Privacy Preserving Anomaly Detection on Homomorphic Encrypted Data from IoT Sensors

arXiv:2403.09322v1 Announce Type: new
Abstract: IoT devices have become indispensable components of our lives, and the advancement of AI technologies will make them even more pervasive, increasing the vulnerability to malfunctions or cyberattacks and raising privacy concerns. Encryption can mitigate these challenges; however, most existing anomaly detection techniques decrypt the data to perform the analysis, potentially undermining the encryption protection provided during transit or storage. Homomorphic encryption schemes are promising solutions as they enable the processing and execution of operations …

advancement ai technologies anomaly detection arxiv can challenges components cs.cr cyberattacks data decrypt detection devices encrypted encrypted data encryption iot iot devices privacy privacy concerns privacy preserving sensors techniques technologies vulnerability