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otto Emerges From Stealth Mode, Announcing Breakthrough in Machine Learning for Malware Detection

April 12, 2022 at 06:00 AM EDT

ⓘ This article is third-party content and does not represent the views of this site. We make no guarantees regarding its accuracy or completeness.

Using machine learning to combat sophisticated attacks and a user-friendly 'Inbox Zero' interface, ottoBox brings security solutions to technical and non-technical teams.

ottoBox user interface
ottoBox user interface inspired by inbox zero methodology wants to make managing security alerts easy for technical and non-technical teams.

ATLANTA - April 12, 2022 - (Newswire.com)

In response to record-high cyberattacks and unprecedented global shortages in security staff, cybersecurity startup 'otto' announces the release of its automated JavaScript security platform, ottoBox. Using machine learning to combat sophisticated attacks coupled with its user-friendly 'Inbox Zero' interface, the company aims to empower technical and non-technical teams with a highly effective security solution that is easy and intuitive.

"As industries have grown more dependent on third-party scripts and open-source libraries, these connections have become a popular and profitable target for attackers. The advanced malware they are using is hard to detect and is mutating far too quickly to mitigate with blocklists alone. Developing machine learning detection is critical." said Co-founder & CEO Maggie Louie

otto's breakthrough advancements in machine learning

In early 2020, otto raised a $2 million seed round to develop its patented security solution, ottoBox. The core technology is powered by the company's breakthrough advancements in machine learning for malware detection, capable of predicting malware with 93 percent accuracy.

Before joining the founding team at otto, Josh Summitt, Co-founder, and CTO led Bank of America's Application and Data Security Team and worked for several years alongside legendary hacker Kevin Mitnick developing pen-testing experiments for the financial services industry.

Speaking to the breakthrough technology, Josh said, "Automated malware detection is tricky to achieve with machine learning due to many factors. Having the corpus of relevant and diverse malware samples was a big part of overcoming the barriers and producing something unique in the market."

otto Chief Product Officer, Chad Fowler, former CTO of Wunderlist and architect at Living Social, Fowler led the vision of ottoBox's user interface and functional design to embody an "Inbox Zero" methodology, to support teams that are severely short-staffed in cybersecurity.

"The problem with most cybersecurity and threat detection tools is they require a lot of security expertise to understand, let alone manage. Even security experts spend hours in conventional tools trying to review and classify thousands of requests to figure out which represent risks. It seemed like the industry needed something intuitive and automated, so you don't need all the charts and analytics. Instead, you have a very practical solution for teams needing to move quickly and get back to their core jobs," said Fowler.

Press Release Service by Newswire.com

Original Source: otto Emerges From Stealth Mode, Announcing Breakthrough in Machine Learning for Malware Detection

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