Cybersecurity for Data Science: Issues, Opportunities, and Challenges

Cybersecurity (CS) is one of the critical concerns in today’s fast-paced and interconnected world. Advancement in IoT and other computing technologies had made human life and business easy on one hand, while many security breaches
are reported daily. These security breaches cost millions of dollars loss for individuals as well as organizations. Various datasets for cybersecurity are available on the Internet. There is a need to benefit from these datasets by extracting useful information from them to improve cybersecurity. The combination of data science (DS) and machine learning (ML) techniques can improve cybersecurity as machine learning techniques help extract useful information from raw data. In this paper, we have combined DS and ML for improving cybersecurity. We will use the CS
dataset, and ML techniques will be applied to these datasets to identify the issues, opportunities, and cybersecurity challenges. As a contribution to research, we have
provided a framework that will provide insight into ML and DS’s use for protecting cyberspace from CS attacks.