Application of Verifeyed on Iran’s state media published photo

The photo shown below has been published by Iran’s state media showing their missile test. The photo has been used on the front pages of The Los Angeles Times, The Financial Times, The Chicago Tribune and several other newspapers as well as on BBC News, and many other major news Web sites. Four missiles appear to take off from a desert launch pad in one image of the test published on the Iranian Revolutionary Guards website.

Later on it has been uncovered that the photo is tampered with. Let’s apply Verifeyed Professional Edition on the image (download the photo from here to perform the test by your own). Simply, open the photo using the photo examiner window. As shown below, Verifeyed instantly detects traces of tampering. Here, local compression inconsistencies as well as copied and pasted image regions have been used to detect digitally edited areas.



Verifeyed Professional Edition:



Whether you know anything about detecting doctored digital images or not, Verifeyed Professional Edition, with its state-of-the-art image analysis technology, will turn you into a top-level image forensics expert with one click of the mouse. The original image is shown below.








on July 15, 2013

Digital Image Ballistics

We are often times asked what is digital image ballistics which is one of the services provided by the Verifeyed Professional Edition.

Imagine that there is a set of digital images, and you need to find out if they have been captured by a particular smartphone or camera belonging to somebody. This often happens in forensic investigation, in law enforcement, insurance, financial or the media industry. For example, let’s say that somebody claims they have captured some photos and you need to verify it by testing to see if photos are really captured by his or her camera or smartphone, or there is a discovery of some digital images and you need to verify that those photos have been captured by that person’s camera.
Our cutting edge scientific technology makes this possible. The procedure of linking a digital image to a particular camera or smartphone is called image ballistics.

Image ballistics also easily differentiates between cameras and smartphones of the same make and model. Each imaging device has a sensor. An image sensor is a device that converts light, or in other words, the optical image, into an electronic signal. Most currently used sensors are CCD or CMOS sensors consisting of millions of small elements called pixels. Due to variations in the pixels size and material properties, each pixel also has its own behavior and small variations. This behavior is unique and can be used to create a so called fingerprint of that sensor. These fingerprints are used in order to carry out ballistic tests and inspect if a digital image has been taken by that particular camera.

on July 15, 2013

Danger of Photoshop (source: YouTube)

Many tutorials freely show how to edit digital images on Internet (see, ). For example, we easily found these two Youtube videos showing how to make a fake insurance claim by editing digital images.

on May 14, 2013

A New Promotion Video for VerifEyed

on April 11, 2013

BP Digitally Altered Press Photos

A site called Americablog spotted a press photo of BP’s Houston command center, taken on July 16, 2010. The image had been “shopped” to include more on-screen camera action (the photo on the right side is the original one).

on December 11, 2012

Image Tampering in Scientific Literature

Today, we face the problem of digital image forgeries even in scientific literature. For instance, the Journal of Cell Biology, a premier academic journal, estimates that around twenty five (25) percent of manuscripts accepted for publication contain at least one image that has been inappropriately manipulated. In many cases, the author is only trying to clean the background and the changes do not affect the scientific meaning of the results. However, the journal also estimates that roughly one (1) percent of figures are simply fraudulent.

One of the most famous cases of digital image forgeries in a scientific area was in 2004 when a team lead by the South Korean scientist Dr. Hwang Woo-Suk published their results in stem cell research in the journal Science.Their results showed the successful cloning of stem cells. This offered hope for new cures for diseases. Later, in 2005, one of the co- authors admitted that photographs in the paper had been tampered with. This resulted in, among other things, the resignation of Dr. Hwang from his position at Seoul National University.

on December 11, 2012

Sarah Palin

This photomontage of Sarah Palin was widely dispersed across the Internet.

on December 11, 2012

Iranian Missile Test

In July 2008, Iranian media published the image shown on the left demonstrating a successful missile test. The original image is shown on the right side. The photo was subsequently featured on the front pages of newspapers across the world on July 9, 2008. It purported to be a proof of successful launches of Iranian short- range missiles.   

