Technology Brief: Advanced Digital Trust & Security
Advanced Digital Trust & Security: Technology Overview
For decades, cybersecurity relied on a relatively simple principle: protect the network perimeter, scan for known threats and control access through passwords and permissions. This approach worked well when data was stored in corporate data centres, employees worked mainly within office networks and attacks followed more familiar patterns.
Today, data and applications are spread across cloud environments, employees and devices connect from almost anywhere, and industrial systems, power grids and vehicles are increasingly connected. Meanwhile, attackers use automation and AI to develop sophisticated attacks, create convincing deepfakes and exploit weaknesses in hardware and supply chains. Advances in quantum computing could eventually undermine some of today’s encryption methods. These developments are driving demand for new approaches to cybersecurity, beyond simply improving existing tools – Advanced Digital Trust & Security.
We have identified five technology areas that illustrate this next generation of cybersecurity. Their patent landscapes show how quickly they are developing, where innovation is concentrated and which companies are building strong technological positions. The analysis covers specialist Advanced Digital Trust & Security vendors and technology, semiconductor and platform companies, as well as companies from industries such as finance, telecommunications, energy and utilities. These industries are major users of Advanced Digital Trust & Security technologies and also contribute to innovation through their own patent activity.
Patents offer an early indication of technological change, often years before new capabilities reach the market or become visible in company revenues. Tracking patent activity and technological strength can therefore help identify emerging areas of innovation and the companies developing capabilities in these fields.
Explore the five technologies below to learn how they work, where they are applied and why they matter.
Intelligent Threat Defense
What it covers:
AI-driven threat detection and response, cloud-native and API security, zero-trust architectures, protection of industrial control systems, IoT devices and connected vehicles, and software supply-chain security.
Traditional security tools often rely on known attack patterns and predefined rules. AI-driven systems can analyse behaviour across users, devices, networks and cloud workloads to identify suspicious activity, including previously unseen threats. Zero-trust architectures move away from the assumption that everything inside a corporate network is trustworthy, requiring access requests to be verified continuously. These approaches are also increasingly important for industrial systems, where cyberattacks can have physical consequences, and for software supply chains, where a compromised component can expose thousands of organisations to risk.
Why it matters:
Attackers are increasingly automating their operations, while the number of connected systems to protect continues to grow. Security must become more adaptive and automated in response. Intelligent threat defense moves beyond static rules towards systems that can detect, investigate and respond to threats with less manual intervention.
AI & Deepfake Security
What it covers:
Protection of AI models against manipulation, data poisoning, jailbreaks and adversarial attacks; security of AI agents; detection of deepfakes and synthetic media; media forensics; and content provenance and watermarking for AI-generated material.
As artificial intelligence becomes embedded in business processes, AI systems themselves are increasingly becoming targets. Attackers can poison training data, manipulate model inputs or exploit weaknesses in language models and autonomous agents to trigger unintended actions. At the same time, generative AI makes it easier to create realistic fake images, videos and voices, which can be used for fraud, impersonation and disinformation. This field covers technologies that protect AI systems from attacks and help identify content that has been artificially generated or manipulated.
Why it matters:
Trust in AI systems and digital content is becoming increasingly important to the digital economy. AI & Deepfake Security is an emerging area of cybersecurity, with patent activity reflecting growing efforts to address risks that have gained prominence only in recent years.
Identity & Anti-Fraud
What it covers:
Passwordless and continuous authentication, decentralised digital identity and identity wallets, biometric liveness detection and anti-spoofing for face and voice, identity management for machines and workloads, and AI-based detection of payment fraud, account takeover and money laundering.
Stolen credentials and compromised identities are behind many successful cyberattacks. Next-generation identity technologies reduce reliance on passwords through cryptographic credentials and biometrics, verify users continuously based on behaviour, and give individuals greater control over their digital identities. As criminals increasingly use deepfakes and synthetic identities to bypass verification, liveness detection and AI-driven fraud analytics are becoming more important.
Why it matters:
As more transactions, services and interactions move online, reliably verifying who or what is on the other side becomes critical. This applies not only to people, but also to devices, software and AI agents, making identity security central to both cybersecurity and digital commerce.
Quantum & Hardware Security
What it covers:
Quantum key distribution, quantum random number generation, post-quantum cryptography and crypto-agility, as well as hardware-based security technologies such as physically unclonable functions, hardware roots of trust, secure boot and firmware attestation, and protection against side-channel and physical attacks.
Cryptographically relevant quantum computers could break many of the public-key cryptographic methods used to protect digital communications today. This creates a risk that data intercepted now could be decrypted in the future. Post-quantum cryptography develops algorithms designed to withstand such attacks, with NIST publishing its first post-quantum cryptography standards in 2024. Quantum key distribution offers a different approach, using quantum-mechanical properties to help secure key exchange.
Security also increasingly relies on protections built directly into hardware. These include chips with unique physical characteristics, trusted boot processes and countermeasures against attacks that extract secrets through power-consumption measurements or deliberate hardware faults.
