Analyst firm Gartner has listed top 10 security technologies which should be adopted by the organizations to win the cybersecurity battle in 2016.
There is an estimate that globally, by the end of 2019, data breaches could cost us an approximate $21.1 trillion, and that’s why it is imperative for organizations to evolve and stay sharp for protecting their data and business. Let’s take a brief look at the 10 ten technologies recommended by Gartner.
1. Cloud Access Security breakers: CASB assists in rendering a control point for using cloud services across multiple cloud providers. They help in managing risks over the entire set of cloud services.
2. Pervasive Trust services: Trust services help in scaling and supporting the needs of devices with limited processing capabilities. They also assist in providing secure provisioning and protecting device identity.
3. Deception: Deception capabilities create fake vulnerabilities and systems to throw off the attacker’s automation tools and attack their cognitive processes.
4. Intelligence-driven security operations center: An intelligence-driven SOC moves beyond traditional defenses and deploys security mechanisms in sync with the attacker’s systems.
5. Remote Browser: Remote browser helps in keeping the malware at bay by isolating the browsing function from the rest of the network which in turn reduces the surface area for the attacker.
6. Security Testing for DevOps: DevSecOps make use of the underlying security blueprints, scripts, and templates to render protective measures at the very basic level. This strengthens the base which results in lesser malware penetration.
7. Microsegmentation and flow Visibility: After entering the system, it is easy for the attackers to move towards other systems, Microsegmentation intends to hinder the moving flow and curb the situation as it is, without affecting other kindred systems.
8. User and entity behavioral analytics (UEBA): Enabling broad-scope security analytics, UEBA renders user-centric analytics around user behavior. The correlation between the analysis helps in effective monitoring and removal of threats as and when detected.
9. Non-Signature approaches for endpoint prevention: Because signature-based approaches are ineffective against advanced or targeted attacks, Non-signature approaches adopt a different approach which helps in identifying threats at the initial stage.
10. Endpoint Detection and Response (EDR): Recording numerous endpoint and network events, machine learning is put to use for searching data to ensure early identification of breaches.
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