on December 11, 2012

VerifEyed – Enterprise Edition (Insurance and Claims Industry) how to find my ip address

on December 11, 2012

VerifEyed – Enterprise Edition (Banks, financial industry)

on December 11, 2012

VerifEyed: NYC Next Idea winner

VerifEyed winner of NYC Next Idea. Mayor Bloomberg announced the winners of the competition at City Hall.

on December 11, 2012

VerifEyed – You Can Trust Photos Again (Internet Dating)

on December 11, 2012

Faith Hill

In July 2007, Redbook magazine published on its cover page a digitally edited version of singer and actress Faith Hill.


on December 11, 2012

Can an Image Forgery Win Pulitzer?

Another famous case of digital image manipulation is this widely published photograph taken during the 2003 Iraq war.

Brian Walski, who was covering the war for the Los Angeles Times, combined two of his Iraqi photographs into one to improve the composition and to create a more interesting image. The image shows an armed British soldier and Iraqi civilians under hostile fire in Basra. The soldier is gesturing at the civilians and urging them to seek cover. The standing man holding a young child in his arms seems to look at the soldier imploringly. It is the kind of picture that wins a Pulitzer. The tampering was discovered by an editor at The Hartford Courant, who noticed that some background people appeared twice in the photograph. It ended with the photographer being fired.

on December 11, 2012

Image Authentication Without Using Watermarks and Signatures

Image authentication without using watermarks and signatures (called the passive or blind approach) is regarded as a new direction and does not need any explicit prior information about the image. The decision about the trustworthiness of an image being analyzed is based on fusion of the outcomes of separate image analyzers. Here, we provide an overview of some of methods (analyzers) which are employed to analyze digital images.

  • Detection of interpolation and resampling. When two or more images are spliced together to create high quality and consistent image forgeries, geometric transformations are almost always needed. These transformations, typically, are based on the resampling of a portion of an image onto a new sampling lattice. This requires an interpolation step, which typically brings into the signal statistical changes. Detecting these specific statistical changes may signify tampering.
  • Detection of near-duplicated image regions. Detection of duplicated image regions may signify copy-move forgery. In copy-move forgery, a part of the image is copied and pasted into another part of the same image typically with the intention to hide an object or a region.
  • Detection noise inconsistencies. The amount of noise in authentic digital images is typically uniformly distributed across an entire image and typically invisible to the human eye. Additive noise is a very commonly used tool to conceal the traces of tampering and is the main cause of failure of many active or passive authentication methods. Often by creating digital image forgeries, noise becomes inconsistent. Therefore, the detection of various noise levels in an image may signify tampering.
  • Detection of double JPEG compression. In order to alter an image, typically the image must be loaded onto a photo- editing software and after the changes are done, the digital image is re-saved. If the images are in the JPEG format, then the newly created image will be double or more times JPEG compressed. This introduces specific correlations between the discrete cosine transform (DCT) coefficients of image blocks. The knowledge of image’s JPEG compression history can be helpful in finding the traces of tampering.
  • Detection of inconsistencies in color filter array (CFA) interpolated images. Here, the hardware features of digital cameras are used to detect the traces of tampering. Many digital cameras are equipped with a single charge-coupled device (CCD) or complementary metal oxide semiconductor (CMOS) sensor. Then, typically, the color images are obtained in conjunction with a color filter array. In these cameras, only a single color sample is captured at each pixel location. Missing colors are computed by an interpolating process, called CFA interpolation. This process introduces specific correlations between the pixels of the image, which can be destroyed by the tampering process.
  • Detecting inconsistencies in lighting. Different photographs are taken under different lighting conditions. Thus, when two or more images are spliced together to create an image forgery, it is often difficult to match the lighting conditions from the individual photographs. Therefore detecting lighting inconsistencies offers another way to find traces of tampering.
  • Detecting inconsistencies in perspective. When two or more images are spliced together, it is often difficult to maintain correct perspective. Thus, for instance, applying the principles from projective geometry to problems in image forgery detection can be also a proper way to detect traces of tampering.
  • Detecting inconsistencies in chromatic aberration. Optical imaging systems are not perfect and often bring different types of aberrations into an image. One of these aberrations is the chromatic aberration, which is caused by the failure of an optical system to perfectly focus light of different wavelengths. When tampered with, this aberration can become inconsistent across the image. This can be used as another way to detect image forgeries.
on December 11, 2012

