Wireless sensor network (WSN) is composed of large number of sensor nodes with Limited computation power, storage and communication capabilities. The wireless communication employed by sensor network facilitates eavesdropping and packet injection by an adversary. The Security of the wireless sensor networks depends on the existence of strong and efficient key distribution mechanisms.The main task is to safely distribute the shared keys to the sensor nodes with high connectivity, good resilience with minimum resource requirement. The solution to key distribution is such that, a pool of symmetric keys is chosen and a subset of the pool (key chain) is distributed to each sensor node. Two nodes that want to communicate search their key chain to determine whether they share a common key; if they don't share key in common then there may be a path, called key path, among these two nodes where each pair of neighboring nodes on this path have a key in common. In this paper we have shown a novel key pre distribution algorithm based on number theory which uses Chinese Reminder Theorem.

An automatic optic disc localization in retinal images used to screen eye related diseases like diabetic retinopathy. Many techniques are available to detect Optic Disc (OD) in high-resolution retinal images. Unfortunately, there are no efficient methods available to detect OD in low-resolution retinal images. The objective of this research paper is to develop an automated method for localization of Optic Disc in low resolution retinal images. This paper proposes a modified directional matched filter parameters of the retinal blood vessels to localize the center of optic disc. The proposed method was implemented in MATLAB and evaluated both normal and abnormal low resolution retinal images using the subset of Optic Nerve Head Segmentation Dataset (ONHSD) and the success percentage was found to be an average of 96.96% with 23seconds

Optic disc detection is an important step in retinal image screening process. This paper proposes an Automatic detection of an optic disc in retinal fundus images. The manual method graded by clinicians is a time consuming and resource-intensive process. Automatic retinal image analysis provides an immediate detection and characterization of retinal features prior to specialist inspection. This proposed a binary orientation technique to detect optic disc, which provides higher percentage of detection than the already existing methods. The method starts with converting the RGB image input into its LAB component. This image is smoothed using bilateral smoothing filter. Further, filtering is carried out using line operator. After which gray orientation and binary map orientation is carried out and then with the use of the resulting maximum image variation the area of the presence of the OD is found. The portions other than OD are blurred using 2D circular convolution. On applying mathematical steps like peak classification, concentric circles design and image difference calculation, OD is detected. The proposed method was implemented in MATLAB and tested by publically available retinal datasets such as STARE, DRIVE. The success percentage was found to be 98.34% and the comparison is done based on success percentage.

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