相关论文: Development of a Fuzzy Expert System based Livelin…

Fingerprint recognition and matching is a common form of user authentication. While a fingerprint is unique to each individual, authentication is vulnerable when an attacker can forge a copy of the fingerprint (spoof). To combat these…

In an era where biometric security serves as a keystone of modern identity verification systems, ensuring the authenticity of these biometric samples is paramount. Liveness detection, the capability to differentiate between genuine and…

Biometric authentication is one of the promising alternatives to standard password-based authentication offering better usability and security. In this work, we revisit the biometric authentication based on "fuzzy signatures" introduced by…

This paper discusses a fuzzy model for multi-level human emotions recognition by computer systems through keyboard keystrokes, mouse and touchscreen interactions. This model can also be used to detect the other possible emotions at the time…

Face liveness detection is an essential prerequisite for face recognition applications. Previous face liveness detection methods usually train a binary classifier to differentiate between a fake face and a real face before face recognition.…

Facial analysis systems have been deployed by large companies and critiqued by scholars and activists for the past decade. Many existing algorithmic audits examine the performance of these systems on later stage elements of facial analysis…

Urban imagery usually serves as forensic analysis and by design is available for incident mitigation. As more imagery collected, it is harder to narrow down to certain frames among thousands of video clips to a specific incident. A…

Facial Liveness Verification (FLV) is widely used for identity authentication in many security-sensitive domains and offered as Platform-as-a-Service (PaaS) by leading cloud vendors. Yet, with the rapid advances in synthetic media…

Fuzzing has proven to be a highly effective approach to uncover software bugs over the past decade. After AFL popularized the groundbreaking concept of lightweight coverage feedback, the field of fuzzing has seen a vast amount of scientific…

With the growing use of biometric authentication systems in the past years, spoof fingerprint detection has become increasingly important. In this work, we implement and evaluate two different feature extraction techniques for…

Human disease diagnosis is a complicated process and requires high level of expertise. Any attempt of developing a web-based expert system dealing with human disease diagnosis has to overcome various difficulties. This paper describes a…

Facial recognition systems have become an integral part of the modern world. These methods accomplish the task of human identification in an automatic, fast, and non-interfering way. Past research has uncovered high vulnerability to simple…

Vulnerable software represents a tremendous threat to modern information systems. Vulnerabilities in widespread applications may be used to spread malware, steal money and conduct target attacks. To address this problem, developers and…

Biometric technologies, especially face recognition, have become an essential part of identity management systems worldwide. In deployments of biometrics, secure storage of biometric information is necessary in order to protect the users'…

Fuzz Testing techniques are the state of the art in software testing for security issues nowadays. Their great effectiveness attracted the attention of researchers and hackers and involved them in developing a lot of new techniques to…

In this paper, we focus on improving the online face liveness detection system to enhance the security of the downstream face recognition system. Most of the existing frame-based methods are suffering from the prediction inconsistency…

Fingerprint-based recognition has been widely deployed in various applications. However, current recognition systems are vulnerable to spoofing attacks which make use of an artificial replica of a fingerprint to deceive the sensors. In such…

Computer vision applications are omnipresent nowadays. The current paper explores the use of fuzzy logic in computer vision, stressing its role in handling uncertainty, noise, and imprecision in image data. Fuzzy logic is able to model…

Fuzzing is a popular vulnerability automated testing method utilized by professionals and broader community alike. However, despite its abilities, fuzzing is a time-consuming, computationally expensive process. This is problematic for the…

Fuzzing has emerged as a powerful technique for finding security bugs in complicated real-world applications. American fuzzy lop (AFL), a leading fuzzing tool, has demonstrated its powerful bug finding ability through a vast number of…