TY - GEN
T1 - Differential Privacy with Weighted for Privacy-Preservation in Human Activity Recognition
AU - Fujimoto, Ryusei
AU - Nakamura, Yugo
AU - Arakawa, Yutaka
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Many services based on human activity recognition (HAR) have been developed; however, user activity data include a large amount of private information. Although privacy protection is important in activity recognition, it has not been sufficiently explored. Therefore, we propose a privacy-preserving mechanism for HAR services that uses differential privacy. The proposed method reduces the user recognition accuracy to a level that satisfies the privacy requirements by adding weighted noise to the features in the learning model construction and then improves the activity recognition accuracy (service usefulness). The results indicate that when the privacy requirement is defined as less than the probability of a user being identified by chance, the proposed method improves the activity recognition accuracy by approximately 10 % compared to the conventional method.
AB - Many services based on human activity recognition (HAR) have been developed; however, user activity data include a large amount of private information. Although privacy protection is important in activity recognition, it has not been sufficiently explored. Therefore, we propose a privacy-preserving mechanism for HAR services that uses differential privacy. The proposed method reduces the user recognition accuracy to a level that satisfies the privacy requirements by adding weighted noise to the features in the learning model construction and then improves the activity recognition accuracy (service usefulness). The results indicate that when the privacy requirement is defined as less than the probability of a user being identified by chance, the proposed method improves the activity recognition accuracy by approximately 10 % compared to the conventional method.
UR - http://www.scopus.com/inward/record.url?scp=85164190622&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85164190622&partnerID=8YFLogxK
U2 - 10.1109/PerComWorkshops56833.2023.10150239
DO - 10.1109/PerComWorkshops56833.2023.10150239
M3 - Conference contribution
AN - SCOPUS:85164190622
T3 - 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023
SP - 634
EP - 639
BT - 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023
Y2 - 13 March 2023 through 17 March 2023
ER -