1 citations · 1 across the 9 of their papers we have counts for
9 papers
Occluded Oculus: Operationalizing Stylistic Obscurement
Robert Dilworth
What did it take for Hermes, the devout messenger of the Olympian gods, to slay Argus Panoptes, the multi-eyed giant of Greek myth? As the perfect guardian, Panoptes' legion of eve…
Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution
Robert Dilworth
In what way could a data breach involving government-issued IDs such as passports, driver's licenses, etc., rival a random voluntary disclosure on a nondescript social-media platfo…
StegoStylo: Squelching Stylometric Scrutiny through Steganographic Stitching
Robert Dilworth
Stylometry -- the identification of an author through analysis of a text's style (i.e., authorship attribution) -- serves many constructive purposes: it supports copyright and plag…
Tuning for TraceTarnish: Techniques, Trends, and Testing Tangible Traits
Robert Dilworth
In this study, we more rigorously evaluated our attack script , which leverages adversarial stylometry principles to anonymize the authorship of text-based m…
Unveiling Unicode's Unseen Underpinnings in Undermining Authorship Attribution
Robert Dilworth
When using a public communication channel -- whether formal or informal, such as commenting or posting on social media -- end users have no expectation of privacy: they compose a m…
Dark Deceptions in DHCP: Dismantling Network Defenses
Robert Dilworth
This paper explores vulnerabilities in the Dynamic Host Configuration Protocol (DHCP) and their implications on the Confidentiality, Integrity, and Availability (CIA) Triad. Throug…
Privacy Preservation through Practical Machine Unlearning
Robert Dilworth
Machine Learning models thrive on vast datasets, continuously adapting to provide accurate predictions and recommendations. However, in an era dominated by privacy concerns, Machin…
Applications of Positive Unlabeled (PU) and Negative Unlabeled (NU) Learning in Cybersecurity
Robert Dilworth, Charan Gudla
This paper explores the relatively underexplored application of Positive Unlabeled (PU) Learning and Negative Unlabeled (NU) Learning in the cybersecurity domain. While these semi-…
Harnessing PU Learning for Enhanced Cloud-based DDoS Detection: A Comparative Analysis
Robert Dilworth, Charan Gudla
This paper explores the application of Positive-Unlabeled (PU) learning for enhanced Distributed Denial-of-Service (DDoS) detection in cloud environments. Utilizing the $\texttt{BC…