How Deep Learning for Cybersecurity Is Freeing CISOs to Prepare for What's Next
Companies are constantly playing defense against the latest vulnerabilities and cyber threats. New malware variants appear by the second, and tried-and-true attack methods, like phishing and social engineering attacks, remain pervasive.
CISOs, board members, and the general public are well-aware of the dangerous cyber landscape. Yet in the past two years, 60% of businesses have experienced a serious security breach – 31% more than once – according to a recent survey. Advanced persistent threats keep security teams spinning their wheels, trying to hunt, identify, analyze, and remediate in a never-ending cycle. Existing tools based on signatures, heuristics, and reputation tracking are overwhelmed by the sheer volume and the ability of attackers to evolve and bypass defenses.
It’s time for security teams to take another look at prevention vs. remediation, taking advantage of emerging security tools to block attacks before they get downloaded and detonate. Thanks to recent advances in deep learning technology, CISOs can go beyond the prevailing “remediation-first” mindset and achieve the coveted ideal of preventing attacks with near 100% certainty. It may sound like hyperbole, but the technology has been tested and proven and is reimagining cybersecurity for the better.
Where Detection Falls Short, Prevention Enhances Cyber Defenses
By preventing threats, CISOs gain a significant opportunity to reduce wheel spinning and increase the ROI of the business, securing the company’s future while also protecting customers and their data.
Advances in deep learning technology are freeing CISOs from the flood of real breaches and false positives and providing a way to protect the entire attack surface. Deep learning tools are able to block known and unknown threats within milliseconds, before they can download and write to disk. Recently, independent evaluator SE Labs, pitted security provider Deep Instinct’s deep learning solution against a range of high-profile, known malware campaigns and a selection of unknown targeted attacks. The results were eye-opening.
Deep Instinct’s D-Client faced up against malware from well-publicized breaches, fileless targeted attacks, exploits targeted at Microsoft file format vulnerabilities, targeted shellcode injection attacks, and more.
Each threat was successfully prevented pre-execution with no other processes running — resulting in an industry-first 100% prevention rate and zero false-positives. Attackers have learned how to adapt to get past security tools, but now deep learning can act even faster, making zero-time prevention fact rather than a hoped for reality.
Putting CISOs in Full Control of the Security Environment
By adding a deep learning driven pre-emption layer to their environment, CISOs can go beyond sandboxes and signatures to enable threat prevention that hackers cannot evade. Adopting security tools that can detect threats before they execute is also a great enabler of digital transformation. Companies will inevitably need to offer customers more digital products and services and keep sensitive data under lock. The result is increased ROI for the IT department and the company as a whole
When security teams can rely on a tool that can anticipate, identify, and pre-empt threats with confidence, they can shift energy away from remediation and focus on being strategic enablers of business growth. Deep learning driven cyber security can enable zero-time prevention and put CISOs in control — blocking attacks, eliminating false positives and bringing relief from known and unknown threats.
Learn more about Deep Instinct’s solution and how it stood up against known and unknown threats in testing by SE Labs. Get the report here.