No sector is immune from cyber attacks and attackers do not discriminate against size of organisation. The objective may be financial or even political, what is certain is that the increasing level of sophistication means that they present some of the most the most strategically significant risks to business today.
Cybersecurity is driven by the need to remain one step ahead of the attacker. As a business transforms digitally by harnessing artificial intelligence and machine learning, its cyber weaponry needs to transform with it if it is to have a perpetual edge on cyber threats.
Awareness of the threat
In 2017, the WannaCry ransomware attack marked the beginning of a new era in cyber attack sophistication. The speed of the attack paralysed systems as it moved laterally through an organisation in a matter of seconds, affecting some 150 countries around the world. The incident has already inspired multiple other copycat attacks.
As a result, cyber security is changing and CISO’s need access to a growing repertoire and sophistication of tools at their disposal. When it comes to prevention, nothing else offers the same level of sophistication as artificial intelligence – or AI-based threat protection.
Enter AI threat detection
In the early 1990s there were 400 new threats each month, so updating signature-based systems was maintainable and manageable. In 2019 there are now a reported 400,000 new threats every twenty-four hours so updating signatures takes too long.
There are some six million common characteristics within malware files that have been identified. Now, AI-based cyber security can use this information within core algorithms to produce a predictive model that can identify good and bad traits of a file even if a signature changes. Traditional signature-based methods offer 60–70% protection against known and unknown threats but using these new AI-based security tools that learn as they go along, protection can be increased to 99.7%.
As well as detecting the threat, AI-based security can include automated quarantining and orchestration as well as advanced reporting, which can lead to remediation strategies. For example, by identifying how a threat came into the network, where it came from and what it did across the system, the machine learning model is constantly learning and evolving to improve protection levels. It can then automatically update endpoints with the relevant protection.
AI boosts productivity
By helping to eliminate false positives, AI can aid the processing of suspicious files as it avoids flooding IT teams with alerts. Instead, the role of humans is augmented, taking some of the ‘heavy lifting’ away from them, which is better suited to a machine and improving productivity in the process.
What is the future of cybersecurity?
Continuing advances in AI-enabled tools will take security from a reactive operation to a predictive one, greatly reducing the risks of advancing threats. With the introduction of AI, time is finally on the side of the defender as it can often help predict an attack before it occurs. When the malware does turn up, the enterprise is already protected.
However, it’s important to remember that as security professionals advance machine learning defensively, attackers will adopt the latest AI and machine learning techniques for the dark web. Whether DDoS attacks, ransomware or some other kind of malware, a threat actor can use AI to spread the threats faster and target more vulnerable machines through automation. The only way to combat the malicious use of AI is with AI itself. Therefore, adopting AI as part of a business’ toolkit is essential as the technology advances.
Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located IoT Tech Expo, Blockchain Expo, AI & Big Data Expo and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London and Amsterdam and explore the future of enterprise technology.