The desire to help organizations understand the complexity of attack vectors and support their cyber defense with automated incident response capabilities driven by machine intelligence.
Bringing a combination of industry and academic experience to their work, Dr. Awuah and Dr. Kinyua have developed a passion for helping organizations optimize their resources to defend against an ever-growing cyber threat landscape. We have reached a point where cybersecurity students need to gain insights into innovative cybersecurity solutions in the field. Additionally, pattern recognition, anomaly detection, and predictive analytics offer threat intelligence and cybersecurity analytics capabilities that are key ingredients in automated incident response and threat mitigation efforts in today’s threat landscape.
The authors’ research focuses on AI-specific solutions to confront cybersecurity challenges including pattern recognition, anomaly detection, predictive analytics, and user behavior analytics. Other research interests include IoT security, blockchain technology, FinTech security, software-defined networking, technology acceptance, and diffusion of innovations. Our newly published research article examines the challenges that confront today’s security operations center (SOC) teams as a result of the diverse range of cyber defense tools, products, and solutions in a highly dynamic threat environment. Within the SOC environment, a security orchestration, automation, and response (SOAR) solution triggers actionable security operations playbooks to facilitate investigations, delegate tasks, orchestrate disparate tools, and automate remediation actions, among other diverse capabilities.
To be efficient in mitigating evolving threats, organizations should endeavor to empower the security operations team with AI-based automated mitigation systems, which tend to offer security orchestration and response processes to fully automate and manage the complexity of the SOC ecosystems. Throughout their research work, the authors recognize and address the urgent need in organizations to bolster cyber defense operations with innovative security orchestration and automation capabilities in order to effectively and efficiently mitigate today’s sophisticated threat landscape. In particular, the authors anticipate that their current and future research studies will explore the impact of deep reinforcement learning (DRL) in SOAR empowerments involving game theory models with multiple DRL agents and deception techniques based on generative adversarial networks (GANs) models.
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