Techniques and Tools used in Data Science for Cyber Security

Antima Bhimrao Shendge

Abstract: This Paper discusses various methodologies employed within the field of data science specifically aimed at enhancing cybersecurity measures. By integrating Data Science and Cybersecurity techniques such as statistical modeling, machine learning, automation, and data analysis, these fields work together to detect, mitigate, and react against cyber attacks effectively. Today's surge in cyber threats necessitates more advanced traditional cybersecurity measures for safeguarding digital systems effectively. The field of Data Science is revolutionizing cybersecurity through its use of sophisticated analytical techniques like AI and ML alongside large datasets for identifying threats preemptively. The research underscores crucial methodologies including supervised and unsupervised machine learning, anomaly recognition, text analysis for understanding human behavior patterns, which facilitate immediate detection of harmful actions online. Additionally, it evaluates crucial components such as Python scripting languages, Apache Hadoop for big data processing, Security Information and Event Management (SIEM) solutions, Intrusion Detection Systems (IDS), specifically Snort and Zed Attack Proxy (Zeek), along with Threat Intelligence Platforms designed for automating decisions based on extensive security dataset analyses. Through combining analytical insights derived from big data with cybersecurity tactics, companies can better anticipate threats, swiftly address incidents, and fortify their comprehensive digital security posture. Paper highlights how data science's significance is increasing rapidly within contemporary cybersecurity environments, offering both forward-thinking and strategic approaches.

Keywords: intrusion detection systems (IDS), Machine Learning, Deep Learning, Natural Language Processing, Big Data Analytics

How to Cite?: Antima Bhimrao Shendge, "Techniques and Tools used in Data Science for Cyber Security", Volume 14 Issue 12, December 2025, International Journal of Science and Research (IJSR), Pages: 748-750, https://www.ijsr.net/getabstract.php?paperid=SR251209115258, DOI: https://dx.doi.org/10.21275/SR251209115258