Turning Zero-Day into D-Day for Cybersecurity Threats

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Creating Zero Tolerance for Zero-Day Threats

With zero-day threats becoming a major factor in breaches, it is imperative to protect against the vulnerabilities caused by the difficulty in detecting them, as well as by the time lag between detection and prevention.

Detecting and blocking zero-day attacks is no easy feat. Legacy, signature-based methods cannot handle zero-day threats in real time because they require time-consuming, manually tuned heuristics to be able to detect them. Newer methods that evaluate zero-day exploits in a protected sandbox environment also fail to block threats in real time. More advanced solutions using artificial intelligence machine learning come to fill the void of real-time detection and prevention, but the detection accuracy issues that arise affect the efficacy of the protection they offer.

Deep learning as a cybersecurity solution brings a new proactive and predictive approach that effectively combats these security gaps abused by attackers. By leveraging deep learning, new, undetected threats are instinctively identified and blocked in real time before they can be exploited and cause harmful breaches. It's D-Day for zero-day attacks when a solution can defeat them by blocking them before they can be carried out.

"Zero-day" is a term used to describe the culprit behind many of the security breaches we hear about almost daily  in the news. But what exactly does it mean? Zero-day — the first or "zeroth" day — refers to the point in time a security hole in code is revealed to hackers or cybersecurity professionals (e.g., a developer, researcher, software programmer).

The term comes from the Warez scene (warez being slang for wares — an abbreviation for computer software) where computer underground circles distribute unauthorized releases of copyrighted work on the same day as (or even before) the original product is released.

While that is the basic definition, zero-day threat is commonly used to describe two cases:

  • Zero-Day Vulnerability: This refers to a security flaw in software, an application or operating system that has yet to be revealed to the software maker or antivirus vendors, though the vulnerability may be known to attackers. Because zero-day vulnerabilities have yet to be discovered, the vulnerability is not yet protected by a known signature or patch, leaving companies vulnerable to attacks.
  • Zero-Day Exploit: This refers to code that attackers use to trigger the zero-day vulnerability to execute their malicious action into the vulnerable software, application or operating system. Since this is done unbeknownst to the victim, it is a critical cybersecurity threat.

In this slideshow, Guy Caspi, CEO of Deep Instinct, takes a closer look at the explosion of zero-day threats and how deep learning can help organizations better protect their valuable cyber assets.


Related Topics : Unisys, Stimulus Package, Security Breaches, Symantec, Electronic Surveillance

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