activity
20182026
most citedEvaluation of an Anomaly Detector for Routers using Parameterizable Malware in an IoT Ecosystem

1 citations · 1 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CR2026

Improving Router Security using BERT

John Carter, Spiros Mancoridis, Pavlos Protopapas +2

Previous work on home router security has shown that using system calls to train a transformer-based language model built on a BERT-style encoder using contrastive learning is effe…

cs.CR2024

Towards Type Agnostic Cyber Defense Agents

Erick Galinkin, Emmanouil Pountrourakis, Spiros Mancoridis

With computing now ubiquitous across government, industry, and education, cybersecurity has become a critical component for every organization on the planet. Due to this ubiquity o…

cs.CR2024

The Price of Pessimism for Automated Defense

Erick Galinkin, Emmanouil Pountourakis, Spiros Mancoridis

The well-worn George Box aphorism ``all models are wrong, but some are useful'' is particularly salient in the cybersecurity domain, where the assumptions built into a model can ha…

cs.CR2022

Simulation of Attacker Defender Interaction in a Noisy Security Game

Erick Galinkin, Emmanouil Pountourakis, John Carter +1

In the cybersecurity setting, defenders are often at the mercy of their detection technologies and subject to the information and experiences that individual analysts have. In orde…

cs.CR2021★ 1 cited

Evaluation of an Anomaly Detector for Routers using Parameterizable Malware in an IoT Ecosystem

John Carter, Spiros Mancoridis

This work explores the evaluation of a machine learning anomaly detector using custom-made parameterizable malware in an Internet of Things (IoT) Ecosystem. It is assumed that the…

cs.CR2021

Evaluating Attacker Risk Behavior in an Internet of Things Ecosystem

Erick Galinkin, John Carter, Spiros Mancoridis

In cybersecurity, attackers range from brash, unsophisticated script kiddies and cybercriminals to stealthy, patient advanced persistent threats. When modeling these attackers, we…

cs.CR2018

Behavioral Malware Classification using Convolutional Recurrent Neural Networks

Bander Alsulami, Spiros Mancoridis

Behavioral malware detection aims to improve on the performance of static signature-based techniques used by anti-virus systems, which are less effective against modern polymorphic…