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Offline signature verification system is widely used as a behavioral biometric for identifying a person. This behavioral biometric trait is a challenge in designing the system that has to counter intrapersonal and interpersonal variations. In this paper, we propose a novel technique PCVOS: Principal Component Variances based Off-line Signature Verification on two critical parameters viz., the Pixel Density (PD) and the Centre of Gravity (CoG) distance. It consists of two parallel processes, namely Signature training which involves extraction of features from the samples of database and Test signature analysis which performs extraction of features from the test samples. The trained values from the database are compared with the features of the test signature using Principal Component Analysis (PCA). The PCVOS algorithm shows a notable improvement over the algorithms in [21], [22] and [23].

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Wireless Sensor Networks (WSNs) consists of a large number of tiny autonomous devices called sensors which are vulnerable to security threats. Heterogeneous Wireless Sensor Networks consists of two types of nodes L1 and L2 that employees Unbalanced Key Distribution Scheme to ensure enhanced security. In this paper, the concept of Link Strength is utilized, which determines the path to be selected for secure routing. Our Keymatches Constrained Secure Routing(KCSR) algorithm provides the flexibility to choose secure path and then route the data accordingly. In this approach, secure and stable paths are chosen for communication. Simulation results show that the proposed algorithm yields better results emphasizing security when compared with earlier works.

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