AI-Based Anomaly and Data Posing Classification in Mobile Crowd Sensing

• Published in: 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) pp. 225 - 229
• Main Authors: Alharam, Aysha, Otrok, Hadi, Elmedany, Wael, Bakht, Ahsan Baidar, Alkaabi, Nouf
• Format: Conference Proceeding
• Language: English
• Published: IEEE 29.09.2021
• Subjects: attacker; Crowdsensing; fault data; Focusing; Machine learning algorithms; Radio frequency; Support vector machines; System performance; Technological innovation

Nowadays, Mobile Crowd Sensing (MCS) became the popular paradigm for sensing data. MCS is vulnerable to many types of threats and faces many challenges. Trustworthiness is one of the main MCS challenges; attackers aim to inject faulty data to corrupt the system or waste its resources. Thus, MCS orga...