Wireless Sensor network (WSN) is an emerging technology and has great potential to be employed in critical situations. The development of wireless sensor networks was originally motivated by military applications like battlefield surveillance. However, Wireless Sensor Networks are also used in many areas such as Industrial, Civilian, Health, Habitat Monitoring, Environmental, Military, Home and Office application areas. Detection and tracking of targets (eg. animal, vehicle) as it moves through a sensor network has become an increasingly important application for sensor networks. The key advantage of WSN is that the network can be deployed on the fly and can operate unattended, without the need for any pre-existing infrastructure and with little maintenance. The system will estimate and track the target based on the spatial differences of the target signal strength detected by the sensors at different locations. Magnetic and acoustic sensors and the signals captured by these sensors are of present interest in the study. The system is made up of three components for detecting and tracking the moving objects. The first component consists of inexpensive off-the shelf wireless sensor devices, such as MicaZ motes, capable of measuring acoustic and magnetic signals generated by vehicles. The second component is responsible for the data aggregation. The third component of the system is responsible for data fusion algorithms. This paper inspects the sensors available in the market and its strengths and weakness and also some of the vehicle detection and tracking algorithms and their classification. This work focuses the overview of each algorithm for detection and tracking and compares them based on evaluation parameters.
Biometric authentication technology is gaining much importance as it serves as a powerful alternative for traditional password based authentication. In the current scenario securing the biometric template against attack is an important issue. Fuzzy vault is a proven biometric crypto system that is used to protect biometric templates and secret data. Multi biometric systems are more secure compared to their single biometric counterparts. In this work, fuzzy vault framework is used to secure both retina and iris template. Retina and iris can be used in high security applications like access control, military applications, border security control. The proposed multimodal fuzzy vault is constructed with feature points extracted from retina and iris. Combination of retina and iris enhances the user convenience as they can be captured from the user by the same device. This work measures the security of the resultant vault by using min-entropy.
In the technology up-front world, mobile devices like smartphones and tablets are inevitable. When computing capacity and storage need of these devices are increasing tremendously, it demands the secure way of storing the data in cost efficient model. This paper describes how securely the mobile data can be stored in the remote cloud using cryptographic techniques with minimal performance degradation
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