Nigeria to Houston: Osuorah pursues sustainable solutions to address increasing complexity of cyber threats

Josemaria Osuorah is a software engineer and a current machine learning and cybersecurity PhD student in Praire View A&M University in Houston. He is currently doing research that optimises cybersecurity practices with AI & Machine Learning. In this interview with IFEOMA OKEKE-KORIEOCHA, Osuorah speaks on how he balances academic responsibilities with his role as a research assistant. He also shares insight on his research which focuses on developing robust and scalable security frameworks that can protect critical infrastructures from modern threats while ensuring efficient and resilient network performance.

What inspired you to pursue a PhD in Electrical Engineering, focusing on Computer Networks, Cybersecurity, and Machine Learning?

My decision to pursue a PhD in Electrical Engineering, with a focus on Computer Networks, Cybersecurity, and Machine Learning, is driven by my passion for Computer Engineering and its role in shaping modern technology.

From my undergraduate studies in Computer Engineering at Madonna University, Nigeria, to my master’s degree in Computer Science (Software Engineering) at the University of Staffordshire, I have been deeply fascinated by the interplay between hardware and software in building secure and efficient computing systems.

As technology continues to evolve, so do the challenges in network security, data protection, and system reliability. I chose the Computer Engineering route within Electrical Engineering to bridge the gap between network infrastructure, cybersecurity protocols, and system optimization.

My research focuses on developing robust and scalable security frameworks that can protect critical infrastructures from modern threats while ensuring efficient and resilient network performance.

Beyond academia, I am passionate about applying my knowledge to practical solutions that enhance digital security and network efficiency. Through my research, I aim to contribute to the advancement of secure and high-performance computing systems, ensuring they meet the growing demands of an increasingly interconnected world.

How do you balance your academic responsibilities with your role as a Research Assistant?

Balancing my PhD studies with my role as a Research Assistant has been both a challenging and rewarding experience. I previously worked as a Software Engineer, but this year, I made the decision to transition fully into my PhD program, allowing me to focus entirely on research and academic development. In my current role as a Research Assistant, I conduct research in Computer Networks, Cybersecurity, and Machine Learning, contributing to the university while also advancing my own studies.

Striking a balance between my responsibilities requires effective time management and discipline. I clearly separate my work hours from my study hours, ensuring that both receive the attention they deserve. There are times when I need to work extra hours during weekdays and weekends to meet deadlines, but I find it fulfilling because my research assistantship complements my doctoral studies, providing valuable hands-on experience while reinforcing my academic work.

One of the major strategies I use is structured scheduling. By setting priorities and allocating dedicated time for research, coursework, and personal activities, I have been able to maintain productivity without feeling overwhelmed. This approach has allowed me to stay focused while still making time for personal growth and relaxation.
So far, my experience has been both demanding and rewarding, and I continue to refine my approach to ensure that I make the most of both my research role and PhD journey.

What is the impact of Machine Learning in the field of Computer Networks and Cybersecurity, and what opportunities or challenges arise from this intersection?

The integration of advanced computational techniques in Computer Networks and Cybersecurity has significantly transformed how we manage network infrastructure and defend against cyber threats. As technology advances, networks are becoming more complex, and security threats are evolving at an unprecedented pace. Traditional security methods, which rely heavily on predefined rules and signatures, are often insufficient in tackling sophisticated cyberattacks.

However, data-driven approaches now offer more dynamic ways to enhance threat detection, real-time security analysis, and network performance optimization.

One of the key opportunities in this intersection is the ability to enhance threat detection and response mechanisms. By analyzing vast amounts of network data, modern security solutions can recognize patterns and anomalies that indicate potential cyber threats, allowing for faster and more accurate identification of malicious activities. This has revolutionised cybersecurity by reducing reliance on manual monitoring and significantly improving response times. Additionally, computational techniques play a crucial role in optimizing network performance, ensuring efficient bandwidth allocation, minimizing downtime, and predicting system failures before they occur. These capabilities contribute to a more resilient and adaptive network infrastructure.

However, while the benefits in computer networks and cybersecurity are immense, there are also notable challenges. One of the primary concerns is data privacy and security. Many modern security techniques require large datasets for analysis, and these often contain sensitive information. Ensuring that this data remains protected from breaches is essential to maintaining trust and compliance with security regulations. Another challenge is the rise of sophisticated cyber threats, where attackers continuously evolve their methods to bypass security systems, making it necessary for security frameworks to constantly adapt.

