CyberSwarm: first of its kind hardware-based security

15 Most Promising Enterprise Security Startups - 2018

The ever-evolving nature of cyberattacks necessitates organizations to constantly update their enterprise security strategies. While big data adoption is on the rise, organizations are also being posed with a new set of security challenges that include striking the right balance between monetizing strategic data assets and protecting personal privacy interests. Furthermore, a majority of security professionals predict that hackers will leverage AI to launch more sophisticated cyberattacks along with exploiting IoT ransomware to cause substantial damage.

Although multi-factor authentication is being increasingly adopted by organizations to avoid basic data breaches involving weak or stolen passwords, there is a need for more sophisticated security technologies. By running the data streaming in from networked access control systems through strong analytics, enterprise security startups promise to help organizations pinpoint hidden trends and threats that human-based security systems might fail to notice. Endpoint detection and response (EDR) solutions, for instance, are capable of monitoring endpoints and sending alerts to security administrators upon detection of anomalous behavior of any kind.

In addition to governments carrying out regulatory changes and tightening security standards, enterprise security startups have started to offer innovative solutions for auditing changes in real time. Not only will this help protect critical assets in multiple ways but organizations can also detect alterations, deletions, inactive user accounts, and a lot more.

Our distinguished panel comprising CEOs, CIOs, VCs, and the editorial board has reviewed the top companies in the enterprise security startups space and shortlisted the ones with proven business process knowledge coupled with extensive and futuristic cybersecurity strategies.

We present to you “15 Most Promising Enterprise Security Startups - 2018.”

15 Most Promising Enterprise Security Startups - 2018

    Top Enterprise Security Startups

  • Delivers Security Information and Event Management (SIEM) on-premise or as a SaaS service

  • Provides decentralized cloud security and storage with protection from external, viral, operational, internal and surveillance threats

  • Provides a SaaS solution that enables continuous improvement of an organizations cybersecurity posture and manage an effective cyber strategy

  • Helping people and organizations safeguard their assets, data, and resources in cyberspace

  • The company provides a security management intelligence platform focused on Security Orchestration and Automated Response (SOAR)

  • CyberSwarm is developing a CPU specialized for cyber security which empowers every device to defend itself in case of a cyber attack

  • Provides next generation security solutions for the next generation internet protocol

  • Fortify 24x7 offers an array of best-of breed cybersecurity solutions and services for businesses

  • Introduced first-of-its-kind multi-dimensional and multi-layered visibility and control for containerized applications

  • With its unique tool, Lucy allows businesses to test their security and help it evolve against cyber threats on both the people side and the system side simultaneously

  • Provides state-of-the-art decentralized authentication and digital identity management solutions

  • PolySwarm is the first decentralized marketplace where security experts build anti-malware engines that compete to protect you

  • Centripetal Networks

    Centripetal Networks

    Offers a purpose-built hardware platform that uses real-time network defense to provide visibility and identify threats indicators at scale

  • HYPR


    HYPR is the leading provider of decentralized authentication with millions of password-less users secured across the globe

  • ThetaRay


    Provides faster, more accurate analytics solutions for identifying emerging risk, discovering new opportunities, and exposing blind spots within large, complex data sets