Today's malware moves so rapidly that if you blink, you might miss it. The truth is, traditional security measures, such as antiviruses, are ineffective at preventing malware from infecting company networks.
According to SonicWall, there were 5.4 billion malware incidents in 2021. At the core of the challenge is the fact that by the time a human analyst detects malicious activity in the environment, it's already too late.
Deep Instinct, a cybersecurity company, has announced the release of a deep learning-powered solution; Deep Instinct Prevention for Applications, a new on-demand anti-malware solution.
Deep Instinct Prevention for Applications uses AI to scan files via API and identifys known, unknown, and zero-day threats in 20 milliseconds. It's a technique designed to protect web applications and cloud storage from malicious attackers, and can scan tens of millions of files per day.
Deep Instincts's example illustrates that deep learning might be the answer to managing malware threats that move at machine speed, and that exclude traditional antivirus solutions.
The issue with antivirus solutions
antivirus services have been a standard in endpoint security for years. Today, many businesses depend on antivirus and antimalware solutions to protect against common known threats.
The issue with these approaches is that they are often slow in comparing activity against threat intelligence feeds to determine if a piece of software is malicious. At the same time, they often overlook malicious content stored in PDF and Office files.
Deep Instinct's Director of Product Solutions, Karen Crowley, believes office files with unknown malware are very often overlooked by traditional AV and endpoint solutions. They also have a high probability of executing an attack if opened by an end user.
Traditional methods must notice the file's behavior after it executes in order to stop it, but the damage is already done, according to Crowley. Attackers are becoming more adept at avoiding sandbox and AV solutions, and files pass by undetected.
Crowley claims that Deep Instinct does not need to go to the cloud to decide whether or not an activity is malicious.
It can scan a wide range of file types, including office documents, PDFs, and.exe files, and detect malicious activity at a glance.
A look at the antivirus market
The announcement comes as the global antivirus software market continues to expand, with researchers estimating the market at $3.92 billion in 2021 and forecasting it will reach a valuation of $4.06 billion in 2022.
Deep Instincts' new antivirus product is in competition with these traditional antivirus solutions, and is aiming to provide an alternative strategy for securing enterprise environments from advanced unknown malware threats.
The provider is in a good position to strengthen its position in the market, having raised a $67 million extension to its Series D funding round last year, which had already closed at $100 million the same year.
McAfee is the primary antivirus vendor competing against Deep Instincts' product. The company measures and manages malware, phishing, viruses, and ransomware, and performs malware detection, quarantine, and application removal.
McAfee announced in October that it would increase net revenue of $2.9 billion in 2020.
Norton, which just announced that it would raise $702 million in the third quarter of FY 2022, is a key competitor. It uses artificial intelligence and machine learning to detect malware, spyware, viruses, and ransomware.
Crowley claims that the use of deep learning distinguishes him from competitors when it comes to differentiation.
Deep Instinct's deep learning-based solution is based on the industry's only deep learning framework developed to fill the gaps in cybersecurity today. There are specific advantages that deep learning brings that enable Deep Instinct to prevent threats faster in 20ms, ensuring we are faster than the malware, according to Crowley.