Privacy and security must be designed into the deployment

AI video analytics can operate in environments where employees, visitors, patients, students, contractors or customers may appear in camera views. RIFE therefore treats privacy, data handling and cybersecurity as part of the technical design—not as an afterthought added after installation.

Because RIFE EDGE AI projects can use different hardware, software components and deployment models, the exact controls are documented for each project. This page explains the design principles used during that process.

Privacy by design

• Purpose limitation: define why the camera is being analysed and which events are actually required.
• Data minimization: collect and retain only the images, clips, metadata or logs required for the agreed operational purpose.
• Local processing where appropriate: edge or on-premise processing can reduce the need to transport raw video outside the site.
• Privacy zones: exclude areas that are not necessary for the use case where the selected platform supports this control.
• Masking or redaction: face or scene masking can be evaluated when required and supported by the selected deployment.
• Role-based visibility: restrict who can view live feeds, events, evidence and administrative settings.

What data may exist in an AI video analytics system?

Depending on configuration, a deployment may process live video, camera identifiers, timestamps, event metadata, confidence scores, snapshots, short video clips, user activity logs and system-health data. Not every project needs to retain all of these categories.

RIFE recommends defining the data inventory before production deployment so that the customer knows what is processed, what is stored, where it is stored and who can access it.

Data retention

RIFE does not publish one fixed retention period for every customer. Retention depends on operational need, customer policy, storage capacity, contractual requirements and the selected software architecture.

A mature retention policy should specify separate rules where required for:

• Event images
• Event video clips
• Event metadata
• System and user logs
• Backups

Where supported, retention can be configured so that data is automatically removed after the agreed period.

Cybersecurity architecture

Security is a shared responsibility across cameras, network infrastructure, RIFE compute, operating systems, applications and customer access. The project design may include:

• Network segmentation between camera, server and user networks
• Firewall rules based on documented communication requirements
• Authenticated administrative access
• Least-privilege user roles
• Encrypted communications where supported and configured
• Controlled remote-access methods
• Audit logs where supported by the deployed software
• Software update and vulnerability-management procedures
• Backup and recovery planning for critical configurations

Exact protocols, encryption standards, identity providers and authentication methods should be confirmed in the technical schedule for the chosen product stack.

Employee, student and patient privacy

For workplaces, schools and healthcare environments, AI should be deployed around a clearly documented safety, security or operational purpose. Camera placement, signage, access permissions, retention and use of identifiable footage should be reviewed against customer policy and applicable legal requirements.

RIFE can design the technology architecture, but the customer remains responsible for determining the lawful basis, notices, internal policies and governance obligations applicable to its organization and location.

Questions procurement and IT teams should ask

1. Does raw video leave the site?
2. Which data categories are retained?
3. Where is each data category stored?
4. Who can view live video and event evidence?
5. How is remote support controlled?
6. Which network ports and outbound services are required?
7. How are user actions logged?
8. How are software updates managed?
9. What happens to stored data at the end of the contract?

Related RIFE EDGE AI resources

Trust & Technology Center · Architecture · Deployment & Support · Pilot Program

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