Dr. Monika-Roopak-Digital Foresnisc Investigation Award-Best Researcher Award
University of Huddersfield-United Kingdom
Author Profile
Early Academic Pursuits
Dr. Monika Roopak embarked on her academic journey with a Bachelor's degree in Computer Engineering from Jamia Millia Islamia, India, followed by a Master's in Information Technology from GGSIPU, Delhi. Her thirst for knowledge led her to pursue a PhD in Cyber Security in IoT Networks from Newcastle University, UK, where she delved into cutting-edge research to address emerging challenges in cybersecurity.
Professional Endeavors
With a solid educational foundation, Dr. Roopak ventured into the professional realm, demonstrating her expertise in various roles. She commenced her career as a Software Engineer Trainee at Eware Technologies, India, where she honed her skills in Dot Net development. Subsequently, she transitioned into academia, serving as an Assistant Professor at Ansal University, India, where she imparted knowledge to aspiring engineers while actively engaging in research and administrative duties.
Her academic journey continued as a Research Fellow at the University of Huddersfield, focusing on digital forensic investigation for cases involving child sexual abuse. Concurrently, she served as a Lab Demonstrator at Newcastle University, UK, where she nurtured the next generation of engineers through teaching and mentoring activities.
Contributions and Research Focus On Digital Foresnisc Investigation Award
Dr. Roopak's research endeavors have been marked by pioneering contributions to the field of cybersecurity. Her PhD thesis, titled "Intrusion Detection System for IoT Networks for Detection of DDoS Attacks," stands as a testament to her innovative approach in developing solutions to combat cyber threats in IoT environments. She proposed novel feature selection methods and deep learning models, achieving remarkable accuracy in detecting DDoS attacks while significantly reducing training time.
Her research prowess extends beyond her doctoral studies, as evidenced by her numerous publications in reputable journals and conferences. She has investigated diverse topics ranging from blackhole attacks in mobile ad hoc networks to facial image age estimation for digital forensic investigations.
Accolades and Recognition
Dr. Roopak's contributions to the field have been widely recognized, earning her several prestigious awards and accolades. Notable among these are the Best Research Paper Award at the 33rd International Conference on Automated Planning and Scheduling (ICAPS 2023) and the 2021 Premium Award for Best Paper in IET Networks. Her research has also been generously funded by governmental and academic institutions, reflecting the significance of her work in advancing cybersecurity.
Impact and Influence
Dr. Monika Roopak research has made a significant impact on the cybersecurity landscape, offering practical solutions to mitigate emerging threats in IoT networks and beyond. Her innovative methodologies and deep insights have not only contributed to academic discourse but also hold immense potential for real-world applications in safeguarding digital infrastructures.
The Digital Forensic Investigation Award recognizes outstanding achievements in the field of digital forensics, a crucial discipline in modern law enforcement, cybersecurity, and intelligence gathering. This award aims to honor individuals or teams who have demonstrated exceptional skill, innovation, and dedication in conducting digital investigations to uncover evidence, solve crimes, and mitigate cyber threats.
Legacy and Future Contributions
As Dr. Roopak continues her academic journey, her legacy is marked by a relentless pursuit of excellence and a commitment to pushing the boundaries of knowledge in cybersecurity. With her interdisciplinary expertise and visionary approach, she is poised to make enduring contributions to the field, shaping the future of cybersecurity and inspiring generations of researchers to come.
Citations
- Citations 572
- h-index 6
- i10-index 5
Notable Publication
- Data-driven Decision Support Systems in E-Governance: Leveraging AI for Policymaking
- Automated planning to prioritise digital forensics investigation cases containing indecent images of children
- An Intrusion Detection System Against DDoS Attacks in IoT Networks
- Multi-Objective based Feature Selection for DDoS Attack Detection in IoT Network
- Comparison of deep learning classification models for facial image age estimation in digital forensic investigations