Improving Source Location Privacy in Social Internet of Things Using a Hybrid Phantom Routing Technique
Source of Publication
Computers & Security
The amalgamation of Smart IoT and Machine learning is an emerging research area. In this context, a new trend in IoT called Social IoT has been considered for this study. The Social IoT has benefits of connectivity exhibited within the network of connected objects through the Internet of Things (IoT). It covers the entire world and provides innovative services to improve life standards, establishes novel businesses, and makes buildings and cities. Certain smart things allow the collection of ubiquitous data or traffic, which pose a threat to source location privacy. Therefore, it limits the source of the Internet of Things vision if implemented wrongly. These threats come along with some challenges, adversary profiles, and the location privacy of personal data. When they are used to monitor important assets, the attacker can easily hunt the location of these assets. However, the source location constitutes a way to prevent the adversary from finding the location of the source. This research has used a hybrid phantom method by combining the phantom node and multi-path route that improves privacy and reduces the consumption of energy. The Analytic Hierarchal Process (AHP) is used for phantom node selection, based on parameters such as energy, distance, heterogeneity, and neighbor list. The result shows the average consistency value of the parameters is 4.2 and the consistency index value is 0.066. The overall priority of the alternative node is 2.089 as compared to other nodes. The sum of the vector weight value is obtained as 4.845. The total average energy consumption is 1.211 J and the average safety period capture ratio is 59.41%. The proposed techniques overwhelmed the deficiencies in existing techniques, reduces energy consumption improves the safety period and increases the network lifetime.
Context-awareness, Privacy, Location Privacy, WSN, Internet of Things (IoT), Social Internet of Things (SIoT)
Hussain, Tariq; Yang, Bailin; Rahman, Haseeb Ur; Iqbal, Arshad; Ali, Farman; and shah, Babar, "Improving Source Location Privacy in Social Internet of Things Using a Hybrid Phantom Routing Technique" (2022). All Works. 5355.
Indexed in Scopus