Perception, performance, and detectability of conversational artificial intelligence across 32 university courses

no code implementations • 7 May 2023 • Hazem Ibrahim, Fengyuan Liu, Rohail Asim, Balaraju Battu, Sidahmed Benabderrahmane, Bashar Alhafni, Wifag Adnan, Tuka Alhanai, Bedoor AlShebli, Riyadh Baghdadi, Jocelyn J. Bélanger, Elena Beretta, Kemal Celik, Moumena Chaqfeh, Mohammed F. Daqaq, Zaynab El Bernoussi, Daryl Fougnie, Borja Garcia de Soto, Alberto Gandolfi, Andras Gyorgy, Nizar Habash, J. Andrew Harris, Aaron Kaufman, Lefteris Kirousis, Korhan Kocak, Kangsan Lee, Seungah S. Lee, Samreen Malik, Michail Maniatakos, David Melcher, Azzam Mourad, Minsu Park, Mahmoud Rasras, Alicja Reuben, Dania Zantout, Nancy W. Gleason, Kinga Makovi, Talal Rahwan, Yasir Zaki

Moreover, current AI-text classifiers cannot reliably detect ChatGPT's use in school work, due to their propensity to classify human-written answers as AI-generated, as well as the ease with which AI-generated text can be edited to evade detection.

A Rule Mining-Based Advanced Persistent Threats Detection System

1 code implementation • 20 May 2021 • Sidahmed Benabderrahmane, Ghita Berrada, James Cheney, Petko Valtchev

Advanced persistent threats (APT) are stealthy cyber-attacks that are aimed at stealing valuable information from target organizations and tend to extend in time.

Blocking

Categorical anomaly detection in heterogeneous data using minimum description length clustering

no code implementations • 14 Jun 2020 • James Cheney, Xavier Gombau, Ghita Berrada, Sidahmed Benabderrahmane

Fast and effective unsupervised anomaly detection algorithms have been proposed for categorical data based on the minimum description length (MDL) principle.

Clustering Unsupervised Anomaly Detection

A baseline for unsupervised advanced persistent threat detection in system-level provenance

1 code implementation • 17 Jun 2019 • Ghita Berrada, Sidahmed Benabderrahmane, James Cheney, William Maxwell, Himan Mookherjee, Alec Theriault, Ryan Wright

Advanced persistent threats (APT) are stealthy, sophisticated, and unpredictable cyberattacks that can steal intellectual property, damage critical infrastructure, or cause millions of dollars in damage.

Cryptography and Security