the free encyclopedia that anyone can edit.
Now in Antispoofing Wiki 54 articles.
Our encyclopedia is dedicated to the Liveness detection, Spoofing attacks and Antispoofing measures. Spoofing is a set of malicious techniques, which allow an attacker to pose as someone else, fabricate liveness cues, or synthesize a completely falsified, non-existent person from scratch to gain access to sensitive data, target’s money, device or vehicle control, and so on.
Spoofing attacks have become an especially common practice since the advent of mobile technology. Internet of Things, face recognition and other systems are also quite vulnerable in the light of this threat. Our goal is to select, review and propose the most effective and promising remedies against liveness spoofing.
Liveness detection allows avoiding a vast scope of fraudulent techniques. Swindlers aim at a rich variety of targets: from mobile phones and smart domestic appliances to Automatic Border Control systems. Remote identity proofing is especially vulnerable as it offers a client enrollment process performed at distance. As a result, a number of simple manipulations can result in successful identity theft, reputation damage, loss of data or money, etc.
Proliferation of easy-to-use deepfake tools further aggravates the issue. Regular people can produce falsified media of decent quality, such as face swaps, with just a few clicks. Neither special training/knowledge nor significant computing power are required for that task — plenty of such tools are available online, powered by the cloud technology (Deepfakes Web, SteosVoice).
Together with that, professional culprits will adopt more sophisticated methods to bypass an antispoofing system. There’s a rich cornucopia of tactics, tools, and tricks to emulate liveness. A motivated fraudster is ready to invest months in social engineering, collecting training data to produce a high-quality deepfake, attempting reverse engineering or trying out novel attack methods.
These techniques at times show immense creativity. For example, liveness mimicry can be achieved with simple and easy-to-obtain components: playdough, gelatin-based candy, body paint, glue and construction paper, as well as other widespread items. Even though being cheap to produce, they sometimes succeed at bypassing even advanced security systems.
- Anti-Spoofing and Liveness Detection
- Anti-Spoofing for IoT
- Antispoofing Performance Metrics: Types and Details
- Fingerprint Liveness — General Overview, Practical Application and Vulnerabilities
- Multimodal Liveness Detection — Methods, Issues and Application
- IP Antispoofing — Types and Practical Application
- Notable Cases of Spoofing Attacks and Bypassing Liveness Detection
- Keystroke Dynamics Recognition: Theory, Methods and Application
- Key Companies in Biometrics and Antispoofing
- Presentation Attacks: Types, Instruments and Detection
- Video Injection Attacks
- Liveness Detection: Definition and Overview
- Spoofing: Definition and Overview
- Adversarial Spoofing Attacks
- Facial Deepfakes
- Digital Face Manipulations: Types, Techniques and Countermeasures
- EfficientNet for Deepfake Detection: Architecture, Purpose and Practical Application
- Deepfake Detection Competitions
- Manual Deepfake Detection: General Overview
- Deepfake Datasets: Role and Practical Application
- Cheapfakes: Definition, Overview and Potential Threats
- Deepfake Detection Software: Types and Practical Application
- Deepfake Detection Standardization: Origin, Goals and Implementation
- Notable Deepfake Websites
- Facial Antispoofing: Types, Countermeasures and Challenges
- Facial Anti-Spoofing Certification
- Face Recognition Methods: Complete Overview
- Human Performance in Face Liveness Detection
- Active Facial Liveness Detection
- Passive Facial Liveness Detection: Advantages and Methods
- Face Morphing Detection — Necessity, Techniques and Potential Challenges
- Databases for Face Antispoofing and Recognition
- Iris Liveness Detection — Techniques, Practical Application and Challenges
- Iris Recognition and Liveness Detection Competitions
- Iris Recognition: Techniques, Stages and Databases
- Makeup Presentation Attacks: Techniques, Attack Instruments and Countermeasures
- Impact of Plastic Surgery on Face Recognition
- Retina Recognition: Techniques, Practical Application and Challenges
- Impact of Aging on Face Recognition: Studies, Databases and Recognition Techniques
- Demographic Bias in Facial Recognition and Liveness
- Impact of Partial Occlusion on Face Recognition
- Biometric Obfuscation Attacks
- Facial Liveness Detection Challenges
- Deepfake Detection (10)
- Liveness Overview (14)
- Voice Liveness (6)
- RIDP Liveness (5)
- Facial liveness (19)
In a more challenging scenario, fraudsters basically resort to extreme solutions. These can include applying advanced movie-level makeup, producing highly realistic 3D masks that emulate body heat, severing a deceased person’s finger/extracting an eye and even undergoing a plastic surgery.
Fake media detection is also an essential part of antispoofing. If not properly addressed and timely prevented, it can result in disastrous consequences: social instability, public opinion manipulation, defamation, etc. Plus, sociology experts indicate two negative phenomena induced by the rise of fake media: liar’s dividend and reality apathy.
Antispoofing techniques and liveness detection solutions are designed with all of these threats in mind. They encompass a wide range of concepts, ideas and visions. Voice, retina, iris, fingerprint, and facial recognition employ liveness parameters to tell a real person from a perpetrator, which is the main goal of antispoofing as such.
The antispoof checking analyzes the input data — such as the light distribution, face coloring, depth and geometry, pop noises, general liveness signals — to spot the fake body parts, facial alterations, replay attacks and synthesized audiovisuals. Detecting them is the main goal of antispoofing as such.
In our articles, we discuss the most successful methods and the best antispoofing tools, as well as liveness detection techniques. We also focus on the international antispoofing and liveness standards, attack types and their classification, terminology, and other aspects of the matter. To validate the data presented, we quote scientific publications, as well as popular media, and news dedicated to liveness security and antispoofing.
Opinions and additions made by the viewers with an appropriate degree of training, education and professional experience are welcome in our facial liveness Wiki.