most citedUN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring

17 citations · 30 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2023★ 4 cited

Evaluating Permissioned Blockchain Using Stochastic Modeling and Chaos Engineering

Shiv Sondhi, Sherif Saad, Kevin Shi +2

Blockchain and distributed ledger technologies rely on distributed consensus algorithms. In recent years many consensus algorithms and protocols have been proposed; most of them ar…

cs.LG2021★ 17 cited

UN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring

Waleed A. Yousef, Issa Traore, William Briguglio

The visualization and detection of anomalies (outliers) are of crucial importance to many fields, particularly cybersecurity. Several approaches have been proposed in these fields,…

cs.DC2021

Chaos Engineering For Understanding Consensus Algorithms Performance in Permissioned Blockchains

Shiv Sondhi, Sherif Saad, Kevin Shi +2

A critical component of any blockchain or distributed ledger technology (DLT) platform is the consensus algorithm. Blockchain consensus algorithms are the primary vehicle for the n…

cs.LG2021

Machine Learning in Precision Medicine to Preserve Privacy via Encryption

William Briguglio, Parisa Moghaddam, Waleed A. Yousef +2

Precision medicine is an emerging approach for disease treatment and prevention that delivers personalized care to individual patients by considering their genetic makeups, medical…

cs.LG2021★ 9 cited

Classifier Calibration: with application to threat scores in cybersecurity

Waleed A. Yousef, Issa Traore, William Briguglio

This paper explores the calibration of a classifier output score in binary classification problems. A calibrator is a function that maps the arbitrary classifier score, of a testin…