Image Integrity Verification by Data Hiding

The data hiding approach refers to a method of embedding secondary data into the primary multimedia sources. This is carried out mainly to fulfill authentication and tampering detection, copyright protection and distribution control. The idea of hiding information has a long history, likely to date back a couple of thousand years. In recent decades, techniques of adding some imperceptible data to multimedia sources received special attention from the research community. This many methods of data hiding developed into multimedia security applications in. Most of them are referred to as digital watermarking or Hash marks.

The main advantage of data hiding compared to digital signatures is that it gives the ability to associate the secondary data with the primary media in a seamless way. They are mostly imperceptible and travel with the host image. The data hiding approach can be divided further in several fields. Digital watermarking is the most popular one.

on December 11, 2012

Image Authentication using Digital Watermarks

Many watermarks have been proposed so far. Below are examples of spatial and frequency domain watermarks. Digital watermarking assumes inserting of a digital watermark at the source (e.g., camera) and verifying the marks integrity at the detection side. Digital watermarks are mostly imperceptible; they are inseparable from the digital media they are embedded in, and they undergo the same transformations as the digital media itself. A major drawback of approaches based on watermarks is that the watermarks must be inserted either at the time of recording the image, or later by a person authorized to do so. This limitation requires specially equipped cameras or subsequent processing of the original image. Furthermore, some watermarks may degrade the image quality. It also requires hiding the watermark key from the device owner.

Digital watermarks are classified as visible or invisible. The visible group is perceptible to the human eye. In the case of the latter group, the existence can only be determined using a detection algorithm. In addition, watermarks can also be designed to be fragile or robust. Fragile watermarks become corrupted when any part of the image is modified. Thus, the most fundamental property of invisible fragile watermarks is the test of image authenticity and tamper detection. Robust watermarks are not affected by common image- manipulation procedures. Therefore, they are a proper way of ownership protection.

on December 11, 2012

Image Authentication using Digital Signatures

The digital signature approach offers an interesting alternative to classical watermarking techniques and is based on the idea of traditional paper- based signing by transforming it into the digital world. It consists mainly of extracting unique features from the image at the source side and encoding these features to form digital signatures. Afterwards signatures are used to verify the image integrity by signature comparison at the detection side. If any changes are made to the image after it was signed, they automatically invalidate the signature. Signatures as well as watermarks provide, among other qualities, protection from tampering, copyright infringement and illegal distribution. There are many methods to generate the signatures, for example, based on image histograms, colors, geometric information, frequency information, etc.

The major drawbacks of digital signatures are similar to watermarks drawbacks. The main disadvantage is the need for a fully secure and trustworthy source. We need a common algorithm on both source and detection sides. The image alone is not self- sufficient to perform the authentication process. Because of this, the benefits of the active approach are significantly reduced.

on December 11, 2012

Katie Couric

In September 2006, a digitally edited photo of the CBS news anchor Katie Couric appeared in their in-house magazine Watch! The original shows that her image was edited to create a slimmer waistline and a thinner face.

on December 11, 2012

Some Examples of Historical Image Forgeries

Creating image forgeries has a long history. Here, are some examples of earlier image forgeries. Here, a photo manipulation with Stalin is shown (1930):

This image shows a historical manipulation with a photo of Mao Tse- tung (1936):

This image shows an earlier photo manipulation with a photo of Adolf Hitler (1937). Here, Joseph Goebbels has been removed from the original photo.

Another example of earlier image forgeries. In the summer of 1968 Fidel Castro approves of the Soviet intervention in Czechoslovakia. Carlos Franqui (the man in the middle) cuts off relations with Castro and goes into exile in Italy. His face was then removed from the photograph.

on December 11, 2012