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Today’s malware moves so fast that if you blink, you might miss it. The reality is that traditional security solutions like antiviruses are ineffective at preventing malware from infecting enterprise networks.
According to SonicWall, there were 5.4 billion malware attacks in 2021. At the heart of the challenge is the fact that by the time a human analyst detects malicious activity in the environment, it’s already too late.
In an attempt to combat malware threats, cybersecurity provider Deep Instinct 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 scan files via API and identifies known, unknown and zero-day threats in <20 milliseconds. It’s an approach designed to protect web applications and cloud storage from malicious attackers, and can scale to scan tens of millions of files per day.
For enterprises, Deep Instinct’s solution highlights that deep learning could provide the answer to responding to malware threats that move at machine speed, and fsidestep the defenses of traditional antivirus solutions.
The problem with antivirus solutions
When it comes to security solutions, antivirus tools have been a staple in endpoint security for years. Today, many enterprises rely on antivirus and antimalware solutions to protect against common known threats.
The problem with these solutions is that they are often slow, comparing activity against threat intelligence feeds to identify if a piece of software is malicious. At the same time, they often miss malicious content stored in PDF and Office files.
“Office files with unknown malware are very often missed by traditional AV and endpoint solutions and have a high probability of executing an attack if opened by an end user,” said Director of Product Solutions at Deep Instinct, Karen Crowley.
“Traditional solutions must see the behavior of the file after it executes to stop it – but by then, the damage is already done. Attackers are getting smarter at evading sandbox and AV solutions and files pass by undetected,” Crowley said.
Crowley says that by building its deep learning capability from the ground up, Deep Instinct doesn’t need to call out to the cloud to decide whether activity is malicious or not.
It can automatically scan a broad range of file types, including office files, PDFs, and .exe files and detect malicious activity at machine speed.
A look at the antivirus market
The announcement comes as the global antivirus software market continues to grow, with researchers valuing the market at $3.92 billion in 2021 and anticipating it will reach a value of $4.06 billion in 2022.
Deep Instinct’s new solution is competing against these traditional antivirus solutions, and aiming to provide an alternative option for securing enterprise environments against advanced unknown malware threats.
The provider is in a strong position to advance its position in the market, having raised a $67 million extension to its Series D funding round last year, which already closed at $100 million that same year.
One of the main antivirus providers competing against Deep Instinct’s offering is McAfee, which protects Windows, Mac OS, Android, and iOS devices, from malware, phishing, viruses, and ransomware with malware detection, quarantine, and removal, and scheduled file and application scanning.
McAfee most recently announced raising net revenue of $2.9 billion in 2020.
Another key competitor is Norton, which recently announced raising $702 million in the third quarter of FY 2022, and uses artificial intelligence and machine learning to identify malware, spyware, viruses and ransomware.
When it comes to differentiation Crowley argues that the solutions use of deep learning separates it from competitors.
“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 which enable Deep Instinct to prevent threats faster in <20ms, ensuring we are faster than the malware,” Crowley said.
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