State of The Art in WBAN Security & Open Research Issues

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Mitigation of Single Point Failure and Successful Data Recovery in Wireless Body Area Network

A wireless body area network can play a significant role in monitoring the physiological signs of human body and hence can be applied in various application areas such as battlefield, sports, hospital etc. As WBAN deals with vital signs of human body, network reliability is of utmost importance. The reliability of WBAN is the ability of the network to be connected even during node failures and malicious attacks. In this paper, we have proposed an efficient and highly reliable wireless body area network (WBAN) with a combination of cooperated network coding that can provide increased throughput and deal with single point of failure. Cooperated network coding in real time application areas of wireless body area network is an efficient way to deal with packet loss, single point of failure, data recovery and reduced latency due to retransmission of information. In this paper, we have proposed a many-to-many cooperated network coding to support multiple sources, multiple relays and multiple sinks or destinations in WBAN

AN ENERGY EFFICIENT CLUSTER-HEAD FORMATION AND MEDIUM ACCESS TECHNIQUE IN MULTI-HOP WBAN

In the present era, Wireless Body Area Network (WBAN) has emerged as one of the most desired healthcare technologies. Along with healthcare, its application area includes sports, entertainment, battlefield etc. Any time to time posture and position changes of human beings result in changes in node connectivity of the WBAN associated with them. To cope with this situation, the data cluster heads should be changed and adjusted as per the distance between the various sensor nodes. Also, the cluster head must be accessible to all neighbouring nodes to ensure that each node transfers its data packet to the cluster head. This ultimately increases the reliability of WBAN. Energy efficiency is another most important requirement in WBAN to increase the network lifetime. Selection of cluster head plays a crucial role in improving energy efficiency. In this paper, an energy efficient, integrated cluster formation and cluster head selection method where cluster head can be selected dynamically to achieve high fault tolerance is presented. This work has relevance to multi-hop WBAN environment as cluster-based topology involves minimum two hop communication between sensor node and the coordinator node. The proposed technique involves selection by the cluster head the frames having least interference. Achieving energy efficiency without any data discrimination, considering probabilistic inter-cluster interference as one of the constraints in cluster creation for avoiding collision, elimination of hard clusters, and incorporation of dynamic channel allocation scheme in CH selection for efficient utilization of the bandwidth and reduction in adverse effects of clustering are the main beneficial features of the technique

IRAbMC: Image Recommendation with Absorbing Markov Chain

Image Recommendation is an important feature for search engine as tremendous amount images are available online. It is necessary to retrieve relevant images to meet user's requirement. In this paper, we present an algorithm Image Recommendation with Absorbing Markov Chain (IRAbMC) to retrieve relevant images for user input query. Images are ranked by calculating keyword relevance probability between annotated keywords from log and keywords of user input query. Absorbing Markov chain is used to calculate keyword relevance. Experiments results show that the IRAbMC algorithm outperforms Markovian Semantic Indexing (MSI) method with improved relevance score of retrieved ranked images

Query Click and Text Similarity Graph for Query Suggestions

Query suggestion is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of suggestions like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the suggestions. If we model the data into various kinds of graphs then we can build a general method for any suggestions. In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and (2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users’ need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product suggestion

IRHDF: Iris Recognition using Hybrid Domain Features

Iris Biometric is a unique physiological noninvasive trait of human beings that remains stable over a person's life. In this paper, we propose an Iris Recognition using Hybrid Domain Features (IRHDF) as Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP). An eye is preprocessed to extract the complex wavelet features to obtain the Region of Interest (ROI) area from an iris. OLBP is further applied on ROI to generate features of magnitude coefficients. Resultant features are generated by fusion of DTCWT and OLBP using arithmetic addition. Euclidean Distance (ED) is used to match the test iris image with database iris features to recognize a person. We observe that the values of Equal Error Rate (EER) and Total Success Rate (TSR) are better than in [7]

SALR: Secure adaptive load-balancing routing in service oriented wireless sensor networks

Congestion control and secure data transfer are the major factors that enhance the efficiency of Service Oriented Wireless Sensor Networks. It is desirable to modify the routing and security schemes adaptively in order to respond effectively to the rapidly changing Network State. Adding more complexities to the routing and security schemes increases the end-to-end delay which is not acceptable in Service Oriented WSNs which are mostly in real time. We propose an algorithm Secure Adaptive Load-Balancing Routing (SALR) protocol, in which the routing decision is taken at every hop considering the unforeseen changes in the network. Multipath selection based on Node Strength is done at every hop to decide the most secure and least congested route. The system predicts the best route rather than running the congestion detection and security schemes repeatedly. Simulation results show that security and latency performance is better than reported protocols

WCTFR : WRAPPING CURVELET TRANSFORM BASED FACE RECOGNITION

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Wrapping Curvelet Transform based Face Recognition (WCTFR). The Wrapping Curvelet Transform (WCT) is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT features of each image. The test image WCT features are compared with database images using Euclidean Distance (ED) to compute Equal Error Rate (EER) and True Success Rate (TSR). The proposed algorithm with WCT performs better than Curvelet Transform algorithms used in [1], [10] and [11]

IRDO: Iris Recognition by Fusion of DTCWT and OLBP

Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using Fusion of Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP) Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI) area from an iris. The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP using arithmetic addition. The Euclidean Distance (ED) is used to compare test iris with database iris features to identify a person. It is observed that the values of Total Success Rate (TSR) and Equal Error Rate (EER) are better in the case of proposed IRDO compared to the state-of-the art technique

OSPCV: Off-line Signature Verification using Principal Component Variances

Signature verification system is always the most sought after biometric verification system. Being a behavioral biometric feature which can always be imitated, the researcher faces a challenge in designing such a system, which has to counter intrapersonal and interpersonal variations. The paper presents a comprehensive way of off-line signature verification based on two features namely, the pixel density and the centre of gravity distance. The data processing consists of two parallel processes namely Signature training and Test signature analysis. Signature training involves extraction of features from the samples of database and Test signature analysis involves extraction of features from test signature and it’s comparison with those of trained values from database. The features are analyzed using Principal Component Analysis (PCA). The proposed work provides a feasible result and a notable improvement over the existing systems