Mrs Naziya Aslam , MNNIT Allahabad , India
Naziya Aslam is a dedicated and accomplished researcher currently pursuing a Ph.D. in Computer Science and Engineering at Motilal Nehru National Institute of Technology, Allahabad, India, focusing on the intelligent detection and mitigation of DDoS attacks in SDN. With a solid educational foundation, including a Master’s degree in Technology from the Central University of Rajasthan and a Bachelor’s degree in Technology from Chhatrapati Shahu Ji Maharaj University, she has consistently excelled academically. Naziya has contributed to several high-impact publications and received prestigious awards, such as the Maulana Azad National Fellowship. Fluent in English, Hindi, and Urdu, she is skilled in various programming languages and development tools. She enjoys reading novels, traveling, and playing badminton. Married to Mohammad Shahnawaz, Naziya exemplifies hard work, self-confidence, and optimism. ๐
Publication Profile
Google Scholar
Education
๐งโ๐ Naziya Aslam is currently pursuing a Ph.D. in Computer Science and Engineering at Motilal Nehru National Institute of Technology, Allahabad, focusing on intelligent detection and mitigation of DDoS attacks in SDN, boasting a CGPA of 8.25. She earned her Master’s degree in Technology with a specialization in Information Security from the Central University of Rajasthan, achieving a CGPA of 7.58. She completed her Bachelor’s degree in Technology, specializing in Information Technology, from Chhtrapati Sahu Ji Maharaj University, with a CPI of 9.42. Her academic journey began at Shree Sanatan Dharm Education Center in Kanpur and Modern International School in Saudi Arabia, with stellar performances. ๐โจ
Teaching Experience
๐ผ From July 2019 to July 2022, Naziya Aslam served as Project Staff (JRF) in the Computer Science and Engineering Department at Motilal Nehru National Institute of Technology, Allahabad, Prayagraj, India. During this time, she worked on a significant project titled “Intelligent Detection and Mitigation of DDoS Attack in SDN.” Her role involved developing innovative solutions to enhance network security, leveraging her expertise in software-defined networking. This experience not only honed her technical skills but also solidified her passion for research and development in cybersecurity. ๐
Achievements
๐ Naziya Aslam has achieved significant academic milestones throughout her career. In 2024, she qualified for GATE, adding to her impressive track record of success. She was awarded the prestigious Maulana Azad National Fellowship (MANF) in 2022. She qualified for UGC-NET for JRF and Assistant Professor in both December 2020 and June 2021. Additionally, she qualified for GATE in 2019 and 2017, and UGC-NET for Assistant Professor in June 2019 and July 2018. From June 2017 to June 2019, she was a recipient of the MHRD, Govt of India scholarship, further showcasing her dedication and excellence in her field. ๐โจ
Certifications
๐ Naziya Aslam has completed several certifications, enhancing her expertise in various areas. In October 2023, she attended the SACSA2023 Online Faculty Development Program on security aspects in computer science, organized by MNNIT Allahabad. She participated in the Math of Machine Learning Spring School workshop by IIT Kharagpur in March 2023. In February 2021, she joined the Information Security Awareness seminar by MNNIT Allahabad. She completed faculty development programs on Artificial Intelligence using Python and IT Infrastructure and Cyber Security in 2020, and a workshop on women’s rights in February 2019. Additionally, she underwent industrial training in network management and web development in 2015. ๐๐
Research Focus
๐ Naziya Aslam’s research primarily focuses on cybersecurity within software-defined networking (SDN), with a strong emphasis on mitigating Distributed Denial of Service (DDoS) attacks. Her work includes developing intelligent applications and methodologies for detecting and preventing such attacks. Notable publications include “ONOS Flood Defender,” “A Comprehensive Analysis of Machine Learning- and Deep Learning-Based Solutions for DDoS Attack Detection in SDN,” “ONOS DDoS Defender,” and “DDoS SourceTracer.” These studies utilize machine learning, deep learning, and ensemble approaches to enhance network security and resilience, demonstrating her dedication to advancing cybersecurity in SDN environments. ๐ก๏ธ๐ป๐