AI & Fraud Detection Technology

Industry-leading protection against altered or tampered digital media

The Attestiv Platform is built on our patented AI technology to authenticate, validate, and protect the integrity of important digital media and data.

Our technology takes any digital media (including photos, videos, documents, sensor data, telemetry data, etc.) that is captured by Attestiv apps and APIs or imported from any external source to identify if it has been altered or tampered with.

We forensically scan each item to detect anomalies giving it a tamper score. We optionally store a fingerprint on a blockchain (distributed ledger) where it cannot be changed, enabling validation at any point in the future. We offer additional analysis to help automate and simplify processing of digital media, including text extraction and object recognition.

Our Process

1.
Intake via app or API
2.
Analysis and tamper detection
3.
Validation & Reporting
4.
Automation

(optional)

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Intake via app or API

Images, video, documents or data from mobile devices, cameras, drones, surveillance systems, or legacy media libraries are captured or imported through the Attestiv mobile web app or APIs.

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Real-time analysis & tamper detection

Attestiv uses AI to detect photo or video anomalies and/or fraud attempts by using a forensic scan resulting in an aggregate tamper score. We also provide an added deep scan of images, with different sensitivity levels, to locate and isolate signs of manipulation or transplantation which are displayed via a heat map overlay.

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Validation & Reporting

Patented real-time verification informs viewers of the digital media whether it is authentic, imported, unknown or altered. Downloadable in-depth reports highligh areas that matter most for improving the quality of data used for making important decisions.

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Automation

Attestiv provides document analysis to read and process text within documents eliminating manual entry and also recognizes objects within images and videos.

Tamper Scoring System

Every item that gets analyzed by our system is given a score ranging between 1 to 100. Items scoring lower on the spectrum are considered to be trustworthy and need no further review. 

We also group and analyze related images into an Analysis Report that summarizes and calls out areas needing review. 

dashboard view of the Attestiv Platform

Our AI models explained

Images

Many editing tools leave traces in an image’s metadata. Additionally, bad actors may directly edit this data in an attempt to cover their tracks. This model searches through the image metadata for signs of this kind of tampering.

Documents

The metadata model looks for indicators of tampering in the scanned document’s EXIF data. Many editing tools will leave traces in the metadata, and in addition, fraudsters may edit this data directly to cover up their tracks.

 

Images

The provenance model matches images to the software in which they were saved, possibly after editing. If we trace the image back to an editing tool, like Photoshop, we can feel justified in being a little suspicious of that image.

Documents

The provenance model matches the scanned document to the software used to save the edits. If the scanned document can be traced back to an editing tool, then it indicates that the scanned document has been manipulated in some way.

Images only

The photo of photo model identifies photos of other photos or screens (television, computer monitors, etc.)

Images & Documents

The integrity model finds evidence of tampering in the image file itself. This includes AI-generated content, mismatched file extensions and corrupted contents.

Images only

The quality model identifies photos that are exceptionally blurry or noisy.

Images only

The reverse search model performs a reverse image search against a wide range of websites.

Documents Only

This model highlights any text alterations it can find in the document using its deep-learning algorithms.  It calculates a graded score based on the model’s confidence in its findings.

Videos only

This model checks for AI-generated content and graphics

Videos only

These models check for facial replacement or lip synching

Features

Patented technology

Attestiv makes extensive use of AI to perform media analysis, categorization, text extraction, and authentication. The easy to understand scoring system breaks down results in categories with a easy to understand description of potential manipulations.

Enterprise-ready

Attestiv is designed to meet enterprise security and compliance requirements for regulated industries, offering highest levels of data encryption at rest and in flight, APIs that purge all data after analysis, and ACLs to securely manage and administer settings for your organization. 

Tamper-proof photos & videos

As data is captured from cameras or imported from digital media libraries, Attestiv captures data and metadata from the digital media and optionally stores a unique “fingerprint” in an encrypted, tamper-proof distributed ledger.

Optimized User Experience

Whether your goal is to save time and money on media inspection or to prevent fraud and cyberthreats, Attestiv solutions will meet your user experience goals while helping you automate the handling and validation of digital media.

Demo Videos

Understanding the dashboard

(Video length: 100 seconds)

Validation and fingerprinting

(Video length: 226 seconds)

Media analysis

(Video length: 170 seconds)

Industry Standards

Attestiv Products, Solutions & Technology

Scalable. Secure. Compliant.

From the Blog

Mark Morley

Mark Morley is the Chief Operating Officer of Attestiv.

He received his formative Data Integrity training at Deloitte. Served as the CFO of Iomega (NYSE), the international manufacturer of Zip storage devices, at the time,  the second fastest-growing public company in the U.S.. He served as the CFO of Encore Computer (NASDAQ) as it grew from Revenue of $2 million to over $200 million. During “Desert Storm”, Mark was required to hold the highest U.S. and NATO clearances.

Mark authored a seminal article on Data Integrity online (Wall Street Journal Online). Additionally, he served as EVP, General Counsel and CFO at Digital Guardian, a high-growth cybersecurity company.

Earlier in his career, he worked at an independent insurance agency, Amica as a claims representative, and was the CEO of the captive insurance subsidiary of a NYSE company.

He obtained Bachelor (Economics) and Doctor of Law degrees from Boston College and is a graduate of Harvard Business School.