By Michael Sanya Oluyede
The growing spate of cyberattacks pose a huge challenge to the remarkable feats in technological innovations of the digital age.
The agility of cybercriminals and the consequences of their actions on businesses are unsettling, necessitating continuous enhancements in cybersecurity. Since its advent, Machine Learning (ML) has proven effective in identifying and managing cyber threats. However, the emergence of unsupervised learning, a la Artificial Intelligence (AI), offers a newer perspective on the issue. This is because AI is capable of detecting any known threats timely and faster, even unknown ones, too.
Leveraging clustering algorithms, such as k-means and hierarchical clustering, unsupervised learning can easily spot any action that deviates from the normal behavior in a computer or network asset. This has made AI a critical means of fortifying cyber defences.
More so, AI is adaptive, which makes it possible to identity and respond quickly to even unpredictable breach to a computer network. Exciting as the fusion of AI into cybersecurity sounds, it is however replete with its own challenges. These challenges have raised such ethical questions, including exposure to adversarial attacks, bias in AI algorithms, and privacy concerns. For instance, in a situation of an adversarial attack, AI threat detection capabilities become weak, vulnerable, and ineffective.
It is not all gloom anyway. This is why it is essential that, as we move forward, we place greater priorities on transparency, adaptability, and continuous learning of newer ways to boost cybersecurity.
As an expert, I advise that businesses and organisations invest in the development of AI-driven solutions that prioritize security and privacy. Even if we are to combine AI and quantum computing, the approach is not without its challenge. Particularly, the risk the approach poses to traditional encryption methods. The aforementioned challenges evidently underscores the need to develop AI-driven threats detection and response mechanism, in tandem with the growing Internet of Things (IoT).
Overall, I believe that the integration of AI in cybersecurity is a double-edged sword, which presents both benefits and challenges requiring urgent attention. Particularly, that we ensure that the development and deployment of AI in cybersecurity prioritize security, privacy, and transparency.
Oluyede, MSc Advanced Computer Networks, (Sheffield Hallam University,) CCIE, CCNP, VCP-DCV, VCP-NV
