Monthly Archives: July 2018

Amped Authenticate Update 11362: JPEG Dimples, Improved JPEG HT, Social Media Identification, and much more!

Not long has passed since the release of Amped Authenticate 10641 but… yes, the next one is already out! Amped Authenticate 11362 is now released with a lot of improvements, including two new filters based on JPEG Dimples, one of the last discoveries of the image forensics scientific community!

JPEG Dimples

Despite many attempts to send JPEG into retirement, today the vast majority of digital images still use it. Amped Authenticate users know that traces left by JPEG compression are a superb asset when it comes to investigating the digital history of an image, as witnessed by the vast JPEG-based toolkit that Authenticate provides: quantization table analysis, JPEG ghosts, inconsistencies in blocking artifacts, double quantization traces in the DCT coefficients, and more.

But JPEG is still full of new surprises nowadays! A few months ago, while Amped was attending (and sponsoring!) the IEEE 2017 International Workshop on Information Forensics and Security (WIFS 2017), a new footprint was presented to the scientific community: JPEG Dimples (click here to see the original work Photo forensics from JPEG dimples by Shruti Agarwal and Prof. Hany Farid).

JPEG Dimples manifest themselves as a grid of slightly brighter/darker pixels, spaced by 8 pixels in each dimension. Like most image forensic fingerprints, even JPEG Dimples are hardly visible by the human eye, but they can be easily detected with a proper algorithm.

But why does this grid appear? And why is it important for our analysis? We’ll answer these questions in detail in a future blog post, however the reason behind JPEG Dimples is rather simple: during the DCT coefficients quantization phase, different operators exist to approximate decimal values to integer values: the round operator (which approximates the decimal number to the nearest integer) the floor operator (approximation to the nearest smaller integer) or the ceil operator (approximation to the nearest bigger integer). The table below shows the difference in approximating a Value (first column) to an integer using round, floor and ceil.

Value Round Floor Ceil
9.8 10 9 10
6.3 6 6 7
4.5 5 4 5
-7.3 -7 -8 -7

Obviously, using floor tends to produce smaller values in the 8-by-8 DCT block than using round, and the opposite with ceil. And when we go back to the pixel domain, this leads to a slightly darker or brighter pixel on the top-left corner of the pixel block (see example below)! Measuring the presence of this grid will tell us to which degree an image contains the JPEG Dimples footprint.

Image showing Dimples

Example of an image showing strong JPEG Dimples

Now you may be wondering “well, how many cameras will ever be using floor or ceil in place of the more classical round?” Not so few, actually. According to the work presented at WIFS 2017, more than 60% of tested cameras do introduce Dimples. We also carried out an internal evaluation on Amped datasets and numbers were less upsetting, still, we found Dimples in roughly 30% of tested cameras. A footprint with such a spread could not be missing in Amped Authenticate, and so here we are. Continue reading

Extracting Channels

If you’ve attended one of my classes or lectures, you’ve likely heard me say the following phrase many times, “There’s what you know, and there’s what you can prove.” The essence of this statement forms the basis of the Criminal Justice system as well as science.

What I “know” is subject to bias. What I “know” is found in the realm of truth. As a Kansas City Chiefs supporter, I “know” that the Oakland Raiders are a horrible team. I “know” that their fans are the worst in the world. After all, the Chiefs are the best and their fans are as pure as the wind-driven snow. This is “true” to me. Whilst funny and used to illustrate a point (I’m sure there are some really great people among the Raiders fan base), truths are things we “know.” Truths are rooted deep in feelings/emotions and unlikely to be changed by facts. There is a segment of the US population that believes it true that Elvis is still alive and that he’s likely hanging out on some Caribbean island with Tupac and Biggy Smalls.

Facts are measurable; they form the basis of tests of reliability. I can measure the temperature in a specific location and you, standing in the same location, can perform the same test and come to the same measurement. Supported by facts, our tests in this discipline become reliable, repeatable, and reproducible. Our conclusions can thus be trusted.

What on earth does this all have to do with Amped FIVE and Forensic Multimedia Analysis? I’m glad you asked.

By now, you’re well familiar with the fact that Amped Software operationalizes tools out of image science, math, statistics, etc. We also operationalize tools and training out of the world of psychology. By this I mean if we’re going to work in the visual world, we must know how that visual world operates not only from a mechanical standpoint but also from how the brain processes the inputs from its collection devices.

Continue reading