We are at a turning point in the development of cybersecurity. When generative AI models like ChatGPT first gained widespread attention, their promise to protect networks from hackers was only matched by its potential to aid hackers. Although a diverse array of cutting-edge cybersecurity technologies have lately been launched by technology companies, the size and sophistication of threat actors continue to rise.
In order to ensure the utmost protection of data transmission, storage, and access, which is a critical component of the fight against cyberattacks, cybersecurity practices are put into place here.
How to use AI in the cybersecurity sector
In many sectors, including cybersecurity, AI has many benefits and uses. AI may help businesses by staying up-to-date in terms of security, which is advantageous given the quickly growing nature of cyberattacks and the emergence of sophisticated attacking mediums.
Compared to manual methods and conventional security systems, AI can automate threat detection and offer a more efficient response. This aids organisations in maximising their cybersecurity defences and avoiding emerging threats. Here are a few major advantages of utilising AI in the field of cyber security.
Threat detection: Businesses can tremendously benefit from AI-based cybersecurity practices in identifying cyber threats and disruptive activities by cyber criminals. In fact, the proliferation of new malware is happening at an alarming rate, making it extremely challenging for traditional software systems to keep up with the evolving threat landscape.
AI algorithms, however, discover patterns, recognize malware and find any unauthorised activities done before they impact a system. This makes AI a valuable tool for protecting against cybercrime and maintaining the security of business operations.
Bot defence: The defence against bots is one more area where AI is used to counter digital threats. Bots create a substantial portion of online traffic in today's virtual world, some of which may be security risks. Cybercriminals employ bots, also known as automatic scripts or software, to launch attacks on websites, networks, and systems.
Additionally, detrimental acts like Distributed Denial of Service (DDoS) attacks, account takeovers, and the scraping of private data can all be carried out via bots.
Phishing detection: By identifying complex phishing attempts, AI can significantly improve the cybersecurity landscape. Incoming emails and communications can be analysed and categorised by machine learning models powered by AI to determine whether they are authentic or fake.
AI can search for words, phrases, and other indicators that are frequently linked to phishing assaults by utilising natural language processing techniques. The ability for security teams to quickly detect and handle potential risks minimises the possibility of a successful phishing attack.
AI cybersecurity limitations
Despite their increasing sophistication, AI systems are still constrained by their knowledge base. These systems are potentially impotent in the face of unforeseen or complex dangers that lay outside of their specified domain because they can only operate with the help of their trained data sets.
Furthermore, these restrictions make them vulnerable to false positives and false negatives, making it easier for unknown threats and needless signals to take place.
The existence of ingrained biases and the resulting discrimination is a serious threat AI systems must contend with. These biases can result from imbalanced data sets or flawed algorithms, leading to biassed or erroneous judgements that could have catastrophic repercussions.
Finally, an over-reliance on AI systems poses a serious risk since it can cause dangerous complacency and, eventually, a false sense of security. This could subsequently result in a disappointing lack of attention being paid to other essential facets of cybersecurity, like user education, the application of laws, and regular system updates and patches.
