A Lightweight Defense Mechanism against Next Generation of Phishing Emails Using Distilled Attention-Augmented BiLSTM

The current generation of large language models produces sophisticated social-engineering content that bypasses standard text screening systems in business communication platforms. Our proposed solution for mail gateway and endpoint deception detection operates in a privacy-protective manner whil...

Deep Learning for Contextualized NetFlow-Based Network Intrusion Detection: Methods, Data, Evaluation and Deployment

Network Intrusion Detection Systems NIDS have progressively shifted from signature-based techniques toward machine learning and, more recently, deep learning methods. Meanwhile, the widespread adoption of encryption has reduced payload visibility, weakening inspection pipelines that depend on...

Towards Adapting Federated and Quantum Machine Learning for Network Intrusion Detection: a Survey

This survey explores the integration of Federated Learning FL with Network Intrusion Detection Systems NIDS, with particular emphasis on deep learning and quantum machine learning approaches. FL enables collaborative model training across distributed devices while preserving data privacy-a critic...

Resource-Efficient Automatic Software Vulnerability Assessment Via Knowledge Distillation and Particle Swarm Optimization

The increasing complexity of software systems has led to a surge in cybersecurity vulnerabilities, necessitating efficient and scalable solutions for vulnerability assessment. However, the deployment of large pre-trained models in real-world scenarios is hindered by their substantial computationa...

The vulnerability of the Python commonutils.py module, a set of tools for automating function design, neural architecture search, hyperparameter tuning, and model compression of Neural Network Intelligence (NNI), allows attackers to execute arbitrary code.

The vulnerability of the Python commonUtils.py module, a set of tools for automating function design, neural network architecture search, hyperparameter tuning, and Neural Network Intelligence NNI model compression, is related to improper code generation. Exploiting this vulnerability allows an...