Eligibility criteria for applying for the course:

Third Year UG/Final year UG/PG students of CSE/IT/ISE/ECE

Brief introduction of the topic:

Every day cyber attacks are evolving and getting more sophisticated. Taking advantage of the prevailing situation due to COVID-19 pandemic, cyber criminals have become more active as evidenced by recent ransomware and DoS attacks on major institutions. Since the attacks become very sophisticated enough to bypass the typical security measures enforced by firewalls and anti-virus systems, it is imperative to think beyond them and adapt to the growing challenges in cybersecurity. Intel recently reported that after the recent incident at the Indo-China border, China is planning cyber attacks on India’s Critical Infrastructure Systems. A Cyber war has the potential to cause more damage to the economy of the target nation than the war between the armed forces. Thus it is expected that we can witness more such cyberwars from the neighbouring nations as it is not easy to attribute the attack to any nation.

Artificial Intelligence, in particular deep learning, is spreading its wings as it has the potential to offer betterment to the existing solutions in almost every technology. Critical Information Infrastructure Systems built around technologies like AI/ML is rapidly increasing and therefore specialized cybersecurity measures must be adopted to safeguard both data as well as the systems providing the critical services. We have been witnessing in recent years that cybersecurity could be the killer application for deep learning. This course is intended to introduce the participants to the foundations of deep learning and its implications towards cybersecurity. After the course, the participants would get exposure to the various advanced topics in the field of cybersecurity and machine learning and would be motivated to pursue their career in these domains.

According to research by Symantec, nearly 8 out of 10 individuals are subject to the different types of harassment or bullying in India. Out of these, around 63?ced online abuses and insults, and 59% were subject to false rumours and hateful comments. Cyberbullying can frequently occur in social media, chat rooms, and gaming platforms where people can view and participate in the sharing of content. NLP techniques adapted for analyzing and identifying such comments in social media. There are language-specific challenges to handle the comments in Indian languages. Most of the existing Natural Language Processing tools have been developed for or trained on the general text. So the available models fail miserably on user-generated content in social media. The proposed Offensive and Hate Speech Detection models protect the women in social networks against the hateful, nasty comments. Automatic detection of abnormal messages allows for large-scale social media monitoring and reduces manual monitoring efforts on social media.

Target audience:

Undergraduate or Postgraduate students of engineering colleges in Karnataka

Detailed course schedule: