CIoTA: Collaborative IoT Anomaly Detection via Blockchain

Autor:	Golomb, Tomer, Mirsky, Yisroel, Elovici, Yuval
Rok vydání:	2018
Předmět:	Computer Science - Computers and Society Computer Science - Cryptography and Security Computer Science - Distributed Parallel and Cluster Computing Computer Science - Learning
Druh dokumentu:	Working Paper
Popis:	Due to their rapid growth and deployment, Internet of things (IoT) devices have become a central aspect of our daily lives. However, they tend to have many vulnerabilities which can be exploited by an attacker. Unsupervised techniques, such as anomaly detection, can help us secure the IoT devices. However, an anomaly detection model must be trained for a long time in order to capture all benign behaviors. This approach is vulnerable to adversarial attacks since all observations are assumed to be benign while training the anomaly detection model. In this paper, we propose CIoTA, a lightweight framework that utilizes the blockchain concept to perform distributed and collaborative anomaly detection for devices with limited resources. CIoTA uses blockchain to incrementally update a trusted anomaly detection model via self-attestation and consensus among IoT devices. We evaluate CIoTA on our own distributed IoT simulation platform, which consists of 48 Raspberry Pis, to demonstrate CIoTA's ability to enhance the security of each device and the security of the network as a whole. Comment: Appears in the workshop on Decentralized IoT Security and Standards (DISS) of the Network and Distributed Systems Security Symposium (NDSS) 2018
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1803.03807 Zobrazit plný text záznamu View this record from Arxiv