Abstract:
The Internet of Things (IoT) has become pervasive, encompassing various aspects of life. A wide array of devices is interconnected within IoT networks, collecting data, communicating usage information, and performing tasks. However, as the number of IoT devices grows exponentially, ensuring the secure preservation of critical data has emerged as a significant challenge. With the increasing connectivity of everything to the global Internet, security and privacy concerns such as data integrity, confidentiality, and authenticity are being exposed. Trust is vital in safeguarding user data's privacy, availability, and security. To establish reliable connections among IoT nodes, it is crucial to securely develop trust between devices, enabling confidential packet transmission to their destinations. Several solutions have been proposed to address trust issues in the IoT environment. These solutions encompass reputation mechanisms, hierarchical models, fuzzy techniques, social networking, routing strategies, and historical behavior analysis of nodes. In response to these security challenges, our research proposes a novel approach that combines multiple parameters for calculating trust. These parameters include node honesty, proximity to other nodes, and frequency of interactions. By intelligently predicting threshold values for each node using machine learning algorithms, our methodology aims to identify trustworthy nodes across the network. This prevents packet forwarding to compromised or untrustworthy nodes. To evaluate the effectiveness of our proposed approach, we utilize the Ns-2/3 network simulator and set trust computation range values between 0 and 1. The evaluation results demonstrate that our approach achieves enhanced security and trustworthiness compared to traditional methods. In summary, our research addresses the pressing security challenges in IoT by proposing a methodology that integrates various trust calculation parameters and employs machine learning algorithms for intelligent node trust prediction. The evaluation using the Ns-2/3 network simulator confirms the effectiveness of our approach in enhancing security and trustworthiness within IoT networks, surpassing traditional methods.
Page(s):
341-341
DOI:
DOI not available
Published:
Journal: Abstract Book on International Conference on Food and Applied Sciences (ICFAS-23) 3-5 August 23, Volume: 0, Issue: 0, Year: 2023
Keywords:
Security
,
Trust
,
Confidentiality
,
trustworthiness