Results 151 to 160 of about 31,289 (240)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

A New Strategy to Design Reconfigurable Rivest–Shamir–Adleman (RSA) Accelerators

International Journal of Circuit Theory and Applications, Volume 54, Issue 6, Page 3043-3054, June 2026.
A reconfigurable FPGA‐based RSA accelerator is proposed using compression‐based modular multipliers combined with pseudomoduli arithmetic. The approach maps modular exponentiation to low‐cost arithmetic domains and applies a correction stage, achieving significant improvements in delay, operating frequency, and delay–area efficiency compared with ...
Augusto C. B. Vassoler, Gabriel B. M. Fernandes, Lucas R. Kieslich, Eduardo A. Bezerra, Hector Pettenghi   +4 more
wiley   +1 more source

Graph neural networks embedded with domain knowledge for cyber threat intelligence entity and relationship mining. [PDF]

PeerJ Comput Sci
Liu G, Lu K, Pi S.
europepmc   +1 more source

Artificial Intelligence in the Food Industry: Transforming Safety, Efficiency, and Sustainability From Farm to Fork

eFood, Volume 7, Issue 3, June 2026.
This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar, Mariyam Shahid, Manat Chaijan, Worawan Panpipat, Djilali Benabdelmoumene, Ahmed Mediani, Abdifetah Ibrahim Omar, Sabrin R. M. Ibrahim, Qudrat Ullah, Temesgen Anjulo Ageru   +9 more
wiley   +1 more source

ID-insensitive deepfake detection model based on multi-attention mechanism. [PDF]

Sci Rep
Sheng Y, Zou Z, Yu Z, Pang M, Ou W, Han W.   +5 more
europepmc   +1 more source

A Trust‐Based Random Forest Approach for Detecting Blackhole Attacks in Vehicular Ad Hoc Networks

Engineering Reports, Volume 8, Issue 6, June 2026.
A multi‐metric trust framework combined with Random Forest learning detects and mitigates blackhole attacks in VANETs. By dynamically isolating malicious vehicles, the model sustains high packet delivery, low latency, and accurate intrusion detection under severe attack conditions.
Mohammed Al‐Shabi, Anmar Abuhamdah, Fawaz Alanazi, Asma A. Alahashmi, Fuad Alsarari, Abdulbasit A. Darem   +5 more
wiley   +1 more source

Tailoring Spatial Correlations With Quantum Interference

Laser &Photonics Reviews, Volume 20, Issue 11, 5 June 2026.
Imposing spatial structure on interfering photons fundamentally reshapes their correlations. By controlling the mutual distinguishability of two photons, we write and edit these correlations, encoding information that is invisible to conventional intensity measurements and revealed only through their joint behavior.
Carlo Schiano, Bereneice Sephton, Elnaz Darsheshdar, Lorenzo Marrucci, Corrado de Lisio, Vincenzo D'Ambrosio   +5 more
wiley   +1 more source

Wiener index application in intuitionistic fuzzy rough graphs for transport network flow. [PDF]

Sci Rep
Shaik N, Shaik SB.
europepmc   +1 more source

Missing the Mark: Adoption of Watermarking for Generative AI Systems in Practice and Implications Under the New EU AI Act

Policy &Internet, Volume 18, Issue 2, June 2026.
ABSTRACT AI‐generated images have become so good in recent years that individuals often cannot distinguish them from ‘real’ images. This development, combined with the rapid spread of AI‐generated content online, creates a series of societal risks. Watermarking, a technique that involves embedding information within the content to indicate their AI ...
Bram Rijsbosch, Gijs van Dijck, Konrad Kollnig   +2 more
wiley   +1 more source

OPHash: learning of organ and pathology context-sensitive hashing for medical image retrieval. [PDF]

J Med Imaging (Bellingham)
Manna A, Sathish R, Sethuraman R, Sheet D.   +3 more
europepmc   +1 more source