Additionally, computational demands can be resource-intensive, requiring high processing power and robust infrastructure, which may not be readily available in all network environments. There is also the risk of false positives, where normal network behavior is mistakenly flagged as a threat, leading to unnecessary interventions and disruptions.

Addressing these challenges requires continuous refinement of security models, ethical considerations in data handling, and ongoing investment in computational resources.

Despite these hurdles, the application of advanced computational techniques in computer networks and cybersecurity is redefining how we approach digital security and network management. As technology evolves, the ability to automate security responses, enhance network reliability, and scale with growing data demands will continue to unlock new possibilities. By addressing the challenges and improving the efficiency of these systems, new security innovations will remain a driving force in strengthening global cybersecurity and advancing the future of network technology.

Considering the nature and changing current cybersecurity threats, what machine learning techniques would you suggest to be most suitable to address these threats ?

With the increasing sophistication of cybersecurity threats, modern security frameworks must continuously evolve to detect, prevent, and mitigate attacks effectively. The digital landscape is facing an ever-growing range of cyber threats, including ransomware, phishing attacks, data breaches, and zero-day exploits. These threats are becoming more advanced, making it necessary to adopt proactive and adaptive security mechanisms that can respond swiftly to emerging risks.

One of the most effective approaches to tackling these evolving threats is anomaly detection, which focuses on identifying unusual patterns in network activity. This technique is essential for detecting intrusion attempts, malware activities, and insider threats, as it helps distinguish normal operations from potential security breaches. By continuously monitoring network traffic and system behavior, anomaly detection enables security teams to respond to threats before they escalate.

Another crucial method is behavioral analysis, which examines the activities of users and systems to identify suspicious actions that may indicate a security compromise. Unlike traditional rule-based security measures that rely solely on known attack signatures, behavioral analysis is capable of detecting new and previously unseen attack patterns. This makes it particularly effective in combating threats such as advanced persistent threats (APTs), phishing scams, and unauthorized access attempts.

Additionally, pattern recognition techniques play a significant role in identifying recurring cyber threats by analyzing historical data. This approach helps security systems recognize attack signatures and respond quickly and efficiently to known security threats. The ability to automate threat detection and response ensures that security incidents are addressed with minimal delays, reducing the potential damage caused by cyberattacks.

Despite the advantages these techniques offer, challenges such as data privacy concerns, evolving attack methods, and the need for continuous monitoring must be addressed to ensure effective cybersecurity defenses. Implementing strong encryption, multi-layered security strategies, and real-time monitoring systems is essential to safeguarding critical information and infrastructure.

As cyber threats continue to evolve, the need for advanced security techniques becomes even more pressing. By integrating proactive threat detection, continuous monitoring, and rapid response mechanisms, organizations can build stronger and more resilient security frameworks, ensuring the protection of digital assets in an increasingly connected world.

Can you walk us through a project or research you intend to carry out during your study that combines Computer Networks, Cybersecurity, and Machine Learning?

As part of my PhD research, I am focusing on the development of an advanced cybersecurity framework for real-time network monitoring and threat detection. This project aims to address the increasing complexity of cyber threats by improving how security breaches are identified and mitigated in modern network infrastructures.

With the growing reliance on digital communication and the expansion of connected systems, organizations face rising challenges in safeguarding sensitive data, preventing cyberattacks, and ensuring network reliability. Traditional security approaches often struggle to keep up with new attack methods, making it necessary to develop more efficient and adaptive security mechanisms. My research seeks to provide a proactive and automated approach to network security by analyzing network traffic patterns, identifying unusual activities, and responding to threats in real time.

One of the main aspects of this research is network anomaly detection, where deviations from normal network behavior are continuously monitored. By analysing traffic flow, security threats such as unauthorized access, malware infiltration, and denial-of-service attacks can be detected early and mitigated before causing major disruptions.

Another important part of the project is automated incident response, which focuses on minimizing the time taken to contain cyber threats. Upon detecting a potential security breach, the system will be designed to take immediate action, such as isolating compromised devices, blocking malicious connections, or notifying security teams for further investigation. By ensuring rapid response times, this approach will help prevent small security incidents from escalating into large-scale cyberattacks.

