Security and Artificial Intelligence
In the digital age, information is one of the most valuable assets for any organisation. This intrinsic value also brings with it a growing concern for the security of such information. The increasing complexity of threats, combined with the vast amount of data being generated, communicated, and stored, poses a crucial challenge in protecting information systems and safeguarding privacy. In this context, Artificial Intelligence (AI) emerges as a revolutionary tool in Governance, Risk management and Compliance (GRC) in the field of information security.
In this article, we explore how AI is transforming the information security risk management landscape.We will examine the scenarios in which it appears, the use cases highlighted and the emerging trends that illustrate how this synergy is redefining the way in which corporate asset protection should be approached. As we move forward at this intersection between technology and security, it is crucial to understand how Artificial Intelligence is forging a path towards a more secure future in the protection of digital assets.
In today's information security management scenario, we face a constantly evolving landscape marked by an exponential increase in the complexity and frequency of attacks. Criminals have refined their tactics, exploiting new vulnerabilities and intrusion techniques to steal or hijack sensitive data and cause serious disruptions to business operations. As these attacks become more sophisticated, the need for equally advanced security measures becomes more evident.
However, this challenge is exacerbated by the overwhelming amount of information and events that are generated during an attack. Security systems are faced with a constant deluge of data, logs, and alerts from multiple sources. Manually analysing this flood of information becomes virtually impossible for traditional security teams, resulting in a slow response to threats and the possibility of missing key indicators of compromise.
In this scenario, Artificial Intelligence can be incorporated, with a high impact, into the mechanisms that the different security management models propose for the adequate treatment and management of risks. Always bearing in mind that the human role remains essential. Contextual understanding, ethical decision-making and adaptation to emerging threats require human experience and judgement. The combination of human knowledge and expertise with AI capabilities can translate into new, robust, and adaptive defence capabilities in the changing information security landscape.
Human knowledge and AI capabilities must be combined
On the dark side, cybercriminals have proven adept at adopting emerging technologies, and Artificial Intelligence is no exception. They are leveraging their capabilities to orchestrate more precise and sophisticated attacks, using machine learning algorithms to identify vulnerabilities and design customised attack strategies. Also, to automate repetitive tasks, such as sending mass phishing emails, which increases the efficiency and reach of their malicious operations.
Moreover, once the attack is orchestrated, they are using it to evade detection through adversary generation algorithms that can mutate, in real time, the characteristics of an attack to evade security systems that rely on predefined patterns.
Let's not forget that cybercriminals have access to the same tools we do, but more means at their disposal, more time for training, trial and error, and no concern for compliance with data protection and privacy laws and regulations. We play by different and unequal rules.
Cybercriminals have access to the same tools we do
Still, the lack of patching and updating, misconfiguration of security systems and phishing that continues to work, among others, leads to a scenario where the bad guys still don't need to invest heavily in research and development... yet.
Expectations for the use of Artificial Intelligence are many. Prioritising the development of one or the other line of work will have to be aligned, in each organisation, with its particular risk management and treatment strategy.
- Advanced threat detection: AI will enable more accurate and advanced threat detection by analysing anomalous behaviour patterns in real time. This will improve the ability to anticipate and mitigate attacks before the impact is significant, reducing exposure time and attack surface.
- Automated reaction and response in real time: AI gathers knowledge continuously and applies reasoning to identify reactions between threats. This enables real-time analysis, which in turn allows for agile response, rapid assessment, and action in critical risk situations, minimising the impact and safeguarding the integrity of systems.
- Reduction of decision-making time: Security analysts must make decisions that require the collection, synthesis, and analysis of relevant data. AI can take over the initial stages of such activities and present analysts with relevant contextualised information, resulting in their ability to make informed decisions quickly and accurately.
- Proactive threat identification: Artificial intelligence systems will be able to constantly analyse infrastructure, information, and communication flows and, by correlating with external sources, identify previously unidentified emerging threats. This early identification will allow the implementation of risk mitigation measures to prevent them from materialising into incidents.
- User behaviour models: Through continuous analysis, AI will be able to build normality models that allow the detection of anomalous or unusual activity that could be indicative of an intrusion. Therefore, the rate of false positives in security alerts will also be reduced, as machine learning algorithms will enable the detection between normal situations and truly suspicious activities.
- Strengthening authentication: Increasingly a key element in risk management, strong authentication and authorisation mechanisms supported by behavioural patterns can be implemented with the help of AI to ensure more accurate authentication that is difficult to forge, reducing the risks associated with credential leakage and unauthorised use of fraudulently obtained legitimate credentials.
- Improved threat attribution: AI can improve threat attribution methods by analysing the distinctive behaviour of malicious groups and similarities in the code patterns used in their attacks. This analysis helps to identify more precisely the perpetrators of an attack and contributes to a more targeted and effective response against known cybercrime actors.
Taken together, these expectations underline the transformative role of Artificial Intelligence in information security management, offering more dynamic and proactive solutions in an increasingly challenging digital landscape.
In today's complex scenario, dealing with security challenges may seem daunting, but ignoring them does not make the elephant in the room goes away. In this context, the responsibility of the companies that provide information security management services and the professionals that form them is clear: to collaborate with our clients to forge solid defensive strategies.
It is essential to understand that a secure architecture is not built through the simple accumulation of isolated components but is gestated through holistic vision and expert design. Each element must be considered in its relationship to the whole, so that they form a coherent and resilient structure, a true Information Security Management System (ISMS).
A secure architecture is built through holistic vision and expert design
At Izertis we approach the security of our clients' systems and services from this perspective: embracing complexity and designing strategies that protect their assets and safeguard the trust of their clients and partners, that evolve in a constantly changing security environment, and that guarantee a more secure and resilient environment in which the client can develop their business.