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I4CT PhD graduates, Dr. Parikshit Narendra Mahalle




Title: "Identity Management Framework for Internet of Things"

PhD Graduate: Dr. Parikshit Narendra Mahalle


The Internet of Things (IoT) is a wide-reaching network of devices, and these devices can intercommunicate and collaborate with each other to produce variety of services at any time, any place, and in any way. Maintaining access control, authentication and managing the identity of devices while they interact with other devices, services and people is an important challenge for Identity Management (IdM).The IdM presents significant challenges in the current Internet communication. These challenges are exacerbated in the IoT by the unbound number of devices and expected limitations in constrained resources. Current IdM solutions are mainly concerned with identities that are used by end users, and services to identify themselves in the networked world. However, these IdM solutions are designed by considering that significant resources are available and applicability of these IdM solutions to the resource constrained IoT needs a thorough analysis. This thesis contributes to the area of IdM for ubiquitous devices in the IoT. It initially presents the motivational factors together with the IdM problems in the context of IoT and proposes an IdM framework. Following this, it refers to the major challenges for IdM. Key milestones identified for IdM are context management, context-aware clustering with hierarchical addressing, trust management, mutual authentication and access control. All IoT devices deal with multiple contexts. Hence, context management requires context awareness and the decision theory-based device classification and framework is presented for context management. Time analysis and simulation results confirm that proposed solution is energy efficient. This context management is used to presents context-aware clustering with hierarchical addressing scheme. The proposed addressing scheme confirms the performance for throughput, end-to-end delay and energy by simulation. A relationship between trust and access control along with the trust management life cycle is introduced. This thesis presents a fuzzy approach to trust-based access control with the notion of trust levels for IdM and simulation results shows that the proposed trust management model guarantees scalability, and is energy efficient. An attack modeling and threat analysis in order to get actual view of the IoT networks is presented. In the following part of this thesis, it presents a novel scheme for authentication and access control for the IoT devices. Evaluation of proposed scheme using security protocol verification tool for different attacks, and performance analysis in terms of computational time is discussed. In addition to the above, the concept of capability for access control is presented and the implementation of identity driven capability-based access control in the IoT is discussed. Implementation results witness that the proposed access control scheme is efficient in terms of access time, and compared with the existing solutions. This thesis also presents the evaluation of the proposed scheme using security protocol verification tool at the end. Results in the view of attack resistance, energy efficiency, and other performance parameters are discussed in every contribution of this research work.

Assessment Committee:

Associate Professor Henning Olesen, Aalborg University, Denmark (chairman)
Associate Professor K.P. Subbalakshmi, Stevens Institute of Tech., USA
Associate Professor Geir M. Koien, University of Agder, Norway


Associate Professor Neeli Prasad, Aalborg University, Denmark


Associate Professor Albena Mihovska, Aalborg University, Denmark