Title | Insiders Detection in the Uncertain IoD using Fuzzy Logic |
Publication Type | Conference Paper |
Year of Publication | 2022 |
Authors | Benfriha, Sihem, Labraoui, Nabila |
Conference Name | 2022 International Arab Conference on Information Technology (ACIT) |
Keywords | Behavioral sciences, Collaboration, false trust, Fuzzy logic, insiders, Internet, Internet of drones, policy-based governance, Proposals, pubcrawl, resilience, Resiliency, Scalability, security, surveillance, Traffic Control, Trust |
Abstract | Unmanned aerial vehicles (UAVs) and various network entities deployed on the ground can communicate with each other over the Internet of Drones (IoD), a network architecture designed expressly to allow communications between heterogenous entities. Drone technology has a wide range of uses, including on-demand package delivery, traffic and wild life surveillance, inspection of infrastructure and search, rescue and agriculture. However, IoD systems are vulnerable to numerous attacks, The main goal is to develop an all-encompassing security model that can be used to analyze security concerns in various UAV-based systems. With exceptional flexibility and increasing efficiency, trust management is a promising alternative to traditional detection methods. In a heterogeneous environment, it is also compatible with other security mechanisms. In this article, we present a fuzzy logic as an Insider Detection technique which calculate sensor data trust and assessing node behavior. To build confidence throughout the entire IoD, our proposal divides trust into two parts: Data trust and Node trust. This is in contrast to earlier models. Experimental results show that our solution is effective in terms of False positive ratio and Average of end-to-end delay. |
DOI | 10.1109/ACIT57182.2022.9994119 |
Citation Key | benfriha_insiders_2022 |