6 citations · 7 across the 7 of their papers we have counts for
8 papers
PhreshPhish: A Real-World, High-Quality, Large-Scale Phishing Website Dataset and Benchmark
Thomas Dalton, Hemanth Gowda, Girish Rao +5
Phishing remains a pervasive and growing threat, inflicting heavy economic and reputational damage. While machine learning has been effective in real-time detection of phishing att…
SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis
Yansong Li, Paula Branco, Alexander M. Hoole +4
As Large Language Models (LLMs) evolve in understanding and generating code, accurately evaluating their reliability in analyzing source code vulnerabilities becomes increasingly v…
Is Score Suboptimal for Cybersecurity Models? Introducing , a Cost-Aware Alternative for Model Assessment
Manish Marwah, Asad Narayanan, Stephan Jou +2
The cost of errors related to machine learning classifiers, namely, false positives and false negatives, are not equal and are application dependent. For example, in cybersecurity…
STAN: Synthetic Network Traffic Generation with Generative Neural Models
Shengzhe Xu, Manish Marwah, Martin Arlitt +1
Deep learning models have achieved great success in recent years but progress in some domains like cybersecurity is stymied due to a paucity of realistic datasets. Organizations ar…
Attention-Based Self-Supervised Feature Learning for Security Data
I-Ta Lee, Manish Marwah, Martin Arlitt
While applications of machine learning in cyber-security have grown rapidly, most models use manually constructed features. This manual approach is error-prone and requires domain…
ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications
Xiao Zhang, Manish Marwah, I-ta Lee +2
In this paper, we introduce Anomaly Contribution Explainer or ACE, a tool to explain security anomaly detection models in terms of the model features through a regression framework…
Sparkle: Optimizing Spark for Large Memory Machines and Analytics
Mijung Kim, Jun Li, Haris Volos +7
Spark is an in-memory analytics platform that targets commodity server environments today. It relies on the Hadoop Distributed File System (HDFS) to persist intermediate checkpoint…
Modeling Scalability of Distributed Machine Learning
Alexander Ulanov, Andrey Simanovsky, Manish Marwah
Present day machine learning is computationally intensive and processes large amounts of data. It is implemented in a distributed fashion in order to address these scalability issu…