Sam Linford

Cyber Magazine speaks with Deep Instinct's Sam Linford on reducing the cycle of stress in security teams and using AI to reduce productivity challenges

Q. TELL ME ABOUT DEEP INSTINCT AND HOW IT HOPES TO REDUCE STRESS IN SECURITY TEAMS?

» Deep Instinct, founded in 2015, is the first company to apply end-to-end deep learning to cybersecurity. Our deep-learning framework is one of only six in the world, and, furthermore, is the only purpose-built deep-learning framework dedicated to cybersecurity. Through our deep-learning solution, we shift organisations’ focus from responding to cyberattacks to preventing them, preexecution. Our deep-learning brain can also go one step further by stopping zero-day malware and ransomware threats, with both superior accuracy and speed compared to other endpoint protection platforms (EPP).

Thanks to our advanced solution, we are able to take the stress and pressure off security teams by stopping the fastest cyber-attacks before they enter the network or compromise endpoints, causing irreversible damage.

Q. WHY IS THERE SO MUCH STRESS AND PRESSURE PLACED ON THE C - SUITE, AS WELL AS THE FEAR FELT BY THOSE WHOSE DECISION IT IS TO PAY RANSOM DEMANDS?

» The cyber-threat landscape has grown exponentially, and the task of protecting networks against sophisticated cyber-attacks becomes increasingly difficult. Ultimately, the pressure felt by cybersecurity professionals has resulted in them not only leaving their employer, but the industry itself.

Deep Instinct’s research has shown that 49% of UK professionals have considered quitting the industry due to stress, with the unrelenting threat from ransomware and the fear of the next supply chain attack the primary factor. Compounding the situation, nearly half felt their stress had measurably increased over the last 12 months.

It is not only the fear of when an attack will come, but the pressures exerted when a ransomware attack hits. When ransomware attacks breach an organisation’s network, correct decision-making is crucial – it can be the difference between an enterprise surviving a cyberattack unscathed or it costing millions. This pressure normally ends up falling into the laps of C-suites and security leaders, and, unfortunately, not all can handle the pressure.

Q. HOW CAN ORGANISATIONS STOP A CYCLE OF STRESS AND PREVENT THEMSELVES FROM BECOMING THE VICTIMS OF RANSOMWARE ATTACKS IN THE FIRST PLACE?

» Clearly, the mindset of reacting to and mitigating cyberattacks is not working – ransomware attacks are continuing to grow in number, and this is pushing people away from the cybersecurity industry. EDR tools that work on a reactive and mitigation approach are increasingly being evaded by the latest malware and techniques used by threat actors, and these solutions alone are therefore not enough to guarantee protection against such attacks.

As such, organisations should flip their mindset by looking to prevent ransomware attacks: having a preventionfirst cybersecurity strategy means that security teams are able to stop ransomware attacks before they encrypt files and data. This would immediately lift the stress off security teams, as they would no longer feel like sitting ducks waiting for the inevitable ransomware attack to hit and wouldn’t have the pain of trying to recover their stolen data.

Once there is acceptance, you then need to start implementing solutions that will help encourage a prevention-first strategy.

AI has proven to be an extremely useful tool in shifting an organisation’s mindset towards prevention-first. There is a consensus among cybersecurity professionals that AI-enabled tools are highly effective against sophisticated ransomware attacks.

Our research has backed this claim up, with 47% agreeing that “they need greater automation through AI/ML to improve security operations”, and 79% saying they would rather depend on AI than humans to hunt threats.

Q. WHY IS AI RECOGNISED AS HAVING THE POTENTIAL TO REDUCE CRITICAL PRODUCTIVITY CHALLENGES? WHAT CHALLENGES CAN IT HELP WITH?

» While conventional machine learningbased security can provide support against known threats, it does have its limitations when it comes to zero-day threats and false positive rates.

Therefore, organisations need to look towards advanced AI-based solutions such as deep learning, which can accurately prevent ransomware threats in real time with little human input. Deep learning is developed through neural networks that are designed to mimic the human brain. The neural networks are trained on massive sets of raw data samples consisting of millions of files, with the deep-learning “brain” independently teaching itself to detect which files are malicious and which ones are benign.

This results in the extremely intelligent system being able to stop the fastest known ransomware attacks in less than 20 milliseconds – even including unknown and zero-day threats. By preventing ransomware attacks, security teams can finally end the stressful situation of detection, response, and mitigation.

Q. WHAT'S NEXT FOR DEEP INSTINCT?

» Deep-learning technology has recently come into the mainstream with some of the biggest tech giants – such as Google, Netflix, Amazon, and Tesla – now using it to support their services. As we continue to develop deep learning, cybersecurity will be seen as the natural evolution of the technology.

We at Deep Instinct will continue to push the message of using deep learning to help support a prevention-first mindset. We will continue to adapt the solution to fight against future cyber threats across endpoints and also data in transit with our new Prevention for Applications solution.