Cybercrime is the single biggest threat to enterprise and companies today, and a threat that doesn’t seem to be abating anytime soon. Despite various high level innovations, it continues to obliterate millions of dollars in man hours and data every year. In fact, according to a study by research firm Cybersecurity Ventures, the cost of cybercrime will reach USD 6 trillion every year. Not satisfied with standard malware and Trojan threats, cybercriminals today are using increasingly innovative methods to attack individuals and organisations. It is no longer enough to target a company with an indiscriminate malware attack, hackers are using updated tools to be able to identify the most vulnerable points and highest risk spaces to attack.

It’s a huge risk which needs more than just relying on traditional tools and technologies. Especially because the world doesn’t seem to have enough cybersecurity experts. Over the next two years this scarcity will reach alarming proportions, with an estimated 3.5 million vacant cybersecurity positions globally, says a Cybersecurity Ventures report. So those cybersecurity teams that are present need to deal with huge quantities of cybersecurity information and alerts generated by IT systems and networks. Looking for precise pieces information about cyber-attacks in the tons of cyber data, will need more than human effort- it will need tools like Artificial Intelligence.

Beginning with the fact that while cybersecurity tools may detect regular threats; it takes more than that to be able to detect malware that changes form. Traditional tools may miss hackers manoeuvring in enterprise systems to prepare for data exfiltration, or miss malevolent employee actions, maybe masquerading as risky data handling and system usage.

Artificial intelligence can better address many of these challenges. Its biggest strength is its ability to go beyond a rigid, robotic approach, and adapt to changing situations. It can use probabilities to draw smarter conclusions. Using Machine learning algorithms that can train systems to identify odd patterns in data and spot outliers, and can pointing out abnormal activities- cyber-attacks. Machine learning can be used to pick out indications, even very subtle or isolated ones that could point towards foul play that will eventually be a cyber-attack.

Since it is powered by computers, AI can function at the speed of computing power. With the soaring power of computing and storage, AI systems can now sift through humongous volumes of data much faster than before.  They far surpass human ability not only in terms of volume and speed, but also reliability.

However, AI cannot replace human intelligence. We still need human experts be able to factor in soft considerations like business goals and regulations, and deciding the best response to a cyber-threat. In fact, human intervention is also needed to train systems that will use machine learning, teaching them to identify the results that would help in reaching the right conclusions. With ML adding value, an AI system gets better at identifying threats as it works with more data over time, but Human Intelligence will always be a significant part of this learning process.

So it will need to be an intelligent combination of Artificial intelligence and human intelligence, if we are to be close to any success in repelling cyber-attacks.