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This paper explores behavioral biometrics, an emerging authentication method leveraging unique user behavior patterns for continuous security. This dynamic approach offers enhanced protection compared to traditional methods, yet significant challenges must be addressed. A key concern, examined herein, is accuracy; false positives and false negatives can undermine system effectiveness. User frustration arises from false positives, while false negatives create security vulnerabilities. The work emphasizes the need for careful system tuning and advanced machine learning to mitigate these errors. Data privacy and security are also paramount, given the sensitive, non-replaceable nature of the collected information. The paper highlights the importance of robust security measures, user transparency, and informed consent. Furthermore, it acknowledges that natural human behavioral variability, influenced by physical and environmental factors, can impact authentication accuracy, necessitating adaptive systems. In conclusion, addressing these technical and ethical challenges is crucial for realizing the full potential of behavioral biometrics.
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Privacy in the Age of Autonomous Vehicles
To prepare for the age of the intelligent, highly connected, and autonomous vehicle, a new approach to concepts of granting consent, managing privacy, and dealing with the need to interact quickly and meaningfully is needed. Additionally, in an environment where personal data is rapidly shared with a multitude of independent parties, there exists a need to reduce the information asymmetry that currently exists between the user and data collecting entities. This Article rethinks the traditional notice and consent model in the context of real-time communication between vehicles or vehicles and infrastructure or vehicles and other surroundings and proposes a re-engineering of current privacy concepts to prepare for a rapidly approaching digital future. In this future, multiple independent actors such as vehicles or other machines may seek personal information at a rate that makes the traditional informed consent model untenable. This Article proposes a two-step approach: As an attempt to meet and balance user needs for a seamless experience while preserving their rights to privacy, the first step is a less static consent paradigm able to better support personal data in systems which use machine based real time communication and automation. In addition, the article proposes a radical re-thinking of the current privacy protection system by sharing the vision of “Privacy as a Service” as a second step, which is an independently managed method of granular technical privacy control that can better protect individual privacy while at the same time facilitating high-frequency communication in a machine-to-machine environment.
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- Award ID(s):
- 1654085
- PAR ID:
- 10039659
- Date Published:
- Journal Name:
- Washington and Lee law review
- Volume:
- 73
- Issue:
- 2
- ISSN:
- 0043-0463
- Page Range / eLocation ID:
- 724-755
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- The DOI is not currently available.
