Graduation Year

2018

Document Type

Dissertation

Degree

Ph.D.

Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Electrical Engineering

Major Professor

Salvatore D. Morgera, Ph.D.

Committee Member

Gangaram Ladde, Ph.D.

Committee Member

Nasir Ghani, Ph.D.

Committee Member

Christopher Passaglia, Ph.D.

Committee Member

Selcuk Kose, Ph.D.

Keywords

Human Immune System, IoT's, IDS, Negative Selection, RPL, WSN's, Danger Theory

Abstract

Network security has always been an area of priority and extensive research. Recent years have seen a considerable growth in experimentation with biologically inspired techniques. This is a consequence of our increased understanding of living systems and the application of that understanding to machines and software. The mounting complexity of telecommunications networks and the need for increasing levels of security have been the driving factor. The human body can act as a great role model for its unique abilities in protecting itself from external, foreign entities. Many abnormalities in the human body are similar to that of the attacks in wireless sensor networks (WSN). This paper presents basic ideas drawn from human immune system analogies that can help modelling a system to counter the attacks on a WSN by monitoring parameters such as energy, frequency of data transfer, data sent and received. This is implemented by exploiting two immune concepts, namely danger theory and negative selection. Danger theory aggregates the anomalies based on the weights of the anomalous parameters. The objective is to design a cooperative intrusion detection system (IDS) based on danger theory. Negative selection differentiates between normal and anomalous strings and counters the impact of malicious nodes faster than danger theory. We also explore other human immune system concepts and their adaptability to Wireless Sensor Network Security.

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