Corporate cybersecurity today is tasked with protecting connected hardware and cloud-based software from a myriad of threats, with present day threat actors leveraging AI and advanced techniques to gain access to corporate networks, interrupt business operations, and steal proprietary or sensitive data. The next generation of cybersecurity tools leverage AI and ML to combat these evolving threats across cloud networks, applications, endpoints, and operational technology.
The traditional enterprise network perimeter is fading, and enterprise workflows are increasingly reliant on the internet and cloud applications. Businesses often rely on multiple cloud platforms from different providers, distributing their workloads, data, and applications across not only private networks but also public cloud infrastructure, leaving many potential entry points for malicious actors. Operational technology, such as manufacturing equipment, critical infrastructure, and healthcare devices, are also growing increasingly connected across all industries, providing cybercriminals yet another expanding target. This evolving threat landscape requires a holistic approach to cybersecurity that considers an organization's entire network landscape.
The growing demand for proactive cybersecurity solutions in response to evolving threats has resulted in the adoption of different types of security products across a wide range of sectors including financial services, information technology, healthcare, industrials, and utilities.
Cybersecurity solutions serve multiple purposes, including improving visibility into cloud networks and connected IoT devices, managing access to corporate networks, and enhancing threat detection and response workflows. Numerous organizations have observed measurable advantages, such as cost savings, quicker turnaround times, and reduced manual efforts as they deploy these solutions in their workflows.
We have identified key next-gen cybersecurity use cases below:
Large incumbents maintain a strong presence in this industry as they expand traditional cybersecurity portfolios with complementary products focused on cloud services produced through a mix of internal development and acquisitions. Some larger disruptors also follow an acquisition strategy, acquiring smaller startups to expand their portfolios. These acquisitive incumbents and larger disruptors are therefore listed across multiple segments of the market map.
The endpoint security space, in particular, has a significant incumbent presence, as traditional antivirus software vendors are adding behavior analytics and artificial intelligence to their products. Symantec (now owned by Accenture) and Trend Micro are some of the largest endpoint protection providers globally, each claiming more than 18% of the segment’s overall market share.
While the market map features more endpoint security companies than any other segment, companies offering cloud security products have attracted the most private funding—more than USD 7.1 billion for the cloud network and cloud-native application security segments as of August 2021. Further, nine out of ten startups in this hub were established over the last decade and have collectively raised over USD 12 billion as of the same date.
The cloud service providers, pureplay cybersecurity companies, and endpoint security software providers in this section have either acquired stakes in next-gen startups, or pivoted their business model to offer products and services across multiple segments.
Major cloud providers like Microsoft and Fastly generally bundle security products along with their primary offerings. Pureplay cybersecurity incumbents, such as Palo Alto Networks, have been gradually building their product portfolio to keep up with industry trends, using acquisitions to bridge gaps and speed up go-to-market activities.
Incumbents in the endpoint security segment have historically offered traditional antivirus software to retail and enterprise customers. These companies have improved their offering to feature AI and behavior analytics to detect known and unknown threats. These companies have also started building endpoint detection and response (EDR) tools to leverage automation and machine learning.