When it comes to artificial intelligence, there are two camps. The first camp is an advocate, promising a big, positive future for AI. The other camp is not so optimistic.
AI for cybersecurity – The good
Cybersecurity experts have reiterated on several occasions that passwords are extremely vulnerable to hacking, compromising financial and personal information. With the introduction of biometric logins, artificial intelligence is making a positive contribution to cybersecurity.
Security breaches and malicious activities can also be detected using AI. Conventional systems cannot keep up with the sheer number of spam ware and malware that is created every month, and AI can step in and help fight this problem. Cybersecurity companies are already training their AI systems to identify malware and viruses through complex algorithms.
AI-run systems unlock potential for natural language processing (NLP) that collects information automatically by combing through data, news, and studies on known and potential cyber threats. Knowledge of this can give insight into developing robust prevention strategies, stay updated on the latest risks, and design responsive strategies for keeping companies organized.
AI for cybersecurity – The bad
An immense amount of memory, computing power, and data are required to build and maintain an AI system. Moreover, since the systems are trained through learning data sets, cybersecurity firms need to procure different data sets from various resources. This is a time and cost-intensive approach that some companies cannot afford.
AI is not just used by companies, but also by hackers for testing their malware. An AI-proof malware can be extremely destructive – being able to penetrate conventional systems or even AI-boosted systems.
Considering these limitations, AI is a long way from becoming a dedicated cybersecurity solution. The optimal approach is to combine it with traditional techniques, to get the best of both worlds.