org/abs/2111.15031

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A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels

Autor: Joyce, Robert J., Raff, Edward, Nicholas, Charles

In some problem spaces, the high cost of obtaining ground truth labels necessitates use of lower quality reference datasets. It is difficult to benchmark model performance using these datasets, as evaluation results may be biased. We propose a supple

Externí odkaz: http://arxiv.org/abs/2109.11126

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