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Trust Stamp announces an AI-powered solution for Deep Fake and other Injection Attacks

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Trust Stamp (Nasdaq: IDAI), a privacy-first identity company, announced the filing of a provisional patent (#63/662,575) for an AI-powered technology to counter injection attacks in biometric authentication processes. These attacks, often using deep fake images and videos, aim to bypass a user's device camera or inject images captured out of context into the data stream between the user's device and the server. Dr. Norman Poh, Trust Stamp's Chief Science Officer, emphasized the increasing frequency of such attacks and the necessity for advanced detection mechanisms. This new technology targets injection attacks regardless of the artifacts used, aiming to enhance security in the face of rapid advances in generative AI.

Positive
  • Trust Stamp filed a provisional patent for a new AI-powered technology to detect injection attacks (#63/662,575).
  • The technology addresses growing threats from deep fake images and videos in biometric authentication.
  • The company aims to enhance security measures against billions of daily injection attacks.
Negative
  • None.

Insights

The provisional patent announced by Trust Stamp involves a new AI-powered technology designed to combat injection attacks in biometric authentication. This development is noteworthy, particularly given the recent proliferation of deep fake technologies. Deep fakes involve the use of AI to create highly convincing fake images and videos which can bypass traditional authentication methods. By filing for this patent, Trust Stamp is taking proactive measures to strengthen its security infrastructure against these sophisticated threats.

From a technical standpoint, the solution addresses a pressing need in the cybersecurity landscape. With billions of attacks being recorded daily, the technology aims to provide a robust layer of defense against unauthorized access. This innovation could potentially position Trust Stamp as a leader in the biometric security space, making its platform more attractive to businesses and governments seeking advanced security solutions.

However, it's essential to monitor the progress from provisional patent to a fully developed product. The successful implementation of this technology could significantly enhance Trust Stamp�s market credibility and competitive edge. Still, it remains to be seen how effectively it integrates with current systems and whether it can stay ahead of the evolving threat landscape.

Trust Stamp’s announcement reflects a strategic move to address one of the most critical vulnerabilities in biometric authentication systems. The market for biometric security is growing rapidly, driven by increasing demand for secure and user-friendly authentication methods. Injection attacks, particularly those using deep fakes, pose a substantial risk to the integrity of these systems and a robust countermeasure could create significant market opportunities for Trust Stamp.

From a market perspective, this patent could enhance Trust Stamp’s value proposition, making its solutions more appealing to high-profile clients, notably in sectors like finance, healthcare and government, where security concerns are paramount. This could translate into new contracts and partnerships, thus driving revenue growth.

Moreover, given the increasing regulatory scrutiny around data privacy and security, Trust Stamp’s proactive stance in developing cutting-edge technology could also improve its standing with regulators and compliance bodies, potentially resulting in a smoother path to market for its solutions. However, the effectiveness and adoption of the new technology will be critical in determining its long-term impact on the company’s market position.

Trust Stamp announces a provisional patent for a new AI-powered technology to counter Injection Attacks, including deep fake images and Videos

ATLANTA, GA, June 24, 2024 (GLOBE NEWSWIRE) -- Trust Stamp (Nasdaq: IDAI), the Privacy-First Identity CompanyTM, announced that it has filed provisional patent #63/662,575 with the US Patent and Trademark Office for a new methodology to detect injection attacks in biometric authentication processes, including attacks executed using deep fake images and videos.

Injection attacks targeting biometric processes typically bypass the camera on a user’s device or inject video or still images captured in a different context into the data stream between the user’s device and the server to which they are authenticating.

Dr Norman Poh, Trust Stamp’s Chief Science Officer, commented, "We already have a number of liveness detection technologies implemented, but there are now billions of daily attacks being perpetrated with a growing number of injection attacks using genuine artifacts captured out of context as well as deep fake images and videos. When genuine artifacts are used out of context, they may be able to pass legacy liveness detection tests. With rapid advances in generative AI technology, we always have to be watchful for deep fakes that can defeat liveness tests. This latest presentation attack detection technology that we have patented targets injection attacks regardless of the artifacts being used."

Enquiries

Trust Stamp                                                   Email: Shareholders@truststamp.ai

Norman Poh, Chief Science Officer: npoh@truststamp.ai

About Trust Stamp

Trust Stamp, the Privacy-First Identity CompanyTM, is a global provider of AI-powered identity services for use in multiple sectors, including banking and finance, regulatory compliance, government, real estate, communications, and humanitarian services. Its technology empowers organizations with advanced biometric identity solutions that reduce fraud, protect personal data privacy, increase operational efficiency, and reach a broader base of users worldwide through its unique data transformation and comparison capabilities.

Located across North America, Europe, Asia, and Africa, Trust Stamp trades on the Nasdaq Capital Market (Nasdaq: IDAI). The company was founded in 2016 by Gareth Genner and Andrew Gowasack.

Safe Harbor Statement: Caution Concerning Forward-Looking Remarks 

All statements in this release that are not based on historical fact are “forward-looking statements,” including within the meaning of the Private Securities Litigation Reform Act of 1995 and the provisions of Section 27A of the Securities Act of 1933, as amended, and Section 21E of the Securities Exchange Act of 1934, as amended. The information in this announcement may contain forward-looking statements and information related to, among other things, the company, its business plan and strategy, and its industry. These statements reflect management’s current views with respect to future events-based information currently available and are subject to risks and uncertainties that could cause the company’s actual results to differ materially from those contained in the forward-looking statements. Investors are cautioned not to place undue reliance on these forward-looking statements, which speak only as of the date on which they are made. The company does not undertake any obligation to revise or update these forward-looking statements to reflect events or circumstances after such date or to reflect the occurrence of unanticipated events.


FAQ

What did Trust Stamp (IDAI) announce on June 24, 2024?

Trust Stamp announced the filing of a provisional patent for an AI-powered technology to detect injection attacks in biometric authentication.

What is the purpose of Trust Stamp's new AI-powered technology?

The new AI-powered technology aims to detect and counter injection attacks, including those using deep fake images and videos, in biometric authentication processes.

What is the patent number of Trust Stamp's new technology?

The provisional patent number for Trust Stamp's new technology is #63/662,575.

Who commented on the new technology from Trust Stamp?

Dr. Norman Poh, Trust Stamp’s Chief Science Officer, commented on the new AI-powered technology.

What threats does Trust Stamp’s new technology aim to address?

The technology aims to address injection attacks, including those using deep fake images and videos, in biometric authentication.

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