Combating Advanced Persistent Threats (APTS) in Critical Infrastructure
Year: 2025
Type: article
Abstract: This report focuses on Advanced Persistent Threats (APTs) as one of the most serious and complex cybersecurity challenges facing critical infrastructure in the modern age of globalisation and digital networking. APTs are sophisticated, stealthy, and long-term cyberattacks often carried out by state-sponsored actors, organized cybercriminals, or hacktivist groups. These threats are designed to infiltrate systems, remain undetected for extended periods, and extract valuable information or disrupt operations. The sectors most targeted include energy, healthcare, water, transport, finance, and telecommunications, all of which are vital to national security, public safety, and economic stability. APTs are dangerous because they exploit vulnerabilities not only in technology but also in people and supply chains. The report identifies that modern APTs have evolved from traditional signature-based attacks to using advanced tools like artificial intelligence (AI) and machine learning (ML) to enhance evasion and precision. As such, traditional security measures are often insufficient. The report highlights the need for a multi-layered security approach grounded in prevention, detection, and response. Key strategies include adopting a Zero Trust security model, enhancing threat detection using AI/ML, increasing cybersecurity awareness among employees, sharing threat intelligence, and fostering cooperation between nations and private sectors. This report serves as a strategic guide for policymakers, cybersecurity professionals, and organizational leaders, emphasizing the urgency of strengthening defenses against APTs. Effective APT management requires constant vigilance, coordinated action, and advanced technological integration to ensure the protection of critical assets in an increasingly connected world.
Authors: Capstone Project by Cohort 6 of the National Cyber Security Scholar Program, Karthik Varadharajan
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7089471033
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