The current information related to security and IoT by conducting a theoretical and methodological study. It provides a detailed explanation on what is the meaning of IoT and on the various applications in IoT. It also presents the major issue of the security of IoT for applications. Moreover, the chapter discusses the metrics that define lightweight algorithms in hardware and software, and it presents the reasons for choosing blocks in lightweight algorithms and studying the architecture of those blocks. It also refers to the blocks/algorithms, both the traditional ones and the lightweight ones.

Routing Optimization in mobile ad hoc networks is an ever-demanding task. Mobile ad hoc networks are highly dynamic topology natured and hence several routing protocols meet the challenge of link quality, delay and energy conscious routing. This paper proposes a link quality, delay and energy conscious routing approach based on ant colony optimization. Based on the estimated link quality, delay and residual energy of the nearby nodes, Adaptive node stability (ANS) mechanism is mathematically modeled to make the routing strategy. LQDEARP selects the efficient node based on the ANS mechanism and sends the data packets through that node. Simulation results proved that LQDEARP reduces delay and energy consumption and increases packet delivery ratio than that of the AODV and DECRP protocol.

In the biometrics, the technologies grow day by day and the security also increased related to that technologies. The fingerprint was the most intensively researched in the field of biometrics system due to permanence and uniqueness features which made varies of different peoples. The paper addressing many stages, in addition to the primary stages of any biometrics system the fusion of unimodal system was used in order to improve the performance of the system. The double enhancement techniques were used to make the images very clear by Histogram Equalization and Fast Fourier Transformation (FFT). The feature extraction was conducted using three techniques which called Zernike Moment (ZM), Hu-Moments (Hu) and Gray-Level Co-occurrence Matrix (GLCM) that categorized to statistical and texture features. The matching between these features was performed using the Euclidean distance to find the scores matrix. Additionally, the fusion as the most modern technique was used to improve the performance of the biometrics system which performed in this work by feature level and score level fusions. The feature level fusion by using concatenation and score level fusion by using Weight sum rule strategy led to improve the performance of the system. The system was evaluated by False Accepted Rate (FAR), False Rejected Rate (FRR), Equal Error Rate (EER) and Genuine Accept Rate (GAR). The results show that, the fusion gave the most efficiency results compared with individual system. The work was tested on four datasets such as Fingerprint Verification Competition (FVC2000), (FVC2002), (FVC2004) and our department datasets which called KVK dataset. The best results were achieved by FVC2002 with maximum GAR reached to 98.45% and minimum EER of 1.54% as compared with other datasets and existing works.

Optimizing routing in mobile adhoc networks is a challenging task. Since mobile adhoc networks are highly dynamic topology natured, several routing protocols face the challenge of delay and energy conscious routing. This paper proposes a novel delay and energy conscious routing approach based on ant colony optimization. Based on the estimated delay and residual energy of the nearby nodes, "Delay and Energy Conscious Routing Protocol" (DECRP) finds the efficient node and sends the data packets through that node. Simulation results proved that DECRP reduces delay and energy consumption and increases packet delivery ratio than that of the "Adhoc On Demand Distance Vector" (AODV) protocol.

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