Privacy Preserving in Ubiquitous Computing: Challenges &amp;#x00026; Issues

Ma, Tinghuai; Kim, Shin-Dug; Wang, Jun; Zhao, Yawei

doi:10.1109/icebe.2008.55

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…Traditional solutions to these issues are based on three steps, namely: user's identification (user declares his identity), authentication (the system verify the authenticity of this claims) and authorisation (user is granted specific access rights) [46]. However, these issues have only recently being addressed in ubiquitous environments [29], whereby they also contrast with the need for natural forms of interaction that do not require active intervention by the user. One initiative that seeks to address this issue of ubiquitous interaction is that of Ambient Intelligence (AmI) [1].…”

Section: In Our Scenario Greg Plays a Treasure Game What Happens Ifmentioning

confidence: 99%

Facilitating Ubiquitous interaction Using Intelligent Agents

Campbell

Collier

Dragone

et al. 2012

Studies in Computational Intelligence

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Facilitating intuitive interaction is a prerequisite for the ubiquitous computing paradigm in all its manifestations. How to achieve such interaction in practice remains an open question. Such interfaces must be perceived as being intuitive across a variety of contexts, including those of the hosting devices. Indeed, the heterogeneity of the device population raises significant challenges. While individual devices and the interaction modalities supported by, each satisfy the requirements of individual domains, integrating diverse devices such that the user experiences is perceived as consistent and intuitive is problematic. This chapter discusses and illustrates how intelligent agents may be harnessed for integrating a range of diverse interface and interaction modalities such that the ubiquitous user interface concept may be validated.

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Section: In Our Scenario Greg Plays a Treasure Game What Happens Ifmentioning

confidence: 99%

Facilitating Ubiquitous interaction Using Intelligent Agents

Campbell

Collier

Dragone

et al. 2012

Studies in Computational Intelligence

View full text Add to dashboard Cite

show abstract

“…There have been many works in the area of privacy preserving in ubiquitous computing [17], [23], [24]. They emphasized the importance of privacy preserving, clarified the problems that we must not ignore.…”

Section: Related Workmentioning

confidence: 99%

Privacy preserving in ubiquitous computing: Classification & hierarchy

Shen

Wang

et al. 2011

COMSIS J

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In this paper, we adopt the classification of personal information and hierarchy of services to build a privacy system, in which one communicates with each other via pipes with different security levels. In each level, one has the corresponding rights to access each other. The requesters are not able to be infringed based on the personal information that service obtains from service providers. Privacy system can decrease the interaction, while in other circumstance the system strengthens and enhances the privacy preserving. Thus we strike a balance between two goals of Ubiquitous Computing: interaction and privacy preserving.

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“…Meanwhile, privacy concerns regarding IoT devices have arisen over the past decades as IoT ecosystems rapidly expand to industries, cities, houses, and personal wearable devices [6][7][8]. Sensor data are highly detailed, precise, and personal.…”

Section: Introductionmentioning

confidence: 99%

Efficient Lp Distance Computation Using Function-Hiding Inner Product Encryption for Privacy-Preserving Anomaly Detection

Ryu

Jeon

Hong

et al. 2023

Sensors

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In Internet of Things (IoT) systems in which a large number of IoT devices are connected to each other and to third-party servers, it is crucial to verify whether each device operates appropriately. Although anomaly detection can help with this verification, individual devices cannot afford this process because of resource constraints. Therefore, it is reasonable to outsource anomaly detection to servers; however, sharing device state information with outside servers may raise privacy concerns. In this paper, we propose a method to compute the Lp distance privately for even p>2 using inner product functional encryption and we use this method to compute an advanced metric, namely p-powered error, for anomaly detection in a privacy-preserving manner. We demonstrate implementations on both a desktop computer and Raspberry Pi device to confirm the feasibility of our method. The experimental results demonstrate that the proposed method is sufficiently efficient for use in real-world IoT devices. Finally, we suggest two possible applications of the proposed computation method for Lp distance for privacy-preserving anomaly detection, namely smart building management and remote device diagnosis.

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Privacy Preserving in Ubiquitous Computing: Challenges & Issues

Cited by 4 publications

References 15 publications

Facilitating Ubiquitous interaction Using Intelligent Agents

Facilitating Ubiquitous interaction Using Intelligent Agents

Privacy preserving in ubiquitous computing: Classification & hierarchy

Efficient Lp Distance Computation Using Function-Hiding Inner Product Encryption for Privacy-Preserving Anomaly Detection

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