Siemens had 192 patents in cybersecurity during Q1 2024. Siemens AG filed patents in Q1 2024 for methods involving data transmission using distributed databases, training local functions with machine learning, detecting objects on touch sensors, transmitting medical datasets securely, and assessing person re-identification risk in databases. These methods utilize cryptographic linking, encryption, and anonymization techniques to ensure data security and privacy. GlobalData’s report on Siemens gives a 360-degree view of the company including its patenting strategy. Buy the report here.

Siemens grant share with cybersecurity as a theme is 30% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Method for transmitting data by way of at least two moving components, computer program product, transmitter and receiver (Patent ID: US20240106807A1)

The patent filed by Siemens AG describes a method for transmitting data from a source to a target using components of a network that are moving relative to the source and target. The data is transmitted using a distributed database with at least two parts that are cryptographically linked to each other. The method involves sending and receiving data, with at least one of the components being a vehicle. The parts of the distributed database are transmitted multiple times by different components, and each part is provided with a hash value of the preceding part to ensure cryptographic linkage.

Furthermore, the method ensures that the moving components do not transmit the entire distributed database but only a partial set of parts. Each part is requested or received with a signature by the component transmitting it. The patent also includes a non-transitory computer memory storing instructions for transmitting data through moving components, distributing the data into a distributed database, and requesting or receiving signatures for each part transmitted. This method allows for secure and efficient data transmission in dynamic network environments.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.