Improving Cellular IoT Security with Identity Federation and Anomaly Detection
| Title | Improving Cellular IoT Security with Identity Federation and Anomaly Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Santos, Bernardo, Dzogovic, Bruno, Feng, Boning, Jacot, Niels, Do, Van Thuan, Do, Thanh Van |
| Conference Name | 2020 5th International Conference on Computer and Communication Systems (ICCCS) |
| Keywords | Adaptation models, anomaly detection, Clustering algorithms, composability, Cross Layer Security, Data models, IoT security, machine learning, mobile network security, Partitioning algorithms, pubcrawl, resilience, Resiliency, security |
| Abstract | As we notice the increasing adoption of Cellular IoT solutions (smart-home, e-health, among others), there are still some security aspects that can be improved as these devices can suffer various types of attacks that can have a high-impact over our daily lives. In order to avoid this, we present a multi-front security solution that consists on a federated cross-layered authentication mechanism, as well as a machine learning platform with anomaly detection techniques for data traffic analysis as a way to study devices' behavior so it can preemptively detect attacks and minimize their impact. In this paper, we also present a proof-of-concept to illustrate the proposed solution and showcase its feasibility, as well as the discussion of future iterations that will occur for this work. |
| DOI | 10.1109/ICCCS49078.2020.9118438 |
| Citation Key | santos_improving_2020 |