In today’s dynamic and rapidly evolving digital ecosystem, traditional security measures can barely keep up the pace. With each passing day, threat actors come up with new techniques and develop new tools, making the digital landscape a high-stakes game of cat and mouse. Artificial intelligence and machine learning presents a massive game changing opportunity in the continuous battle with threat actors.
As digital transformation continues to change all aspects of human life, we find the threat vector increasing in a linear fashion. This coupled with the advancement in techniques employed by threat actors has led to an increased complexity and a massive volume of potential attacks. Given the sheer volume and complexity, it is impossible for cybersecurity personnel to monitor and effectively respond to threats effectively. This is where AI and machine learning come in, not to replace human experience, but instead to complement it, resulting in a robust defence against the rising tide of cyber threats.
As we examine how Artificial Intelligence and Machine Learning are revolutionising cyber defence, three key areas stand out as the most transformative. These technologies improve response times to threats, enhance operational efficiency and excels at routine tasks like pattern identification which can be tiresome.
Speed of Response To Threats
Traditionally, it could take days for bad actors to launch an attack against an organisation due to the complexity of reconnaissance, vulnerability identification and exploit engineering. However, with the advent of automation bad actors can now accelerate their attack times considerably. Similarly, security analysts would have to spend days going through logs in attempt to identify threats and implement countermeasures. This delay could cause cyber defence teams to lag an initial attack, even when the vulnerability exploited is already known.
This is where Machine Learning (ML) and Artificial Intelligence (AI) shines. ML algorithms ingest and analyse historical data at a much faster rate than humans, allowing for quicker discovery of potential threats. Furthermore, the speed of analysis can be kept consistent and at the same quality regardless of the data volume, unlike humans who are likely to slow down and are prone to mistakes when overwhelmed with data.
Leveraging these technologies will enable cyber defence teams to drastically shorten response times, potentially detecting and mitigating threats before they can cause considerable damage.
Efficiency: Augmenting Human Capabilities
Cyber defence comprises numerous manual tasks, ranging from patch management and log analysis to compliance auditing, to name but a few. Human expertise is invaluable in cyber defence; however, it is impossible for individuals to perfectly repeat manual processes consistently. Furthermore, the limitation of human focus emphasises the need for a much better solution for achieving efficiency.
With AI, vast amounts of log data can be processed at a much fast rate than humans can, patches can be prioritized more efficiently based on risk assessment and primary compliance checks can be automated.
By leveraging these technologies to handle repetitive and data intensive tasks, human can focus on problem-solving and decision making. This way organizations can achieve a more robust, efficient, and adaptable cyber defence posture.
Pattern Identification
Building on the previous point, which suggests that AI and ML should not replace humans but instead augment their capabilities. AI systems can identify trends, subtle patterns in network traffic, user behaviour and system logs which could indicate a potential threat. Additionally, ML algorithms excel at detecting anomalies that deviate from predefined baseline, especially when these deviations are too slight for human analysts to notice. Finally, AI systems have the ability to learn from new attack patterns which creates a defence posture that evolves with the changing threat landscape.
As previously discussed, Artificial Intelligence and Machine Learning are transforming cybersecurity by significantly reducing response times, increasing operational efficiency, and excelling at recognising patterns. These technologies are more than simply tools in cybersecurity, they are forming the foundation of current defence methods. Organisations can now strengthen their cyber defence posture by combining human experience with AI and ML capabilities. As cyber threats grow in complexity and size, including AI and ML into cybersecurity operations is no longer an advantage, but a necessity. The future of cyber defence rests in the combination of human understanding and machine intelligence, which will result in a dynamic and robust shield against the ever-changing landscape of digital threats.
As digital transformation continues to change all aspects of human life, we find the threat vector increasing in a linear fashion. This coupled with the advancement in techniques employed by threat actors has led to an increased complexity and a massive volume of potential attacks. Given the sheer volume and complexity, it is impossible for cybersecurity personnel to monitor and effectively respond to threats effectively. This is where AI and machine learning come in, not to replace human experience, but instead to complement it, resulting in a robust defence against the rising tide of cyber threats.
