Cybersecurity is still a growing field, but much of the investment money is being attracted to chain security and artificial intelligence (AI) to address a range of security issues.
The past year has been a busy one for startups, with investors reevaluating the rules for which companies they invest in, and large companies acquiring innovative technologies. However, focusing on a single acquisition or the formation of a startup, it's easy to miss out on investment trends.
Mach37 is an accelerator focused on cybersecurity innovation, and Datatribe is a venture capital firm focused on cybersecurity startups. From the recent announcements made by Mach37 and Datatribe, we can see the investment areas that investors are most interested in.
While Mach37 and Datatribe differ in their approach to identifying cybersecurity innovations, they are both looking for companies and technologies that can solve increasingly complex cybersecurity challenges. At the moment, people are pouring a lot of resources into anything that is labeled artificial intelligence (AI), but it will be a while before we know how these investments will play out.
mach37 focuses on scale and market consolidation as the goal is to build the potential for long-term growth for each startup. For start-up companies, the accelerator is a complex stress test. Many potential investors, early adopters, and potential channel partners want to know how the company is performing in the accelerator program before investing or partnering. Startups can benefit from mentorship opportunities, learn to develop sustainable business practices, and get help with customer queues.
Mach37 has included a range of startups offering artificial intelligence software-as-a-service (SaaS) platforms, intelligence-grade stealth, and cybersecurity intelligence platforms in its 2023 (16th) Cyber Accelerator class. In contrast, Datatribe focuses on the seed stage, seeking a more fundamental, groundbreaking shift in the field of cybersecurity and data science.
The venture capital firm recently announced the Datatribe Challenge, where seed-stage cybersecurity startups apply for up to $2 million in seed funding. The finalists were selected based on how they addressed issues such as secure logins and AI risk management. The five finalists focused on hardware bill of materials and vulnerability analysis (CERITAS), secure login and authentication (dapple security), software bill of materials and chain security (vigilant ops), serverless cops (leaksignal), and AI machine learning (ML) model scoring (Ampsight) as part of risk management.
"The winner of this challenge is Vigilant Ops, which marks a growing focus on the security of the building blocks of hardware and software products," said John Funge, General Manager of Datatribe. Companies that leverage the value of new data sets to include hardware and software bills of materials (HBOM and SBOM) are seizing an opportunity to look beyond the horizon to address the challenges posed by the increased focus on software and hardware chain security. ”
While AI may feel fresh, it has actually been a key factor in cybersecurity for years. The development and evolution of AI has shaped the direction of cybersecurity in terms of the democratization of technological capabilities and the development and use of tools. The defensive uses of AI need to evolve not only to respond to the onslaught of new threats, but also to provide a new level of continuous monitoring, and what's next for threats, looking for toxic data designed to discard AI models, detect false positives, and describe other new phenomena.
The two projects' focus on authentication, threat intelligence, and artificial intelligence tools reflects the broader cybersecurity landscape, with organizations looking for better authentication methods and improved intelligence on attacker activity. As attackers increasingly target third-party components to compromise applications and devices, chain security has also become a more important part of the discussion.
Back in 2021, nearly 75% of enterprises planned to spend their IT budgets on AI and machine learning, and now this proportion is close to 100%. Organizations have already seen the power of AI in terms of threats, defenses, and operational advancements, and now they are looking to buy.
Here, start-ups tend to outpace large enterprise solutions in terms of speed of innovation and product availability. It's an exciting time for cybersecurity startups focused on artificial intelligence, as well as investors looking for new ways to solve old problems.