State of The Art in WBAN Security & Open Research Issues

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TCP performance over end-to-end rate control and stochastic available capacity

Motivated by TCP over end-to-end ABR, we study the performance of adaptive window congestion control, when it operates over an explicit feedback rate-control mechanism, in a situation in which the bandwidth available to the elastic traffic is stochastically time varying. It is assumed that the sender and receiver of the adaptive window protocol are colocated with the rate-control endpoints. The objective of the study is to understand if the interaction of the rate-control loop and the window-control loop is beneficial for end-to-end throughput, and how the parameters of the problem (propagation delay, bottleneck buffers, and rate of variation of the available bottleneck bandwidth) affect the performance.The available bottleneck bandwidth is modeled as a two-state Markov chain. We develop an analysis that explicitly models the bottleneck buffers, the delayed explicit rate feedback, and TCP's adaptive window mechanism. The analysis, however, applies only when the variations in the available bandwidth occur over periods larger than the round-trip delay. For fast variations of the bottleneck bandwidth, we provide results from a simulation on a TCP testbed that uses Linux TCP code, and a simulation/emulation of the network model inside the Linux kernel.We find that, over end-to-end ABR, the performance of TCP improves significantly if the network bottleneck bandwidth variations are slow as compared to the round-trip propagation delay. Further, we find that TCP over ABR is relatively insensitive to bottleneck buffer size. These results are for a short-term average link capacity feedback at the ABR level (INSTCAP). We use the testbed to study EFFCAP feedback, which is motivated by the notion of the effective capacity of the bottleneck link. We find that EFFCAP feedback is adaptive to the rate of bandwidth variations at the bottleneck link, and thus yields good performance (as compared to INSTCAP) over a wide range of the rate of bottleneck bandwidth variation. Finally, we study if TCP over ABR, with EFFCAP feedback, provides throughput fairness even if the connections have different round-trip propagation delays

Born to be Alive: A Role for the BCL-2 Family in Melanoma Tumor Cell Survival, Apoptosis, and Treatment

The global incidence of melanoma has dramatically increased during the recent decades, yet the advancement of primary and adjuvant therapies has not kept a similar pace. The development of melanoma is often centered on cellular signaling that hyper-activates survival pathways, while inducing a concomitant blockade to cell death. Aberrations in cell death signaling not only promote tumor survival and enhanced metastatic potential, but also create resistance to anti-tumor strategies. Chemotherapeutic agents target melanoma tumor cells by inducing a form of cell death called apoptosis, which is governed by the BCL-2 family of proteins. The BCL-2 family is comprised of anti-apoptotic proteins (e.g., BCL-2, BCL-xL, and MCL-1) and pro-apoptotic proteins (e.g., BAK, BAX, and BIM), and their coordinated regulation and function are essential for optimal responses to chemotherapeutics. Here we will discuss what is currently known about the mechanisms of BCL-2 family function with a focus on the signaling pathways that maintain melanoma tumor cell survival. Importantly, we will critically evaluate the literature regarding how chemotherapeutic strategies directly impact on BCL-2 family function and offer several suggestions for future regimens to target melanoma and enhance patient survival

Cyber Forensics in Cloud Computing

Cloud computing is a broad and diverse phenomenon; much of the growth represents a transfer of traditional IT services to a new cloud model. Cloud computing is anticipated to be one of the most transformative technologies in the history of computing. Cloud organizations, including the providers and customers of cloud services, have yet to establish a well-defined forensic capability. Without this they are unable to ensure the robustness and suitability of their services to support investigations of criminal activity. In this paper, we take the first steps towards defining the new area of cloud forensics, and analyze its challenges and opportunities. Keywords: Cloud Computing, Software as a Service, Platform as a Service, Infrastructure as a Service, Signature-based Analysis, Behavior-based Analysis, Cloud Forensics

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

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

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