At the Cyber Security & Data Protection Summit, in November, we welcomed Justin-Vaughan Brown, VP Product Marketing and Communications at Deep Instinct to analyse and explore the deep learning-driven, prevention first approach to ransomware.
Public sector organisations are facing challenging times:
- 57% see unknown malware as the primary factor limiting threat prevention
- Over 50% quote the sheer volume of unknown malware as the biggest barrier to detection
- 24.4 hours is the average time to respond to a security incident – over 3 working days
- Traditional AV technologies missed nearly 75% of Q1 2021 malware
- Critical infrastructure, healthcare and government offices are seen as high impact targets
This session looks at ways to address this “perfect storm” of increasing attack volumes, expanded threat vectors and a targeted focus on public sector bodies. It highlights the opportunities deep learning brings to prevent ransomware and other malware in <20 ms before an attacker can gain persistence.
View the session in full here:
Deep Instinct takes a prevention-first approach to stopping ransomware and other malware using the world’s first and only purpose-built, deep learning cybersecurity framework.
They can predict and prevent known, unknown, and zero-day threats in <20 milliseconds, 750X faster than the fastest ransomware can encrypt. Deep Instinct has >99% zero-day accuracy and promises a <0.1% false-positive rate. The Deep Instinct Prevention Platform is an essential addition to every security stack—providing complete, multi-layered protection against threats across hybrid environments.
Read the Ransomware ebook from Deep Instinct
Piers Kelly
Experienced Marketing Manager with a demonstrated history of working in the events services industry. Enjoys writing on Cyber Security, Emerging Tech & Digital Transformation. Marketing professional with a Bachelor of Arts (BA) in Politics and Economics from Newcastle University.
