Lulea University of Technology – Sweden.
My Journey with Luleå University of Technology – Master’s in Information Security
When I enrolled at Luleå University of Technology in Sweden to pursue a Master of Science in Information Security, I knew I was stepping into a program that would challenge my technical expertise, broaden my worldview, and prepare me to lead in one of the most critical fields of our time. The program was rigorous, research-driven, and deeply relevant to the fast-changing landscape of cybersecurity. Looking back, it was not just about earning a degree—it was a transformative journey that reshaped my approach to technology, problem-solving, and leadership.
The foundation of my studies lay in courses such as Cryptography, Network Security, and Operating Systems Security, where I gained deep technical insight into protecting information assets in complex digital environments. These courses challenged me to think critically about both the mathematical underpinnings of security and their real-world applications in safeguarding organizations against threats.
As the program advanced, I immersed myself in Security Management, Risk Analysis, and Legal Aspects of IT Security, which broadened my perspective beyond technical defenses to include governance, compliance, and ethical considerations. I came to appreciate that information security is not only about firewalls and encryption but also about policies, people, and processes. This systems-level understanding equipped me with the skills to align security initiatives with organizational goals and regulatory requirements.
One of the most defining experiences was my Master’s Thesis: “Long Short-Term Memory Recurrent Neural Network for Detecting DDoS Flooding Attacks within TensorFlow Implementation Framework.” Distributed Denial of Service (DDoS) attacks remain one of the most devastating threats to internet service providers—easy to launch, but costly and complex to detect. My research focused on leveraging deep learning, specifically LSTM recurrent neural networks, to detect and mitigate such attacks more effectively than conventional statistical methods.
Through Design Science Research Methodology (DSRM), I built and trained models using both CPU and GPU systems, testing seven evaluation parameters to measure detection accuracy and performance. The results were remarkable: my model achieved a detection accuracy of 99.968%, outperforming existing benchmarks such as Yuan et al.’s 97.606%. Importantly, the study revealed that training performance was influenced more by dataset size than by hardware type, and that increasing epochs extended training time without affecting accuracy. This work not only contributed to the academic field but also demonstrated the real-world potential for developing Intrusion Detection Systems (IDS) capable of recognizing multiple attack types with high reliability.
The program also emphasized scientific methodology, instructional rigor, and real-world application. I learned to balance research with hands-on security practices like penetration testing and incident response. These experiences built both my technical depth and my leadership capacity to communicate findings clearly and drive actionable change.
Ultimately, my journey at LTU shaped me into more than a cybersecurity specialist. It cultivated in me a philosophy that information security is not merely about defending systems but about enabling trust, resilience, and innovation in a digital-first world. With strong academic results, practical expertise, and research that pushed the boundaries of security detection, I emerged from the program ready to contribute meaningfully to safeguarding organizations and communities.
This degree continues to fuel my mission: to apply advanced research and leadership in building secure, ethical, and future-ready digital environments that empower people and institutions alike.