The Indispensable Enabler: Cyber Security for IoT

The broad range of assets in use by industry drive the need for a scalable, automated system for monitoring and prediction. Human-oriented data science approaches take too much time, rely on hard-to-find talent and require custom model building for each type of asset. In many instances, the problem is further compounded because large differences in operating conditions, maintenance schedules and load patterns can drive model proliferation; the need for different models for the same type of asset. With fifty billion connected devices expected to be online by 2020, the continuing militarization of computer security, Cloud computing shifts and Mobile access enablement, security is more critical and complicated now than ever before. Yet, existing approaches such as signature-based detection, whitelists and blacklists and SIEM (Security information and event management) systems only address part of the problem. Many threats still escape detection, often despite the fact that they’ve left behind a pattern that is waiting to be found. The most innovative solutions will be Cognitive, data-driven Analytics platform for Clouds, Devices and the Internet of Things industrial and security market that deliver out of-band, symptom-sensitive analytics, insights, and security.