Indu Krishna

Associate Data Analyst, Research and Innovation

Indu is an Associate Data Analyst at Security Quotient, specializing in Cyber Security and Behavior Analytics. She stepped into this role in October 2023, right after earning her Master’s degree in Computational Linguistics. Indu is passionate about exploring new cyber security and data science frontiers and is determined to grow within her role. In her work, Indu focuses on transforming raw data into clear, actionable insights and visually compelling stories. However, her contributions extend beyond the analysis space into contributing significantly to Security Quotient’s web presence by writing insightful blog articles and case studies. Her work demonstrates how cyber security data analytics underpin the defense against digital vulnerabilities.

Articles authored by Indu Krishna
A laptop screen displaying the word compliance.

Compliance for SMEs

Cyber Security Compliance for SMEs : Data Protection Strategies

Compliance frameworks allow SMEs to achieve business continuity, protect sensitive data, and maintain customer trust, through proven strategies.

Cyber Security Behavior Data Analytics

Role of Behavior Indicator Map in Cyber Security Data Analytics

The behavior indicator map is customizable and adaptable and this makes them a highly valuable tool in the cyber security realm. These features ensure that the maps remain relevant and effective in the face of evolving threats, changing organizational structures and varying user behaviors.

In response to today's dynamic cyber security landscape, professionals have shifted their focus from traditional signature-based methods to more advanced techniques, and Cybersecurity Behavior Data Analytics has emerged as a game-changer.

Cyber Security Behavior Data Analytics

Understanding Cyber Security Data Analytics

At its core, Cyber Security Behavior Data Analytics is an advanced strategy that focuses on understanding and analyzing the behavioral patterns of users or employees in a digital environment. By recognizing subtle changes in user behavior, it can anticipate security incidents before they escalate, allowing organizations to take pre-emptive measures.