@article{Shandilya_2022, title={Paradigm Shift in Adaptive Cyber Defense for Securing the Web Data: The Future Ahead}, volume={21}, url={https://journals.riverpublishers.com/index.php/JWE/article/view/12979}, DOI={10.13052/jwe1540-9589.21416}, abstractNote={<p>Web Applications are becoming more sophisticated to cater the ever-growing demand of data processing and computing. Fast technological advancements in web engineering not only facilitate data intensive and high-performance computing, but also raise serious concerns on security. Cyber threats are also ramping up at the equal pace and attackers are now more organised and equipped with high-end servers. The Data over Web needs to be more authenticated and reliable. Data Provenance-aware methods are capable of identification of data breaches and manipulation through various attacks. They analyse underlying data for the potential threats to ensure protection against various attacks. Cyber Security Practitioners are witnessing severe issues in securing the Web Data and applications as the security risks are growing rapidly due to the sudden eruption in internet usage due to the pandemic in the last few years. People and organisations are relying more on Internet and web applications than ever before. The efforts for securing the web data on such a massive scale is premature to counter the ever-evolving attack attempts. Nature-inspired Cyber Security (NICS) facilitates the development and implementation of robust defensive mechanisms which are more adaptive and highly tolerant to online malicious programs. These methods are also capable of dealing with the common algorithmic issues like incompleteness and uncertainty of information and to provide a high-level security mechanism by effectively implementing the bio-inspired methodologies like deception, and camouflage etc. This article will attempt to explore the effectiveness of NICS in web data and application security to provide smart security methods.</p>}, number={04}, journal={Journal of Web Engineering}, author={Shandilya, Shishir Kumar}, year={2022}, month={Apr.}, pages={1371–1376} }