Sybil Attack Prediction on Vehicle Network Using Deep Learning

Jurnal RESTI: Rekayasa Sistem dan Teknologi Informasi

article

Zulfahmi Helmi¹  Ramzi Adriman¹  Teuku Yuliar Arif¹  Hubbul Walidainy¹  Maya Fitria¹ 

[1] Universitas Syiah Kuala

关键词: VANET;    Intelligent Transportation System (ITS);    Sybil Attack;    Deep learning;   

DOI  :  10.29207/resti.v6i3.4089

来源: Ikatan Ahli Indormatika Indonesia

【 摘 要 】

Vehicular Ad Hoc Network (VANET) or vehicle network is a technology developed for autonomous vehicles in Intelligent Transportation Systems (ITS). The communication system of VANET is using a wireless network that is potentially being attacked. The Sybil attack is one of the attacks that occur by broadcasting spurious information to the nodes in the network and could cause a crippled network. The Sybil strikes the network by camouflaging themselves as a node and providing false information to nearby nodes. This study is conducted to predict the Sybil attack by analyzing the attack pattern using a deep learning algorithm. The variables exerted in this research are time, location, and traffic density. By implementing a deep learning algorithm enacting the Sybil attack pattern and combining several variables, such as time, position, and traffic density, it reaches 94% of detected Sybil attacks.

【 授权许可】

Unknown