Company patents
NTT Research, Inc.
NTT Research, Inc. surprisingly concentrates a dominant 58.0% of its patent portfolio in Cryptographic Mechanisms, showing rapid growth with a +111.1% YoY increase in 2025, though patenting in this area has seen a -57.9% decline so far in 2026. While Machine Learning & AI also saw significant growth (+400.0% YoY in 2024), the company's patenting in several categories like Network Security & Access Control, Coding & Decoding, and Medical Diagnostics & Surgery has seen a complete -100.0% decline so far in 2026, indicating a potential shift in focus away from these areas.
Patent Trend by Technology Area
Yearly patent publications since 2023
Product themes
Product-level themes inferred from filings since 2023, with category chips showing where each theme appears. Select a theme to filter the patents below.
69 US filings (since 2023) · 9 categories · 13 themes
Applying artificial intelligence and machine learning techniques to enhance cryptographic systems, such as generating encryption models, improving zero-trust architectures, or enabling privacy-preserving computations like federated learning.
Systems and methods for encrypting data at a fine-grained level (e.g., per data unit or based on sensitivity) and controlling access to it, often involving delegated authorization, contextual policies, or secure data sharing.
Utilizing dedicated hardware components, secure enclaves, or trusted execution environments to perform cryptographic operations, enhancing security, performance, or isolation from software vulnerabilities.
Techniques for improving the performance, efficiency, or practicality of fully homomorphic encryption (FHE) schemes, often involving hardware accelerators or optimized algorithms for operations like bootstrapping and key-switching.
Techniques for protecting data at rest or in backup, ensuring its integrity, confidentiality, and verifiable origin, often involving encryption, unique identifiers, or secure repositories.
Development of encoding and decoding algorithms and apparatuses for robust data transmission and storage, focusing on techniques like LDPC, polar codes, and iterative decoding methods to minimize bit errors and improve communication reliability.
Developing and applying machine learning algorithms that leverage quantum computing principles, such as quantum circuits or autoencoders, for tasks like simulation or data processing.
Methods and systems for generating, distributing, updating, rotating, and securely destroying cryptographic keys to maintain data confidentiality and integrity over time, including quantum key distribution.
Methods and systems for efficiently reducing the size of digital data, often employing adaptive techniques, neural networks, or temporal modeling, to achieve high compression ratios while preserving data quality. Includes entropy coding.
The design and manufacturing of integrated circuits that combine optical and electronic components, particularly for high-speed data communication between processors and memory.
Specialized hardware, architectural designs, and computational methods to improve the speed, efficiency, and security of artificial intelligence and machine learning model execution, particularly for inference and data processing.
Engineering of artificial subwavelength structures (meta-atoms) to create metasurfaces that manipulate light properties (phase, polarization, wavelength) for multi-functional optical devices.
Design and application of devices that are inserted into the body or implanted to treat diseases, modulate physiological functions, or repair anatomical structures.
Patents
Showing 1-6 of 6
Quantum Machine Learning