Sa2a/Fake-task-detection

This project aims to use GAN to create fake tasks and verify fake task detection performance

Fake Task Detection

This project aims to use GAN to create fake tasks and verify fake task detection performance.
Fake task attack is critical for Mobile Crowdsensing system (MCS) that aim to clog the sensing servers in the MCS platform and drain more energy from participants’ smart devices. Typically, fake tasks are created by empirical model such as CrowdSenSim tool. Recently, cyber criminals deploy more intelligent mechanisms to create attacks. Generative Adversarial Network (GAN) is one of the most powerful techniques to generate synthetic samples. GAN considers the entire data in the training dataset to create similar samples. This project aims to use GAN to create fake tasks and verify fake task detection performance.
Report:https://github.com/Sa2a/Fake-task-detection/blob/main/project%20Report.pdf