However, this research also comes with challenges, such as ensuring data privacy, minimizing false alarms, and maintaining network efficiency without introducing unnecessary disruptions. A well-structured security system must be designed to strike a balance between accuracy and operational efficiency while ensuring that it can be applied across different network environments.

This project will further aim to develop a scalable and robust security solution that can be implemented in enterprise networks, cloud infrastructures, and critical national systems. By improving the ability to detect, prevent, and respond to cyber threats, this research will contribute to stronger network defenses and a more secure digital environment in an era of increasing cyber risks.

What solutions do you envision or anticipate when your research is applied in real-world scenarios, such as industry or government?

When applied in real-world scenarios, my research has the potential to provide stronger, more adaptive, and efficient cybersecurity solutions for both industry and government institutions. As cyber threats continue to grow in complexity, organisations require security frameworks that can continuously monitor, detect, and respond to potential risks without relying solely on reactive measures.

The solution I anticipate is the improvement of network security monitoring and threat detection in critical sectors such as finance, healthcare, telecommunications, and government agencies. By strengthening security mechanisms, organisations will be better equipped to identify and mitigate threats such as unauthorized access, malware infiltration, and cyberattacks before they cause significant harm. This will be particularly beneficial in protecting sensitive data, national infrastructure, and essential services that depend on secure communication networks.

In the corporate sector, this research can help enhance cybersecurity management, reducing reliance on manual monitoring while improving efficiency. Many businesses face cybersecurity challenges due to limited resources and skilled personnel, making it essential to have automated security systems that quickly detect and respond to potential threats. This will help organizations prevent financial losses, protect customer data, and ensure business continuity in an increasingly digital world.

For government institutions, the application of this research can reinforce national security efforts by providing stronger protection against cyber espionage, data breaches, and attacks on critical infrastructure. Governments worldwide face growing cybersecurity risks, from threats to public utilities to attacks on communication networks. By implementing more effective security frameworks, authorities can mitigate cyber threats, safeguard sensitive information, and strengthen their ability to respond to security incidents.

Another major outcome of this research is the development of secure and resilient communication networks. As industries and governments continue to adopt cloud-based systems and interconnected technologies, ensuring that these networks remain secure from cyber threats is essential. The ability to monitor threats in real-time and respond swiftly to security breaches will reduce the risk of cyberattacks disrupting essential services.

This research aims to bridge the gap between cybersecurity challenges and practical solutions, ensuring that both public and private sectors can adopt effective, scalable, and proactive security frameworks. By addressing current and emerging cyber threats, it will contribute to a safer and more secure digital environment, allowing organizations to operate with confidence while protecting their systems and data.

Where do you see the field of Computer Networks, Cybersecurity, and Machine Learning evolving in the next 5–10 years?

Over the next five to ten years, the fields of computer networks and cybersecurity will undergo significant advancements, driven by increasing global connectivity, digital transformation, and the growing need for stronger security measures. As cyber threats become more sophisticated, businesses, governments, and individuals must adapt to new security challenges while ensuring that networks remain efficient, scalable, and resilient.
One major development will be the expansion of high-speed, intelligent, and self-regulating networks. With the continued deployment of 5G and the emergence of 6G technology, organizations will experience faster and more efficient communication systems. This will enable an increase in connected devices, smart infrastructure, and cloud-based services, all of which will require stronger security frameworks to protect against cyber threats and unauthorized access.

Cybersecurity will shift towards proactive threat prevention, focusing on continuous monitoring, real-time threat detection, and automated response mechanisms. Instead of reacting to cyberattacks after they happen, organizations will invest in preventative security measures to minimize risks before breaches occur. This shift will be essential as cybercriminals continue to target cloud computing, remote work environments, and critical national infrastructure.

Data privacy and regulatory compliance will also take center stage. As global concerns over data breaches and digital surveillance increase, governments and organizations will implement stricter data protection laws, encryption techniques, and secure identity verification systems to safeguard sensitive information. This will help create a more secure and transparent digital environment for individuals and businesses alike.

Additionally, industries such as finance, healthcare, and smart cities will require more robust and adaptable network security solutions as they continue integrating cloud computing, digital transactions, and automated services. The rapid growth of these sectors will demand secure communication channels and enhanced digital protection measures to prevent financial fraud, identity theft, and system vulnerabilities.

