  The global rise of online users and online devices has ultimately given rise
to the global internet population apart from several cybercrimes and
cyberattacks. The combination of emerging new technology and powerful
algorithms (of Artificial Intelligence, Deep Learning, and Machine Learning) is
needed to counter defense web security including attacks on several search
engines and websites. The unprecedented increase rate of cybercrime and website
attacks urged for new technology consideration to protect data and information
online. There have been recent and continuous cyberattacks on websites, web
domains with ongoing data breaches including - GitHub account hack, data leaks
on Twitter, malware in WordPress plugins, vulnerability in Tomcat server to
name just a few. We have investigated with an in-depth study apart from the
detection and analysis of two major cyberattacks (although there are many more
types): cross-site request forgery (XSRF) and cross-site scripting (XSS)
attacks. The easy identification of cyber trends and patterns with continuous
improvement is possible within the edge of machine learning and AI algorithms.
The use of machine learning algorithms would be extremely helpful to counter
(apart from detection) the XSRF and XSS attacks. We have developed the
algorithm and cyber defense framework - algoXSSF with machine learning
algorithms embedded to combat malicious attacks (including Man-in-the-Middle
attacks) on websites for detection and analysis.
