New IEEE Topics

QUIVER: CONSISTENT OBJECT SHARING FOR EDGE SERVICES

Abstract: We present Quiver, a system that coordinates service proxies placed at the “edge” of the Internet to serve distributed clients accessing a service involving mutable objects. Quiver enables these proxies to perform consistent accesses to shared objects by migrating the objects to proxies performing operations on those objects. These migrations dramatically improve performance when operations involving an object exhibit geographic locality, since migrating this object into the vicinity of proxies hosting these operations will benefit all such operations. This system reduces the workload in the server. It performs the all operations in the proxies itself.  In this system the operations performed in  First-In-First-Out process. This system handles two process serializability and strict stabilizability for durability in the consistent object sharing . Other workloads benefit from Quiver, dispersing the computation load across the proxies and saving the costs of sending operation parameters over the wide area when these are large. Quiver also supports optimizations for single-object reads that do not involve migrating the object. We detail the protocols for implementing object operations and for accommodating the addition, involuntary disconnection, and voluntary departure of proxies. Finally, we discuss the use of Quiver to build an e-commerce application and a distributed network traffic modeling service.

MINING FILE DOWNLOADING TIME IN STOCHASTIC PEER TO PEER NETWORKS

Abstract: On-demand routing protocols use route caches to make routing decisions. Due to mobility, cached routes easily become stale. To address the cache staleness issue, prior work in DSR used heuristics with ad hoc parameters to predict the lifetime of a link or a route. However, heuristics cannot accurately estimate timeouts because topology changes are unpredictable. In this paper, we propose proactively disseminating the broken link information to the nodes that have that link in their caches. We define a new cache structure called a cache table and present a distributed cache update algorithm. Each node maintains in its cache table the information necessary for cache updates. When a link failure is detected, the algorithm notifies all reachable nodes that have cached the link in a distributed manner. The algorithm does not use any ad hoc parameters, thus making route caches fully adaptive to topology changes. We show that the algorithm outperforms DSR with path caches and with Link-Max Life, an adaptive timeout mechanism for link caches. We conclude that proactive cache updating is key to the adaptation of on-demand routing protocols to mobility. 

INTRUSION DETECTION IN HOMOGENEOUS & HETEROGENEOUS WIRELESS SENSOR NETWORKS

Abstract: Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers. In this paper, we consider this issue according to heterogeneous WSN models. Furthermore, we consider two sensing detection models: single-sensing detection and multiple-sensing detection... Our simulation results show the advantage of multiple sensor heterogeneous WSNs.

WATER MARKING RELATIONAL DATABASE USING OPTIMIZATION BASED TECHNIQUES

Abstract: Proving ownerships rights on outsourced relational database is a crucial issue in today's internet based application environments and in many content distribution applications. In this paper, we present a mechanism for proof of ownership based on the secure embedding of a robust imperceptible watermark in relational data. We formulate the watermarking of relational databases as a constrained optimization problem and discus efficient techniques to solve the optimization problem and to handle the on straints. Our watermarking technique is resilient to watermark synchronization errors because it uses a partitioning approach that does not require marker tuple. Our approach overcomes a major weakness in previously proposed watermarking techniques. Watermark decoding is based on a threshold-based technique characterized by an optimal threshold that minimizes the probability of decoding errors. We implemented a proof of concept implementation of our watermarking technique and showed by experimental results that our technique is resilient to tuple deletion, alteration and insertion attacks.

A SIGNATURE BASED INDEXING METHOD FOR EFFICIENT CONTENT BASED RETRIEVAL OF RELATIVE TEMPORAL PATTERNS

Abstract: Project aims for efficient content based retrieval process of relative temporal pattern using signature based indexing method. Rule discovery algorithms in data mining generate a large number of patterns/rules, sometimes even exceeding the size of the underlying database, with only a small fraction being of interest to the user. It is generally understood that interpreting the discovered patterns/rules to gain insight into the domain is an important phase in the knowledge discovery process. However, when there are a large number of generated rules, identifying and analyzing those that are interesting becomes difficult. We address the problem of efficiently retrieving subsets of a large collection of previously discovered temporal patterns. When processing queries on a small database of temporal patterns, sequential scanning of the patterns followed by straightforward computations of query conditions is sufficient. However, as the database grows, this procedure can be too slow, and indexes should be built to speed up the queries. The problem is to determine what types of indexes are suitable for improving the speed of queries involving the content of temporal patterns. We propose a system with signature-based indexing method to speed up content-based queries on temporal patterns And It’s used to optimize the storage and retrieval of a large collection of relative temporal patterns. The use of signature files improves the performance of temporal pattern retrieval. This retrieval system is currently being combined with visualization techniques for monitoring the behavior of a single pattern or a group of patterns over time.

TRUTH DISCOVERY WITH MULTIPLE CONFLICTING INFORMATION PROVIDERS ON WEB

Abstract: The world-wide web has become the most important information source for most of us. Unfortunately, there is no guarantee for the correctness of information on the web. Moreover, different web sites often provide conflicting in-formation on a subject, such as different specifications for the same product. In this paper we propose a new problem called Veracity that is conformity to truth, which studies how to find true facts from a large amount of conflicting information on many subjects that is provided by various web sites. We design a general framework for the Veracity problem, and invent an algorithm called Truth Finder, which utilizes the relationships between web sites and their information, i.e., a web site is trustworthy if it provides many pieces of true information, and a piece of information is likely to be true if it is provided by many trustworthy web sites. Our experiments show that Truth Finder successfully finds true facts among conflicting information, and identifies trustworthy web sites better than the popular search engines.

 

 

TRUST WORTHY COMUTING UNDER RESOURCE CONSTRAINTS WITH THE DOWN POLICY

Abstract: In this project we present a simple way to resolve a complicated network security. This is done by the following two ways. They are as follows, first is the decrypt only when necessary (DOWN) policy, which can substantially improve the ability of low-cost to protect the secrets. The DOWN policy relies on the ability to operate with fractional parts of secrets. We discuss the feasibility of extending the DOWN policy to various asymmetric and symmetric cryptographic primitives. The second is cryptographic authentication strategies which employ only symmetric cryptographic primitives, based on novel ID-based key pre-distribution schemes that demand very low complexity of operations to be performed by the secure coprocessors (ScP) and can take good advantage of the DOWN policy.

CREDIT CARD FRAUD DETECTION USING HIDDEN MARKOV MODELS

Abstract: Now a day the usage of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In this paper, we model the sequence of operations in credit card transaction processing using a Hidden Markov Model (HMM) and show how it can be used for the detection of frauds. An HMM is initially trained with the normal behavior of a cardholder. If an incoming credit card transaction is not accepted by the trained HMM with sufficiently high probability, it is considered to be fraudulent. At the same time, we try to ensure that genuine transactions are not rejected. We present detailed experimental results to show the effectiveness of our approach and compare it with other techniques available in the literature.