IoT Identification & Security –Personality-based IoT Approach
Enabling the Internet of Trusted Things can be like opening Pandora’s Box. We are offering one of the industry’s first and only IoT security solution platforms to leverage the individual personalities of IoT devices to provide accurate visibility and protection of an organization’s IoT assets.
Our platform leverages machine learning to discover IoT devices, assess risk, baseline normal behavior, detect anomalous activities, and provide real-time remediation across an organization’s entire IoT footprint.
Traditional security solutions rely on recognition of operating systems, plugins, and installed applications to classify and provide device contexts. Unfortunately, context for IoT devices are not well understood. Identifying X-ray machines, industrial automation systems, or point-of-sale devices simply as Windows-based devices offers little insight into how best to manage and secure these devices.
The risks of a device, according to traditional security solutions, are often calculated by comparing the device behaviors against the normal/trusted behaviors of a typical user. Such patterns are often used to detect viruses. Unfortunately, this approach cannot be applied to IoT devices. To accurately assess risk to IoT devices, the security solution must have full knowledge of the device including its trusted and intended behaviors. Without such details, many organizations are relying on inaccurate risk assessments of their IoT assets.
Traditional security solutions rely on tools such as Enterprise System Management (EMS) for laptops and Mobile Device Management (MDM) for mobile devices to manage and upgrade end-point devices. These solutions ensure that the latest patch and best-practice configurations are enforced. Unfortunately, this approach is not applicable to IoT devices. IoT devices are purpose-built and not designed to be serviceable by end-users. Any attempt to upgrade their software or even impede their communication can lead to unpredictable behaviors.