Anonymization: Securing privacy in IoT. Issue 6 (17th August 2020)

• Record Type: Journal Article
• Authors: Kaur, Jashanpreet; Sengupta, Jyotsna
• Is Part Of: Journal of information & optimization sciences. Volume 41:Issue 6(2020)
• Page Start: 1463
• Page End: 1477
• Publication Date: 2020-08-17
• Subjects: 68T05 -- 68P27; Anonymization -- Neural Network -- Privacy -- k-anonymity; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2020.1802123
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: The convergence of object automation with the association of internet system has become very communal in our routine life. At home, health centres, industries etc. each field has internet-related control systems installed to support organization's proper execution, thereby, increasing the efficiency and saving time. Beside multi-fold benefits, IoT has brought a plethora of privacy risks and security issues. To maintain the privacy of both, the user and the objects many counter measures are carried out and techniques have been found to address illegitimate access and minimize their effect on private data, communication, location etc. The paper focuses on the IoT threats related to individual's identity and the various techniques like anonymization to preserve and protect individual's identity.