INTELLIGENT PHISHING WEBSITE DETECTION AND PREVENTION SYSTEM BY USING LINK GUARD ALGORITHM

Phishing is a new type of network attack where the attacker creates a replica of an existing Web page to fool users (e.g., by using specially designed e-mails or instant messages) into submitting personal, financial, or password data to what they think is their service provides’ Web site. In this project, we proposed a new end-host based anti-phishing algorithm, which we call Link Guard, by utilizing the generic characteristics of the hyperlinks in phishing attacks. These characteristics are derived by analyzing the phishing data archive provided by the Anti-Phishing Working Group (APWG). Because it is based on the generic characteristics of phishing attacks, Link Guard can detect not only known but also unknown phishing attacks. We have implemented LinkGuard in Windows XP. Our experiments verified that LinkGuard is effective to detect and prevent both known and unknown phishing attacks with minimal false negatives. LinkGuard successfully detects 195 out of the 203 phishing attacks. Our experiments also showed that LinkGuard is light weighted and can detect and prevent phishing attacks in real time. Index

FEATURE SELECTION AND CLASSIFICATION OF INTRUSION DETECTION SYSTEM USING ROUGH SET

With the expansion of computer network there is a challenge to compete with the intruders who can easily break into the system. So it becomes a necessity to device systems or algorithms that can not only detect intrusion but can also improve the detection rate. In this paper we propose an intrusion detection system that uses rough set theory for feature selection, which is extraction of relevant attributes from the entire set of attributes describing a data packet and used the same theory to classify the packet if it is normal or an attack. After the simplification of the discernibility matrix we were to select or reduce the features. We have used Rosetta tool to obtain the reducts and classification rules. NSL KDD dataset is used as training set and is provided to Rosetta to obtain the classification rules.

PUBLISHING SEARCH LOGS PRIVACY GUARANTEE FOR USER SENSITIVE INFORMATION

Search Engine companies maintain the search log to store the histories of their users search queries. These search logs are gold mines for researchers. However, Search engine companies take care of publishing search log in order to provide privacy for user’s sensitive information. In this paper we analyze algorithm for publishing frequent keywords, Queries, and Clicks of a search log. Before Zealous algorithm, we discuss how different variants of anonymity failed to provide good utility (publishing frequent items) and strong privacy for the search logs. And also this paper includes how zealous algorithm provides good utility and strong privacy for publishing search logs.

EFFECTIVE EVENT DERIVATION OF UNCERTAIN EVENTS IN RULE-BASED SYSTEMS

There is a growing need for systems that react automatically to events. While some events are generated externally and deliver data across distributed systems, others need to be derived by the system itself based on available information. Unpredictability of future events which influence the outcome of the present decisions but have not yet occurred and no one can predict what they will be like. In this process, it finds out the uncertain events using the rules. Here it uses the Event Instance Data for find out the efficient process. This performs the two mechanisms are select ability is for calculation of the exact probability space and sampling techniques. For this process it uses the efficient algorithms that are calculate selectable EID and Rule stamp algorithm. In this paper, we also emphasized the important role that event select ability plays in uncertain event derivation. We demonstrated not only that it plays a significant semantic role, but also, that the proper usage of select ability can significantly improve performance, and result in a framework that is much more suited to applications with a high event throughput. This system provides the better results and provides the efficient process.

METHOD TO ACHIEVE SECURITY AND STORAGE SERVICES IN CLOUD COMPUTING

Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users ‘physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphism token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks)

HELIANTHUS - SMART SOLAR PANEL

The paper outlines an application of smart solar “photovoltaic” power generation. Solar panels are typically in fixed position. They're limited in their energy-generating ability because they cannot consistently take full advantage of maximum sunlight. For more effective solar energy system, the solar panel should be able to align with sunlight as it changes during a given day. The present paper examines the design advantages of creating an intelligent solar tracking system like a helianthus flower using microcontroller based embedded system.

INTELLIGENT VEHICLE PARKING USING FUZZY-NEURAL NETWORKS

This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzyneural controller presents good positioning and tracking performance for different types of desired trajectories. It was verified by computer simulation as well as experimentally using a laboratory-scale car-like robot model.

DESIGN SPACE EXPLORATION AND OPTIMIZATION OF SUPER SCALAR PROCESSOR

Designing a microprocessor involves determining the optimal microarchitecture for a given objective function and a given set of constraints. Superscalar processing is the latest in along series of innovations aimed at producing ever-faster microprocessors. By exploiting instruction-level parallelism, superscalar processors[1] are capable of executing more than one instruction in a clock cycle.The architectural design of super scalar processor involves a lot of trade off issues when selecting parameter values for instruction level parallelism.The use of critical quantitative analysis based upon the Simple Scalar simulations is necessary to select optimal parameter values for the processor aimed at specific target environment. This paper aims at finding optimal values for the super scalar processor and determines which processor parameters have the greatest impact on the simulated execution time.

Evaluation of Two Terminal Reliability of Fault-tolerant Multistage Interconnection Networks

This paper iOntroduces a new method based on multi-decomposition for predicting the two terminal reliability of fault-tolerant multistage interconnection networks. The method is well supported by an efficient algorithm which runs polynomially. The method is well illustrated by taking a network consists of eight nodes and twelve links as an example. The proposed method is found to be simple, general and efficient and thus is as such applicable to all types of fault-tolerant multistage interconnection networks. The results show this method provides a greater accurate probability when applied on fault-tolerant multistage interconnection networks. Reliability of two important MINs are evaluated by using the proposed method.

AN EFFICIENT TASK SCHEDULING IN DISTRIBUTED COMPUTING SYSTEMS BY IMPROVED GENETIC ALGORITHM

Task Scheduling problem for heterogeneous systems is concerned with arranging the various tasks to be executed on various processors of a system so that computing resources are utilized most effectively. Parallel processing refers to the concept of speeding-up the execution of a task by dividing the task into multiple fragments that can execute simultaneously, each on its own processor i.e. it is the simultaneous processing of the task on two or more processors in order to obtain faster results. It can be effectively used for tasks that involve a large number of calculations, have time constraints and can be divided into a number of smaller tasks. The scheduling problem deals with the optimal assignment of a set of tasks onto parallel multiprocessor system and orders their execution so that the total completion time is minimized. An Optimal scheduling of parallel tasks with some precedence relationship, onto a parallel machine is known to be NP-complete. This precedence relationship among tasks can be represented as Directed Acyclic Graph (DAG). In this paper, a scheduling algorithm has been proposed to schedule DAG tasks on Heterogeneous processor which uses Genetic algorithm to get optimal schedule. The scheduling problem is also considered. This study includes a search for an optimal mapping of the task and their sequence of execution and also search for an optimal configuration of the parallel system. An approach for the simultaneous optimization of all these three components of scheduling method using genetic algorithm is presented and its performance is evaluated in comparison with the Min-Min and Max-Min scheduling methods.