Divyasri Koshike

Cybersecurity grad with one year of corporate experience as a web developer and tech enthusiast aiming to enhance trust in technology, ensuring data and privacy security for a better world. I have acquired a strong foundation in cybersecurity principles, techniques, Strategies, and technologies.

Information Security Policy: During my coursework, I have written an information security policy for Information classification policy to ensure that information receives an appropriate level of protection in accordance with its importance to the organization. The policy was written with guidelines from ISO27001 and also in accordance with GDPR

Pentesting Server Project: As part of coursework, undertook the task of pentesting a server, tasked with identifying and exploiting vulnerabilities. Demonstrated proficiency in ethical hacking through this project, effectively analyzing system weaknesses and recommending appropriate mitigations. Produced a comprehensive report detailing discovered vulnerabilities and proposed strategies for mitigation.

Digital Forensics Project: Utilized Autopsy to conduct an in-depth analysis of an image file with a .E01 extension, uncovering critical insights into a suspected crime and the perpetrator's intent. Produced a meticulous forensic report outlining findings and conclusions. Acquired proficiency in investigation methodologies and advanced digital forensic tools such as FTK Imager, enhancing capabilities in forensic analysis and evidence extraction.

Cyberoperations Project: Led a comprehensive analysis of network packet captures utilizing Wireshark, meticulously identifying attack patterns within the PCAP file. Generated a detailed technical assessment of the attack, including insights into its methodologies and potential impact, alongside recommended mitigation strategies. This endeavor fostered a profound comprehension of both offensive and defensive cyber operations, culminating in the design of an effective cyber defense strategy.

Cyber Forensic Support System for Flood Attack Detection in IoT:  The project aims to develop a cyber forensics system detecting flood attacks in IoT systems using ML techniques including decision trees, Gradient  Boost, and AdaBoost algorithms. Gradient Boost achieves a peak accuracy of 95% and 97% without and with  Sequential FS, respectively.

Certified in Cybersecurity by ISC2

Introduction to Cybersecurity by Cisco

CompTIA Security+ (SY0-601) Cert Prep: 1 Threats, Attacks, and Vulnerabilities by LinkedIn