For businesses all around the world, image manipulation and fake id 2021 in identity verification has become a major problem. In this post, we’ll learn what image manipulation is and how technologies like AI, CNN, and Special CV filters may assist us in detecting it.
Identity theft is a major problem that affects people all around the world. Every year, thousands of people and businesses become victims of identity theft. Because cyber criminals use a variety of methods to steal personal information, businesses must implement modern ID verification systems to protect their data.
For many firms, picture manipulation in identity verification has become a major issue. Let’s figure out what it is.
What is Image Manipulation and How Does It Work?
The practice of changing or manipulating a digital image using various approaches to accomplish desired outcomes is known as image manipulation or photo modification.
Picture manipulation is a popular method for creating magazine covers and photo albums. Though it is a skilled piece of art, it has also been used to make false claims and fool the public.
Image modifications of a modest nature are permitted. Every one of us alters our pictures in some way.To reduce faults in photographs, we alter contrast, color, and white balance, for example.
However, in recent years, fraudsters have begun to use picture modification to commit financial crimes, harmful attacks, disseminate false information, and steal someone else’s identity.
Why Do Fraudsters Manipulate Images?
The use of images in identity verification has grown increasingly popular in recent years. Images are being manipulated by fraudsters for a variety of illegal purposes. A handful of the most common are mentioned here.
To Make Fake Identification Documents
In most situations, hackers create false IDs using image modification methods, which may then be used to obtain unauthorized access to a system or service.
Fake ID documents look just like the real thing and include a doctored photo of the authorized person. For identification purposes, fake IDs have been widely utilized.
Due to the widespread availability of low-cost, high-resolution printers and photo-editing software, creating false IDs has become quite simple.
Access to Personally Identifiable Information (PII)
A fraudster can use your photograph to obtain personally identifying information such your name, address, social security number, driver’s license number, bank account information, and more.
To Obtain Biometric Face Recognition System Access
Image manipulation can also be used by con artists to get access to the face recognition system. In the case of corporate identity theft, this is becoming a typical occurrence. Even biometric facial authentication systems are being bypassed by fraudsters employing 3D masks and printed photographs.
As a result, businesses require cutting-edge identity verification systems that can instantly validate government-issued identification papers and detect fraudulent IDs.
How Can Manipulation of Images Be Detected?
Technology, without a question, is making the world a better place to live. Image manipulation is one example of how the technology we utilize to achieve good changes may also be used against us.
Image manipulation is a method that allows us to create creative effects. On the other hand, some people abuse this method for deceitful reasons, particularly when it comes to identity verification.
Image modification, like any other technology, has been utilized for both the good and the bad in our imaginations. However, this does not rule out the possibility of picture modification being used for identity verification.
With the aid of various technologies, a number of identity verification companies are stepping forward to assist consumers and organizations in detecting image tampering. Let’s take a look at each of these technologies one by one.
Using Computer Vision to Detect Image Manipulation
One of the most efficient ways for detecting picture alteration is to use computer vision special filters. When it comes to identity verification, it may be a useful tool. This forensic approach determines whether or not a picture has been digitally altered.
Using CNN and AI to detect image manipulation
From doctor pictures and produce false ID papers, cybercriminals use powerful image processing tools such as GNU Gimp and Adobe Photoshop.
Fortunately, there is a technique to check whether or not an image is genuine. The first forensic challenge to address this topic was launched in 2013 by the IEEE Information Forensics and Security Technical Committee.
The group created a public collection of digital pictures shot in varied lighting situations. Then they used algorithms to alter the pictures, including:
- Fill and patch matching based on content (for copying and pasting)
- Healing based on content (for splicing and copying/pasting)
- Seam carving (for image retargeting)
- Clone stamp (for copying/paste)
- Merging mating alpha
A large number of individuals were invited to take part in this challenge and identify photos that were either fabricated or had never been altered. Using their human visual brain, some of the individuals were able to spot faked regions in photographs. According to the findings, CNN has the ability to identify picture fraud. The characteristics of CNN are comparable to those of our visual brain.
Convolutional neural networks, or CNNs, are a type of machine learning that aids in the analysis of visual images. Because of its excellent accuracy, CNN is already being used by several large IT businesses for picture categorization and recognition.
