Cheap Fakes vs Deep Fakes–Rising Identity Fraud Threats in the Digital Age

Imagine that the friend you are talking to is scamming or maybe he’s using your fake identity to access your bank account. The cheap fakes vs deepfakes are changing the entire online environment by exploiting normal editing tools and advanced AI technology. However, such rising threats of identity fraud, erode the public trust in online interaction and present the essential risks–that businesses and individuals are experiencing. 

The rise of these fraudulent technologies provides scammers with new opportunities to create fake identities and engage in more complex digital interactions. Whether it’s simply altering a photo with standard editing software or generating an entirely new face using AI, the line between reality and deception has become increasingly blurred. Moreover, this kind of online counterfeiting compromises personal security and presents additional challenges for online verification systems designed to keep fraudsters at bay.

Cheap Fake Perception: A Low-Effort Fraud

Cheap fakes refer to low-tech fraud and media manipulations created using standard editing tools like Photoshop. This type of fraud also includes basic video or audio edits, which differ from deepfakes. While deepfakes rely on advanced AI technology, cheap fakes require minimal technical skills and resources. Common examples of cheap fakes include alterations to names or dates on identification documents. Fraudsters often reuse edited documents or recycle old footage with misleading captions. These methods are frequently employed to spread misinformation and trick basic verification systems.

Cheap fakes serve as a straightforward tool for fraudsters to forge documents, create fake accounts, or bypass verification processes. Additionally, these fakes are inexpensive, simple to produce, and easily accessible, which heightens the associated risks. Although they are quite different from deepfakes, cheap fakes highlight a challenge in the digital age, undermining trust online. 

Key Differences Between Cheapfakes and Deepfakes

While cheap fakes may be unsophisticated, the ability to deceive and consequently spur identity fraud should by no means be undermined in this age of wildfire-like dissemination of incorrect data. Now, let’s explore the key differences between cheap fakes and their more advanced counterparts—deepfakes. 

Threats Cheapfakes Pose in Identity Fraud

Cheap fakes are unsophisticated but they can have prominent results in the identity fraud sphere. Let’s discuss the important threat that particularly highlights risks due to low-tech fraud: 

1. Low-tech fraud frequently involves fake IDs or basic documents—usable to access restricted areas or while opening bank accounts.
2. The wrong use of cheaper editing tools for fake credentials and deceiving the fundamental safety estimation. 
3. Systems’ manipulation that have low latest technological validation makes the detection process more complicated. 
4. Both exploit weaknesses in online verification systems. Most present weaknesses in manipulated physical or digital documents. Highly convincing AI-generated photos and videos can be made.
5. Generation of fake identity proofs that seem real under normal inspection. 
6. Social engineering scheme usage to get trust or access to sensitive information. 
7. Deceiving the initial identity checks for financial scams, for instance, requesting payday loans or producing scam bank accounts. 
8. Invading the medical records to get illegal access to healthcare services or fake prescription drugs. 
9. Utilizing previous or openly available ID templates to generate a fabricated paper. 
10. Taking advantage of weak online identity checks to create fake profiles for scams or harassment.
11. Fooling automated security systems that rely on pictures, makes it harder to catch fake IDs. 

Warning Deepfakes Pose in Identity Fraud

Deepfake threats are drastically evolving and becoming a bigger challenge in identity safety, manipulating the verification systems’ weaknesses. It also presents the latest challenges to various industries. Let’s discuss some of the advanced-level insights that show risks connected to deepfakes and their association with identity fraud, integrating deepfake detection online: 

1. Scammers utilize deepfake technology to generate highly realistic online personas that fool the biometric verification systems. 
2. It leads to illegal access to sensitive accounts.                                                    
3. The latest deepfake tools have enabled immediate mocking in video calls. 
4. It also creates complications in the identification of fraud interactions and demands experienced deepfake detection online solutions. 
5. However, deepfake-generated visuals and audio are being used for the targeted phishing attacks to eliminate the credentials. 
6. Deepfake techniques are often accompanied by forged digital documents, which are then indistinguishable from authentic credentials under traditional validation mechanisms.
7. Deepfakes are being customized to evade traditional liveness detection protocols; hence there is a dire need for in-real-time deepfake-detecting online tools.
8. Scammers use deepfakes to impersonate high-profile individuals trapping others to get large financial deals.
9. Also, it is used to corroborate false stories in arguments, insurance, or written filings by telling against the validity of the evidence.
10. Nowadays, deepfakes are created through “as-a-service” platforms, allowing uninhibited actors to access sophisticated identity fraud tools.
11. Cybercriminals bring synthetic media into phishing emails or malware campaigns, making their attacks more convincing and potent.
12. Deepfakes falling short on strong detentions online open up the house and the identity checks to fraudsters as they involve using AI-generated visuals.

AI’s Role in Fraud and Fraud Prevention—A Bigger Picture

Artificial Intelligence (AI) has proven to be an essential tool in the prevention of fraud, more so in response to cheap fakes vs deepfakes. Artificial intelligence involves detailed analysis by machine learning algorithms over expansive datasets that delve into minute inconsistencies within media, for instance, unnatural movements or anomalies in facial textures. 

The latest AI model is continuously evolving with the rising threats to facilitate robust security against experienced fraud attacks. Several tools depend on artificial intelligence to generate fake identities for training purposes. It makes it possible to guide the detection system speedily. Furthermore, AI has enabled deepfake and cheap fake detection systems to differentiate between simple and latest forgeries to assist businesses and individuals. 

Fighting the Threat: Solutions for Cheapfakes and Deepfakes

Political deepfakes can erode public confidence and perception while spreading misinformation. However, some fake profiles on social media forums use deepfake-generated visuals and audio. Such fake material usually fools the users and causes scams or traps. The expert scammers are now capable enough to hack the live videos, exploiting them immediately in fake events, or changing the narratives. 

Facia is a deepfake detection software that authorizes governments, media forums, and other private organizations. The main purpose of this software is to protect private and government organizations alongside individuals against the deepfake harmful effects, for instance, exploited content. 

The deepfake detection technology of Facia has revealed an accuracy level of 90% in longer testing, which makes it the current leading solution in the market. Cheapfakes rely on basic edits, so it identifies audio-visual mismatches as well as pixel-level analysis. Learn more from our explainer video here.