• Dr. Narendra Kandoi

As the number of people using the internet grows, so does the need for the secure transmission of confidential & vital data. Web apps security methods must be used in building an online web application since it has been exposed to many different types of cyberattacks. To obtain access or corrupt a legitimate online application, hackers may employ a variety of methods, including phishing sites that mislead users into providing important & private data. Due to this, the necessity to take appropriate steps to identify the risks and be informed of vulnerabilities that could impact the website and therefore the regular business flow is raised as a reaction. As a result of this research, mitigations against the most frequent web application assaults have been implemented, & web administrators now have better tools to identify assaults like phishing links the research also shows how to generate web application logs which make it easier to identify anomalous customers & determine whether their activity is out of limits, out of scope, or otherwise against the regulations. Secure coding techniques are used for mitigation, and a variety of categorization algorithms are used to identify phishing links. The created app was tested & assessed using the suggested BiLSTM against numerous assault situations, and the results demonstrate that the site had effectively mitigated these dangerous web app assaults and for detecting of phishing connections component, a contrast was made among distinct methods to determine the better ones, and superior framework gave 99.06 percent precision.

Web security, Web service application, Web attacks, Phishing detection, Classification algorithms, BiLSTM.

"A Deep Learning based Web Security Mechanism for Detection of Web Application Attacks and Phishing URLs ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.1363-1371, June-2019, Available :http://www.jetir.org/papers/JETIR1908D73.pdf

"A Deep Learning based Web Security Mechanism for Detection of Web Application Attacks and Phishing URLs ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp1363-1371, June-2019, Available at : http://www.jetir.org/papers/JETIR1908D73.pdf