Host-Based Network Intrusion Detection via Feature Flattening and Two-stage Collaborative Classifier

no code implementations • 15 Jun 2023 • Zhiyan Chen, Murat Simsek, Burak Kantarci, Mehran Bagheri, Petar Djukic

Performance of XGBoost, which represents conventional ML, is evaluated.

Network Intrusion Detection

Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats

no code implementations • 7 Apr 2022 • Zhiyan Chen, Jinxin Liu, Yu Shen, Murat Simsek, Burak Kantarci, Hussein T. Mouftah, Petar Djukic

Advanced persistent threat (APT) is prominent for cybercriminals to compromise networks, and it is crucial to long-term and harmful characteristics.

Intrusion Detection

Generative Adversarial Network-Driven Detection of Adversarial Tasks in Mobile Crowdsensing

no code implementations • 16 Feb 2022 • Zhiyan Chen, Burak Kantarci

To this end, we propose a two-level cascading classifier that combines the GAN discriminator with a binary classifier to prevent adversarial fake tasks.

Adversarial Attack Detection Generative Adversarial Network

Federated Learning-Based Risk-Aware Decision toMitigate Fake Task Impacts on CrowdsensingPlatforms

no code implementations • 4 Jan 2021 • Zhiyan Chen, Murat Simsek, Burak Kantarci

Loss measurement considers the lost task values with respect to misclassification, where the final decision utilizes a risk-aware approach where the risk is formulated as a function of the utility loss.

Federated Learning