## 5 Conclusions  
This study has comprehensively analyzed major cybersecurity threats targeting energy infrastructure, illustrating how malware such as Industroyer, Triton, NotPetya, and BlackEnergy3 exploit distinct vulnerabilities across the SCADA, ICS, and SIS layers. Each attack highlights specific systemic weaknesses, confirming the necessity of a layered de  
Figure 22: BlackEnergy3 attack pathways and security defense strategies. -fense model. Through [PERSON]'s model, which emphasizes predictive analytics and cyber persona profiling, security strategies effectively address human-centric vulnerabilities such as insider threats and social engineering susceptibility. Implementing [PERSON]'s structured defense enhances resilience, providing robust predictive capabilities and a preemptive approach to evolving threats across the energy sector. The findings highlight the critical need for a holistic defense strategy to mitigate risks at every layer of energy infrastructure. At the physical layer, it was underscored that stringent access control measures, combined with thorough security inspections, are necessary to protect physical assets. The risk of insider threats and direct physical attacks necessitates constant monitoring, enhanced physical safeguards, and robust incident response systems to minimize the potential damage to critical infrastructure. In the network layer, this study confirmed that malware often uses this as a key entry point to infiltrate systems. To mitigate this risk, implementing strong network segmentation and real-time Intrusion Detection Systems (IDSs) is paramount. Malware such as BlackEnergy3 can quickly propagate through networks, emphasizing the importance of dividing the network into smaller segments, applying advanced firewalls, and employing real-time monitoring to block intrusions at an early stage. The control layer, which includes critical systems such as SCADA and SIS, emerged as the most vulnerable and essential aspect for securing energy infrastructure. Attacks such as Industroyer and Triton illustrate the potential for devastating disruptions to power grids and industrial systems. To safeguard this layer, this study recommends robust encryption of communication protocols, along with anomaly detection systems, to detect abnormal behavior early and prevent malicious manipulation of control systems. At the application layer, the threat posed by malware such as NotPetya, which exploits software vulnerabilities to destroy data, was highlighted. This underlines the importance of timely software updates and an automated patch management system to address known vulnerabilities before they are exploited by attackers. In conclusion, this research underscores the necessity of a multi-layered defense strategy that integrates [PERSON]'s model for a comprehensive approach to cybersecurity in energy infrastructure. [PERSON]'s model advocates for predictive analytics and thorough assessments of 'cyber personas'--a crucial aspect of human factors often targeted in social engineering attacks. By incorporating these advanced layers, [PERSON]'s model provides not only enhanced technical resilience but also systematically addresses human-related vulnerabilities, such as insider threats and susceptibility to social engineering, through continuous monitoring and behavior analysis, which are critical for preemptive cybersecurity measures. These integrations foster a robust, preemptive detection system against insider threats and social engineering, ultimately strengthening the resilience of critical energy infrastructure to evolving cyber threats. A comprehensive, layered security architecture mitigates risks at each individual level and further consolidates these defenses into an integrated, step-by-step mechanism, reinforced by [PERSON]'s model, which strengthens the overall security posture by enabling predictive human factor analysis alongside conventional technical defenses.