TY - GEN
T1 - PEEP with Cloud Encryption
T2 - 15th International Conference on Innovations in Information Technology, IIT 2023
AU - Alnuaimi, Reem
AU - Alnajjar, Fady
AU - Abdulmouti, Hassan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Recent advancements in image-based Facial emotion recognition systems offer deep insights into human psychological states, holding promise for valuable applications such as measuring customer satisfaction in public service areas or student engagement in classrooms. However, the potential impacts on the privacy of individual users of these systems cannot be ignored. In our study, we present PEEP (Privacy using EigEnface Perturbation) integrated with cloud storage encryption as a dual-layered approach to address privacy concerns in such systems. PEEP processes facial data by extracting eigenfaces and adding specific noise, ensuring the anonymity of identities while retaining the capability to recognize emotions. In tandem, cloud storage encryption guarantees that data, if intercepted during transmission or storage, stays encrypted and secure. This combined strategy offers an enhanced privacy solution for emotion recognition systems on remote servers. This study aligns with international initiatives to promote the responsible development and application of artificial intelligence, while emphasizing the importance of upholding human ethical standards and security.
AB - Recent advancements in image-based Facial emotion recognition systems offer deep insights into human psychological states, holding promise for valuable applications such as measuring customer satisfaction in public service areas or student engagement in classrooms. However, the potential impacts on the privacy of individual users of these systems cannot be ignored. In our study, we present PEEP (Privacy using EigEnface Perturbation) integrated with cloud storage encryption as a dual-layered approach to address privacy concerns in such systems. PEEP processes facial data by extracting eigenfaces and adding specific noise, ensuring the anonymity of identities while retaining the capability to recognize emotions. In tandem, cloud storage encryption guarantees that data, if intercepted during transmission or storage, stays encrypted and secure. This combined strategy offers an enhanced privacy solution for emotion recognition systems on remote servers. This study aligns with international initiatives to promote the responsible development and application of artificial intelligence, while emphasizing the importance of upholding human ethical standards and security.
KW - Cloud Storage Encryption
KW - Emotion Recognition Systems
KW - PEEP (Privacy using EigEnface Perturbation)
KW - Privacy Concerns
UR - http://www.scopus.com/inward/record.url?scp=85182917470&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85182917470&partnerID=8YFLogxK
U2 - 10.1109/IIT59782.2023.10366494
DO - 10.1109/IIT59782.2023.10366494
M3 - Conference contribution
AN - SCOPUS:85182917470
T3 - 2023 15th International Conference on Innovations in Information Technology, IIT 2023
SP - 186
EP - 189
BT - 2023 15th International Conference on Innovations in Information Technology, IIT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 November 2023 through 15 November 2023
ER -