Nowadays, enterprises acknowledge the importance of cyber-security for their business operations. However, despite increased investments in cyber-security technologies and measures, there is still a steady rise of security incidents against IT infrastructures, such as phishing, ransomware and DDoS (Distributed Denial of Service) attacks. This is clearly reflected in the increase in notorious attacks that have taken place during the last couple of years, such as the fraudulent attacks against the SWIFT network in the financial sector and the famous “Wannacry” ransomware attack, which affected thousands of organizations around the global.
Cyber-security attacks have significant financial implications. For example, the SWIFT network attack resulted in $81 million being stolen from the Bangladesh Central Bank. Moreover, these attacks also have adverse societal implications, as they reduce citizens’ and businesses trust in the IT systems that underpin our society. Therefore, it’s important to understand why and how IT systems are still vulnerable, whilst exploring new security solutions for alleviating these vulnerabilities.
Coping with cyber-security threats is nowadays more challenging than ever before. The reasons for this are manifold and include:
The above factors make implementation of effective cyber-security challenging and provide opportunities for adversaries to launch large scale, sophisticated and sometimes asymmetric attacks, which can be hardly predicted or mitigated for based on conventional measures. Therefore, security experts are looking for intelligent and new approaches to confront and tackle these attacks. In this context, emerging Artificial Intelligence (AI) systems provide the right tools for building effective security solutions.
Recent advances in AI systems enable the identification of complex patterns based on human-like reasoning. These capabilities have their roots in deep learning which involves the use of advanced neural networks. These networks are able to reason over large amount of information about the problem at hand. Hence, the use of AI for cyber-security leads to the following benefits:
The implementation of AI for cyber-security involves the collection of security-related datasets from appropriate security monitoring probes that have been developed and deployed for the same. The availability of large amounts of relevant data is a prerequisite for training and deploying AI-based deep learning algorithms. In the future, we might also see even more intelligent systems that will require limited or virtually no prior training. These systems are conveniently called “strong AI systems” and are differentiated from the “weak AI systems” that require extensive training using ground truth about security incidents.
Most AI-based security implementations are in their infancy. Enterprises wishing to deploy AI for cyber-security should consider the following recommendations:
In the coming years, companies will be faced with unprecedented cyber-security pressures. Therefore, they have to consider novel and more automated approaches to respond to these pressures. AI provides exciting opportunities for deploying security systems and is certainly a technology that deserves to be explored. We hope that our above listed tips provide a sound starting point in this exploration journey.
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