Epistemological Foundation of Biometrics

Ghilardi, Giampaolo; Keller, Flavio

doi:10.1007/978-94-007-3892-8_2

Cited by 4 publications

(3 citation statements)

References 18 publications

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“…First-generation biometrics can confirm a person’s identity in a quick and reliable way, or authenticate them in different contexts, and law enforcement is one of the areas where such solutions are employed in practice [ 152 ]. The primary purpose of first-generation biometrics is identity verification, such as facial recognition, and the technology is built around simple sensors that capture physical features and store them for later use [ 153 ]. Second-generation biometrics can also be used to detect emotions, with electro-physiologic and behavioral biometrics (e.g., based on ECG, EEG, and EMG) as examples of such technologies [ 154 ].…”

Section: Brain and Biometric Affect Sensorsmentioning

confidence: 99%

A Review of AI Cloud and Edge Sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States

Kaklauskas

Abraham

Ubarte

et al. 2022

Sensors

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Affective, emotional, and physiological states (AFFECT) detection and recognition by capturing human signals is a fast-growing area, which has been applied across numerous domains. The research aim is to review publications on how techniques that use brain and biometric sensors can be used for AFFECT recognition, consolidate the findings, provide a rationale for the current methods, compare the effectiveness of existing methods, and quantify how likely they are to address the issues/challenges in the field. In efforts to achieve the key goals of Society 5.0, Industry 5.0, and human-centered design better, the recognition of emotional, affective, and physiological states is progressively becoming an important matter and offers tremendous growth of knowledge and progress in these and other related fields. In this research, a review of AFFECT recognition brain and biometric sensors, methods, and applications was performed, based on Plutchik’s wheel of emotions. Due to the immense variety of existing sensors and sensing systems, this study aimed to provide an analysis of the available sensors that can be used to define human AFFECT, and to classify them based on the type of sensing area and their efficiency in real implementations. Based on statistical and multiple criteria analysis across 169 nations, our outcomes introduce a connection between a nation’s success, its number of Web of Science articles published, and its frequency of citation on AFFECT recognition. The principal conclusions present how this research contributes to the big picture in the field under analysis and explore forthcoming study trends.

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Section: Brain and Biometric Affect Sensorsmentioning

confidence: 99%

A Review of AI Cloud and Edge Sensors, Methods, and Applications for the Recognition of Emotional, Affective and Physiological States

Kaklauskas

Abraham

Ubarte

et al. 2022

Sensors

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“…person, and permanent. 13 According to Article 29 Data Protection Working Party (A29 WP), an advisory body set up by EU Data Protection Directive, 14 that was replaced by European Data Protection Board but whose opinions stay valid, typical behavioral biometric data "include hand-written signature verification, keystroke analysis, gait analysis, way of walking or moving, patterns indicating some subconscious thinking like telling a lie, etc." 15 As this definition refers to patterns of thinking and moving that are then manifested and recorded in an objectively perceivable manner, online behavior of a person perceivable through her specific usage of devices or contents searching patterns should also fall under the definition of behavioral data if it serves as a means for unique identification.…”

Section: Biometric Data Under the Gdprmentioning

confidence: 99%

“…From a semantic point of view, "unique identification" can refer to recognizing someone as being the one and only person. 16 According to A29 WP, however, this term is relative as it 13 16 According to a dictionary, the term "to identify" means "to recognize or establish as being a particular person or thing", while "unique" can be understood as Moreover, it is generally known that no type of biometrics is fully reliable. Biometric accuracy differs with regard to the technology used.…”

Section: Biometric Data Under the Gdprmentioning

confidence: 99%

Online Behavior Recognition: Can We Consider It Biometric Data under GDPR?

Krausová

2018

MUJLT

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Our everyday use of electronic devices and search for various contents online provides valuable insights into our functioning and preferences. Companies usually extract and analyze this data in order to predict our future behavior and to tailor their marketing accordingly. In terms of the General Data Protection Regulation such practice is called profiling and is subject to specific rules. However, the behavior analysis can be used also for unique identification or verification of identity of a person. Therefore, this paper claims that under certain conditions data about online behavior of an individual fall into the category of biometric data within the meaning defined by the GDPR. Moreover, this paper claims that profiling of a person can not only be done upon existing biometric data as biometric profiling but it can also lead to creation of new biometric data by constituting a new biometric template. This claim is based both on legal interpretation of the concepts of biometric data, unique identification, and profiling as well as analysis of existing technologies. This article also explains under which conditions online behavior can be considered biometric data under the GDPR, at which point profiling results in creation of new biometric data and what are the consequences for a controller and data subjects.

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