I was under no illusion that nowadays data is everywhere and I have grown up with the rise of its importance to artificial intelligence (AI) and cybersecurity, but perhaps never fully appreciated its value until reaching my adult years. I certainly never fully appreciated its potential until being employed into the data industry last year. Coming from a media and marketing background my most prominent experience of AI up to now had been Google Assistant! Yet IDC forecasts that the AI market will grow to $52.2 billion in 2021 and McKinsey estimates AI techniques have the potential to create between $3.5T and $5.8T in value annually across nine business functions in 19 industries.
Using AI for cybersecurity solutions can help develop protection from existing cyber threats and in turn, could help to identify newer malware types and predict possible future malware strains. AI in cybersecurity can spark new standards to allow for far more streamlined and ever-evolving prevention and recovery strategies against malware. Cybersecurity policed by AI will give rise to data-driven security models that detect threats through multiple data sets inclusive of algorithms and codes; learn with automatic scanning systems to collect studies and news on cyber threats through natural language processing; and create real-time global authentication that can alter access rights based on location or network.
There are of course though, limitations to the implementation of AI into cybersecurity. Building and maintaining an AI-powered system requires vast resources and since AI systems are trained with data, new datasets of malicious codes and non-malicious codes regularly need to be fed in to help AI learn. By developing advanced data search and discovery across an organisation, we are starting to see that finding and collecting these accurate datasets may no longer be a time-consuming task. However, as the Envitia team will tell you, helping customers get accurate, up to date, and good quality data to enable exploitation through the use of AI applications is vital to the prevention of inaccurate data providing inefficient outcomes.
Throw into the mix the risk of hackers using AI to test their own malware in a much similar way to the rigorous testing for implementing AI into cybersecurity in the first place. With constant testing, we could see the development of AI-proof malware strains, and if you consider the malware risks we already face today, the thought of AI-proof malware is a destructive one. We assume that investment into AI for malicious and criminal purposes is as powerful a return on investment as it is for defence security reasons.
Cybersecurity, as advanced as it may be today, still leaves every organisation prone to cyber-attacks, even the tech giants of the world that use state of the art security systems are susceptible to cyber threats. AI is unique in that it is an emerging technology itself yet it is primarily being used today as an enabler for other emerging tech. This could mean that the answer for cybersecurity may come from AI developments in emerging fields like autonomous vehicles and IOT as it looks to help improve decisions through better data analytics.
There are steps to be made before AI provides a standalone cybersecurity solution but with research and development, applications that use AI for cybersecurity will soon become common practice. A cyber-secure world policed by AI.
Written by Luca, Junior Sales & Marketing Executive
