Tag: cybersecurity

Researchers have developed X-URL, a character-level deep learning framework that classifies malicious URLs into four threat categories with over 98 ...

Researchers have developed a revocable, time-based attribute-based encryption scheme for cloud-assisted IoT that cuts encryption and decryption times while saving ...

A new deep learning framework can detect six types of cyber-attacks on EEG signals and reconstruct the corrupted brain data ...

A new multi-dimensional evaluation framework shows that the most accurate intrusion detection model is often not the best choice for ...

A systematic review of research from 2021 to 2025 maps how artificial intelligence is reshaping security for IoT and mobile ...

A new framework called TE-CSA aggregates embedding opportunities across the entire denoising trajectory of diffusion language models, boosting hidden-message capacity ...

Researchers in India have developed a hybrid security framework that combines swarm-optimized neural network intrusion detection with blockchain-based trust management ...

A comprehensive new review reveals how false data injection attacks, now supercharged by generative AI and coordinated cyber-physical tactics, threaten ...

A new study combines a lightweight MobileNetV2 model with edge computing to detect network attacks with 94.6 percent accuracy in ...

A new fuzzy logic-based trust management scheme called SFFTM distinguishes malicious underwater sensor nodes from honest ones hampered by unstable ...

Researchers at Guangdong University of Technology have developed DP-MVAD, a dual-path multi-view framework that disentangles trends from perturbations and fuses ...

Researchers in Turkey have built a multimodal Vision Transformer framework that converts Android app features into grayscale and QR code ...

Researchers at Donghua University have developed RFLDefense, a layer-wise defense framework that suppresses backdoor attacks in federated learning even when ...

Researchers in Algeria have combined convolutional neural networks with a Swin Transformer to detect network intrusions with up to 99.69 ...

Researchers have combined prototypical few-shot learning with adversarial training to build an IoT intrusion detection system that learns attacks from ...

A new open-source middleware called BGVD-State makes AI-assisted software security reviews replayable and evidence-gated, ensuring that findings survive handoffs between ...

Researchers at the University of Naples Federico II have built a hybrid AI system that combines ontology-driven knowledge graphs with ...

Researchers have built a transformer-based intrusion detection framework that models relationships among network traffic features and outperforms nine baseline AI ...

A JMIR analysis examines the UK National Commission's 44 recommendations for regulating healthcare AI, spanning life cycle oversight, shared safety ...

Researchers have unveiled a security framework that protects privacy-preserving, secret-shared databases against malicious data owners by combining verifiable secret sharing, ...