Why it matters:
The transition to quantum-resistant cryptography will require extensive changes to digital infrastructure, from communication networks to connected devices. Hardware security provides an additional layer of protection, helping establish trust in the systems on which software and digital services depend.
Privacy & Confidential Computing
What it covers:
Homomorphic encryption, secure multi-party computation, zero-knowledge proofs, differential privacy and privacy-preserving machine learning, as well as confidential computing based on hardware-protected trusted execution environments.
Conventional encryption protects data while it is stored or transmitted, but data generally needs to be decrypted for processing, potentially exposing it to unauthorised access. Privacy-enhancing technologies address this gap in different ways. They enable computations on encrypted data, joint analysis across organisations without directly sharing sensitive information, or verification of specific facts without revealing the underlying data. Confidential computing uses hardware-protected environments to isolate data and AI models from other software running on the same system, including, in some configurations, access by cloud operators.
Why it matters:
Organisations want to use sensitive data for AI, research and business collaboration, but privacy requirements, regulation and commercial concerns often limit what they can share. Privacy-enhancing technologies make it possible to extract value from data while reducing exposure and retaining greater control over its use, creating opportunities in healthcare, finance and cross-border data collaboration.
Global trends: sharp rise in Advanced Digital Trust & Security patents
Indexed global development of patents in Advanced Digital Trust & Security compared to all Cybersecurity technologies
Active Patents in Advanced Digital Trust & Security have more than tripled since 2020
The number of active patent family publications in the five defined Advanced Digital Trust & Security areas increased from around 5,700 in 2015 to around 20,700 in 2020 to 73,000 at the end of September 2026. As a result, patent growth has been much more dynamic than in cybersecurity as a whole.
Global development of patents in the five Advanced Digital Trust & Security areas
Intelligent Threat Defense is the largest patent area within Advanced Digital Trust & Security
The number of active patent family publications in the field of intelligent threat defense increased from just 1,100 in 2015 to nearly 28,000 in 2026. Other significant areas are Quantum & Hardware Security and Privacy & Confidential Computing, which each had around 15,000 active patent family publications in 2026. However, the highest growth rate was observed in AI & Deepfake Security, where the number of patent family publications increased from just 190 in 2015 to over 7,700 in 2026 — equivalent to an annual growth rate of 40%.
Top research countries in Advanced Digital Trust & Security
Top Countries – Total Patents
Top Countries – World-Class Patents
Top research companies in Advanced Digital Trust & Security
Total Patents: Top 20 companies
The top 20 ranking is dominated by large diversified technology companies, telecom operators and financial institutions. Specialised Advanced Digital Trust & Security vendors are fewer among the leaders. IBM leads with 996 patents, ahead of Microsoft with 781, China Mobile with 689 and Intel with 639. Tencent, Dell, Cisco, Alphabet and Samsung also have sizeable portfolios, as do the chip makers Broadcom and NXP. The presence of ICBC, Ping An and Bank of America shows how heavily large financial institutions invest in protecting their own systems, particularly against fraud and cyberattacks. Palo Alto Networks, at 215 patents, is the only pure-play Advanced Digital Trust & Security vendor in the top 20. For investors, total patent volume indicates the breadth of a company’s technological footprint, while the comparison with World-Class Patents helps distinguish broad patent activity from the strength of the underlying innovation.
World-Class Patents: Top 20 companies
World-Class Patents identify the top 10% of patents within each technology. The rating combines relevant international coverage, reflecting the applicant’s assessment of an invention’s commercial importance, with citations, reflecting its technological relevance. As a result, World-Class Patents are more useful than overall patent volumes for identifying the true innovation leaders.
Microsoft holds the largest number of World-Class Patents in Advanced Digital Trust & Security, with 268 in 2026, followed by IBM with 206, Intel with 174 and Cisco with 135. Tencent, Alibaba and Alphabet also have more than 90 World-Class Patents. Compared with the total patent ranking, the picture shifts noticeably. Telecom operators such as China Mobile and NTT drop out of the top 20, while the specialists Zscaler and Palo Alto Networks hold their places with 51 and 44 World-Class Patents, showing that their portfolios are smaller but of high quality. Financial companies such as Bank of America, Visa and Capital One also remain prominent, reflecting their investment in fraud prevention and secure digital payments.
Specialists: Top 20 companies
The specialist ranking only includes companies that hold at least 10% of their total patent portfolio in Advanced Digital Trust & Security. This highlights businesses for which these technologies are a central part of their innovation activity and which are therefore likely to benefit most directly from their growth.
Palo Alto Networks leads with 173 patents, followed by Zscaler with 119, Fortinet with 84 and CrowdStrike with 71. The highest degrees of specialisation are found at Tenable, with 41.9% of its portfolio in Advanced Digital Trust & Security, followed by Rapid7, Netskope and Zscaler, each at more than 25%. Alongside established security vendors such as Check Point, CyberArk, Okta and Cloudflare, the ranking also includes companies from neighbouring fields: IonQ through quantum-secure communication, Coinbase through cryptographic key protection, and Mitek through digital identity verification.