18187520. TELEMETRY DATA BASED COUNTERFEIT DEVICE DETECTION simplified abstract (Cisco Technology, Inc.)

TELEMETRY DATA BASED COUNTERFEIT DEVICE DETECTION

Organization Name

Cisco Technology, Inc.

Inventor(s)

Shi-Jie Wen of Sunnyvale CA (US)

Dao-I Tony Lin of Pleasanton CA (US)

Ranjani Ram of Chapel Hill NC (US)

Li Sun of Austin TX (US)

James Edwin Turman of Round Rock TX (US)

Anthony Winston of Akron OH (US)

Jie Xue of Dublin CA (US)

TELEMETRY DATA BASED COUNTERFEIT DEVICE DETECTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18187520 titled 'TELEMETRY DATA BASED COUNTERFEIT DEVICE DETECTION

Simplified Explanation: The patent application describes techniques for detecting counterfeit products by comparing hardware components and orientations of counterfeit and authentic products using telemetry data.

• Machine learning models analyze telemetry data to generate representative models of hardware intrinsic development data.
• Representative models include sample representative models based on valid telemetry data of authentic devices and test representative models based on unvalidated telemetry data of test devices.
• Comparisons between representative models are used to identify counterfeit products.

Key Features and Innovation: - Detection of counterfeit products through comparison of hardware components and orientations. - Use of telemetry data to generate representative models of hardware intrinsic development data. - Machine learning models analyze telemetry data to identify counterfeit products.

Potential Applications: - Anti-counterfeiting measures in various industries. - Quality control in manufacturing processes. - Product authentication for consumers.

Problems Solved: - Counterfeit product detection. - Ensuring authenticity of products. - Preventing fraud and deception in the market.

Benefits: - Increased consumer trust in product authenticity. - Reduction in counterfeit product sales. - Improved brand reputation and customer satisfaction.

Commercial Applications: Title: Counterfeit Product Detection Technology This technology can be used in industries such as electronics, pharmaceuticals, and luxury goods to prevent the sale of counterfeit products and protect brand reputation.

Prior Art: Prior art related to this technology may include research on counterfeit detection methods using telemetry data and machine learning algorithms.

Frequently Updated Research: Ongoing research in the field of anti-counterfeiting technologies and machine learning applications for product authentication may provide further insights into improving counterfeit detection methods.

Questions about Counterfeit Product Detection Technology: 1. How does this technology impact consumer safety and trust in the market? 2. What are the potential limitations or challenges in implementing this technology in different industries?

Original Abstract Submitted

Techniques are described for detecting counterfeit products by identifying differences between hardware components and orientations of the counterfeit products, and hardware components and orientations of authentic products. In some examples, the hardware components and orientations can be identified by generating hardware intrinsic development data based on telemetry data of products (or “devices”). By way of example, the telemetry data may be analyzed by machine learning (ML) models to generate representative models of the hardware intrinsic development data. In various examples, the representative models can include sample representative models of hardware intrinsic development data generated based on valid telemetry data of authentic devices. In those or other examples, the representative models can include other representative models (or “test representative models”) of hardware intrinsic development data generated based on unvalidated telemetry data of test devices. Comparisons between the representative models can be utilized to identify the counterfeit products.