A Novel Analysis of Advanced Visual Cryptography Techniques for Providing Security Against Web Attacks Using Support Vector Machine Technique

Abstract

In today’s internet applications such as some real time application services like core banking and other public service oriented application have been major issue in authentication of user specification. To perform online dictionary attacks, passwords have been used for security and authentication mechanism. Present days, hacking of databases on web oriented applications is unavoidable to access them easily. Data maintenance is a complex task in internet applications. To solve these type of problems in internet applications, in this paper, we proposed a novel Integrated and Dynamic CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) (I&D CAPTCHA), which is extension version of existing CAPTCHA that valuated third party human attacks in internet applications based Visual Cryptography approach to discuss about authentication problem in real time applications. There is more number of methods presented for security in advanced pictures for insurance from inventive uninvolved or dynamic assaults in system correspondence environment. Like insightful Visual Cryptographic (VC) is a cutting edge strategy, which is utilized to mystery picture safely impart furthermore keep up to privacy. To proceed with difficulties of security in advanced picture information sharing, so in this paper we break down various VC security instruments for computerized picture information offering to regard tomystery information secrecy. Our examination give effective security answers for relative mystery advanced picture information imparting to correspondence progressively environment. Security aspects are main concepts in present days because of increasing statistical data storage. In Artificial Intelligence (AI) oriented applications, it is very difficult in terms of protection to increasing new aspects in real time world. So we also plan a Novel and Advanced Security system to enable solution for basic AI problems in this paper. This framework mainly works based on Captcha as visual security passwords (CaRP); it is two way communication plan which means that, it is the combination of Captcha and visual security plan. Our approach mainly worked with image security with respect to selection of passwords based on random way. In this paper, we also propose AMODS, an adaptive system that periodically updates the detection model to detect the latest unknown attacks. We also propose an adaptive learning strategy, called SVM HYBRID, leveraged by our system to minimize manual work. Our system out performs existing web attack detectionmethods, with an F-value of 94.79% and FP rate of 0.09%. The total number of malicious queries obtained by SVM HYBRID is 2.78 times that by the popular Support Vector Machine Adaptive Learning (SVMAL) method. The malicious queries obtained can be used to update the Web Application Firewall (WAF) signature library.