Responsible application of AI in cybersecurity not only secures the interests of organisations but those of society as a whole
As the digital sphere continues to evolve, so does the threat landscape. The systems and innovations that fuel our current era of digital transformation are under constant siege from increasingly sophisticated and complex cyber-attacks. In this context, it is crucial for organisations to embrace the latest defensive capabilities and ensure that they stay ahead of the curve in terms of cybersecurity.
Artificial intelligence is progressively being viewed as a key piece of the IT security puzzle. Across sectors, AI-powered cybersecurity solutions are revolutionising approaches taken by enterprises in detecting and mitigating cyber threats – bringing to bear capabilities far beyond those of conventional security methodologies.
The Traditional Approach to Cybersecurity
Conventional cybersecurity approaches typically centred around signature-based detection systems, and compared incoming traffic to databases of known threats or malicious code signatures. A match would trigger an alert in the system, leading to action to block or quarantine the identified threat. Likewise, rule-based systems flag traffic that violate rules or policies defining acceptable behaviour on networks.
However, while these systems were effective against known threats, they proved inflexible and ineffective in the face of new or hitherto unidentified threats. Signature-based systems also generated a large number of false positives (due to legitimate traffic being flagged as malicious if it shared characteristics with a known threat), which proved to be a drain on resources.
Manual analysis was also a key part of traditional cybersecurity systems, with security analysts needing to investigate security logs and alerts to identify possible breaches – a process that was time-consuming, and prone to human error.
How AI Redefines Cybersecurity Processes
The growing adoption of AI-based cybersecurity solutions addresses a number of gaps left by conventional approaches. At the core of AI’s effectiveness in cybersecurity lies the machine learning (ML) algorithms that enable it to continuously learn and adapt to a dynamic threat environment.
These ML algorithms are trained using vast datasets – including historical threat data, network traffic, user activity and live threat intelligence feeds – that provide them with the ability to uncover hitherto unseen patterns and signs of compromise. This in turn empowers AI to identify and respond to malware and other threats, including those that are new and emerging, in real-time – without the need for human intervention.
In addition to real-time incident response and malware detection & removal, another key use-case for AI in cybersecurity is phishing detection, wherein the content and structure of emails and other communications are analysed to identify the patterns and anomalies that are indicative of a phishing or social engineering attempt.
Learning from historical data, AI/ML-based cybersecurity systems are well-placed to predict potential vulnerabilities and threats. This empowers organisations with the foresight to proactively strengthen their defences, and to identify and thwart potential attacks before they materialise.
AI-Human Synergy in Cybersecurity
While AI has undoubtedly elevated cybersecurity practices, it is essential not to neglect the ‘human factor’. The new cybersecurity paradigm will be defined by a symbiotic relationship between AI/ML-based systems and human security professionals.
Human experts bring to the table their intuition, critical thinking, and contextual knowledge – enabling them to effectively validate the output of automated systems and combine AI insights with their own experience and subject-matter expertise to arrive at well-informed decisions. The human touch is also critical when it comes to effectively engaging key organisational stakeholders on cybersecurity issues and guiding the implementation of security strategies.
VP & Chief Information Security Officer (CISO), Fulcrum Digital
Ensuring seamless AI-Human collaboration will require organisations to invest in robust and continuous learning & development for cybersecurity professionals, providing them with a comprehensive and up-to-date understanding of AI capabilities and limitations, as well as the ability to accurately interpret and validate AI-generated outputs.
Towards an AI-Driven Cybersecurity Paradigm
AI has already demonstrated immense promise in the cybersecurity sphere. In the years ahead, as organisations continue to implement and scale up AI-driven solutions to elevate the efficacy of their security initiatives, it is essential to take measures to ensure safe and ethically responsible usage of the technology. Given that AI algorithms are not infallible, it is critical that their decision-making is transparent and open to scrutiny by organisational stakeholders. Responsible application of AI in cybersecurity not only secures the interests of organisations but those of society as a whole.