However, these advancements will also bring challenges. As more devices and systems become interconnected, the attack surface for cyber threats will expand, requiring organizations to strengthen their security infrastructure, invest in skilled cybersecurity professionals, and implement advanced defense strategies. Greater emphasis will be placed on cybersecurity awareness, regulatory compliance, and global collaboration to ensure that emerging risks are effectively managed.

Looking ahead, the future of computer networks and cybersecurity will be shaped by technological progress, strategic investments, and a strong commitment to security innovation. The ability to develop and maintain secure, high-speed, and resilient digital infrastructures will be crucial for businesses, governments, and economies to thrive in an increasingly connected world. Those who take a proactive approach to cybersecurity will be best positioned to navigate the challenges and opportunities that lie ahead.

What is your advice for youths looking to build a profession in Computer Networks, Cybersecurity, and related fields?

For youths aspiring to build a career in Computer Networks, Cybersecurity, and related fields, my advice is to focus on strong foundational knowledge, continuous learning, and hands-on experience.
The journey begins with mastering the fundamentals. Understanding core concepts such as networking protocols, operating systems, system security, and data protection is essential. Young professionals should start with basic certifications such as CompTIA Network+, Security+, or Cisco’s CCNA, which provide a solid technical foundation.
Commitment and consistent skill development are key. The field of cybersecurity and networking is constantly evolving, and staying updated requires dedication. Learning programming languages like Python, C, or scripting tools, understanding network security frameworks, and keeping up with emerging threats and solutions are crucial for growth.

Practical experience is equally important. Internships, labs, and real-world projects help in applying theoretical knowledge to real challenges. Engaging in cybersecurity competitions, networking simulations, and ethical hacking exercises can provide valuable exposure.

Additionally, pursuing higher certifications and advanced degrees can open doors to leadership roles. Certifications like CISSP, CEH, and CCNP, combined with real-world experience, can set professionals apart in the industry.

Lastly, passion and perseverance matter. Cybersecurity and networking require problem-solving skills, adaptability, and a proactive mindset. Young professionals should remain curious, continuously learn, and never be afraid to challenge themselves. With the right foundation and commitment, a successful and impactful career in this field is achievable.

Can you share some success stories in your career path?

My career journey, from undergraduate studies to pursuing a PhD, has been shaped by a passion for Computer Networks, Cybersecurity, and Cloud Services, along with continuous learning and hands-on experience.

During my master’s program at University of Staffordshire, I developed A Comparative Analysis Framework Tool for SME Cloud Service Users. This project aimed to help small and medium-sized enterprises (SMEs) evaluate and compare different cloud service providers based on cost, security features, scalability, and reliability. By analysing various cloud infrastructures, the tool provided SMEs with data-driven insights to make informed decisions about their cloud adoption strategies. This research deepened my expertise in cloud security, service evaluation, and network performance optimization.

Navigating the academic environment from my undergraduate days, to my PhD journey has been a path of dedication and growth. Moving from Computer Engineering at the undergraduate level to Computer science (Software Engineering) in my master’s, and now Electrical Engineering at the PhD level, has allowed me to develop a multidisciplinary approach to problem-solving. Balancing coursework, research, and professional engagements has strengthened my ability to adapt to technological advancements and contribute to the field of cybersecurity and networking.

Today, as a PhD researcher and Research Assistant, I am focused on developing robust security frameworks for modern network infrastructures. My journey has taught me that commitment, continuous learning, and practical experience are key to success in this ever-evolving industry.

How do you stay current with the latest developments and advancements in cybersecurity, computer networks, and related fields?

Staying up to date in cybersecurity, computer networks, and related fields requires continuous learning and engagement with industry trends. I achieve this by reading research papers, attending conferences, and following reputable technology publications that cover emerging threats and advancements.

I also participate in academic and professional forums, cybersecurity workshops, and networking events, where experts share insights on new challenges and solutions in the field. Additionally, I stay connected with industry standards and regulatory updates, ensuring that my knowledge aligns with current best practices.

Practical learning is equally important. Engaging in research, hands-on projects, and collaborations helps me apply theoretical knowledge to real-world problems, reinforcing my understanding of evolving technologies. By combining ongoing education, industry engagement, and research, I stay well-informed and prepared for the dynamic nature of these fields.