ABSTRACT
Abstract: Phishing is an aspect of identity theft that uses engineering and social paradigms to steal personal information from unsuspecting users for their selfish gain. Most attacks are in the form of luring the user into clicking a link that directs the user to a rogue page. The major target of phishing attacks are online customers of e-banking and payment service providers, and these groups suffer huge financial loss. Phishing is not all about sending spoofed mails to users as most people assume, rather it is a multifaceted techno-social issue for which there is no particular solution to end its reign. This has given rise to a series of research in this field as scholars are working towards creating more efficient anti-phish solutions by quantifying risks and degree of vulnerability of users. Most approaches to combat phishing are not able to make dynamic decisions to determine the risk rate of the website and this allows for a large number of false positive. The use of blacklists and whitelists has their limitations due to poor scalability and time constraint. Anti-phishing solutions are methods put in place to protect internet users from attacks aimed at defrauding them of their finances. Browser plug-ins have been the most recent methods adopted, though a lot of questions have been raised to question the effectiveness of these plug-ins. In this research we aim at developing an intelligent anti-phishing plug-in for e-banking, capable of detecting phishing attacks based on existing knowledge about features and patterns of phishing websites. The proposed system is developed to protect users from deceptive tricks used by phishers by giving them the ability to identify phishy or fraudulent websites. The proposed model uses fuzzy logic to define rules and assign linguistic indicators in the form of if-then rules to each phishing criteria. The approach adopted is a combination of fuzzy reasoning in quantifying dynamic and unclear phishing.......................

ABSTRACT
An ad hoc network (MANET) is a set of different types of mobile nodes these nodes are connected with each other through wireless link. MANET can be developed at any time, at any place with low cost. In MANET protocols are used to connect nodes which are not in direct range of each other. These protocols are mainly of three types i.e reactive (on demand), proactive (table driven) and hybrid routing protocols. This research effort is focused on first the comparative investigation of routing protocols under the cooperative black hole attack to create scenario and simulate and investigate the performance in terms of packet delivery ratio , average end to end delay and throughput.

ABSTRACT
Anti-patters are the defects which affect the system quality negatively. An indication of the existence of anti- patterns, in the software is known as ―Code Smell‖ which leads to the refactoring of system. Thus the maintenance becomes difficult to manage. More the number of smells more refactoring is needed. Different approaches have been identified for the detection of anti-patterns in the system. The paper aimed at investigating the impact of anti-patterns on classes and what are the certain kinds of anti-patterns that have a higher impact than others finally the results have been concluded for the future studies in open source systems. The paper is divided in to four sections in which the introduction is followed by the types of anti-patterns. Furthermore the related work has been examined carefully with a brief conclusion. Thus the paper reveals different approaches for the identification code smells in the software system. Hence the detection of smells will be helpful in providing more reliability during testing and maintenance phases by predicting anti-patterns and faults before the delivery of the product. Moreover the identification of anti-patterns will be of usage to the community of software engineers and managers for improving the software development maintenance activities.

ABSTRACT
Wireless Body Area Network (WBAN) represents a critical rising technology to resolve the problem on, in or around the patient body, but the implementation of WBAN technology is constrained by the energy consumption by them and by their shelf life. The solution may rely on employing an additional relay node that can reduce the traffic and save the energy consumption of the biosensor node. The present study addresses these issues of reduce the energy consumption by optimum design of network and routing protocol by employing heuristic-based optimization algorithms. Moth-Flame Optimization (MFO) is a search-based heuristics algorithm which updates the position of search agents. MFO has tremendous exploration capabilities and contributes significantly to global search, but it quickly becomes locked in local minima. The recently developed Inspired MFO (IMFO) has been validated by comparing the results of existing MFO for WBAN problem. It has been found that proposed IMFO algorithm outperforms other recently proposed meta-heuristics search algorithms for better relay nodes selection which is a key element for optimization of energy consumption.