Results 211 to 220 of about 1,209,773 (317)

Robustness to Adversarial Attacks.

Mohsen H. Alhazmi (22756263)
openalex   +1 more source

Securing the Unseen: A Comprehensive Exploration Review of AI‐Powered Models for Zero‐Day Attack Detection

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam, Nuruzzaman Faruqui, Akm Azad, Mohammad Ali Moni   +3 more
wiley   +1 more source

FP-ZOO: Fast Patch-Based Zeroth Order Optimization for Black-Box Adversarial Attacks on Vision Models. [PDF]

Sensors (Basel)
Seo J, Jeon S.
europepmc   +1 more source

Enhancing Cyber Security of LoRaWAN Gateways under Adversarial Attacks. [PDF]

Sensors (Basel), 2022
Mohamed A, Wang F, Butun I, Qadir J, Lagerström R, Gastaldo P, Caviglia DD.   +6 more
europepmc   +1 more source

A cybersecurity risk analysis framework for systems with artificial intelligence components

International Transactions in Operational Research, Volume 33, Issue 2, Page 798-825, March 2026.
Abstract The introduction of the European Union Artificial Intelligence (AI) Act, the NIST AI Risk Management Framework, and related international norms and policy documents demand a better understanding and implementation of novel risk analysis issues when facing systems with AI components: dealing with new AI‐related impacts; incorporating AI‐based ...
J.M. Camacho, A. Couce‐Vieira, D. Arroyo, D.R. Insua   +3 more
wiley   +1 more source

Adversarial attacks dataset for low light image enhancement. [PDF]

Data Brief
Martinez A, Olague M, Olague G, Hernandez E, Lopez-Arredondo JC.   +4 more
europepmc   +1 more source

A Word-Granular Adversarial Attacks Framework for Causal Event Extraction. [PDF]

Entropy (Basel), 2022
Zhao Y, Zuo W, Liang S, Yuan X, Zhang Y, Zuo X.   +5 more
europepmc   +1 more source

Deep learning adversarial attacks and defenses in autonomous vehicles: a systematic literature review from a safety perspective [PDF]

Ahmed Dawod Mohammed Ibrahum, Manzoor Hussain, Jang‐Eui Hong   +2 more
openalex   +1 more source

Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks [PDF]

, 2019
David Stutz, Matthias Hein, Bernt Schiele   +2 more
openalex   +1 more source

Pathways to honesty: Exploring the ecological desistance of atypical lying features

Journal of Research on Adolescence, Volume 36, Issue 1, March 2026.
Abstract Atypical lying (i.e., dishonesty that is excessive, impulsive, for fun, or lacks clear motive) may signal broader developmental risks. This study examined whether baseline levels and changes in parenting, peer, and individual factors were associated with trajectories of atypical lying from ages 14 to 26.
Romain Decrop, Emma Rodgers, Scarlet Cho, Alyssa Briones, Jordan Beardslee, Elizabeth Cauffman   +5 more
wiley   +1 more source