Privacy-preserving IoT devices
Almohaimeed, Abdulrahman Gampa, Srikanth Singh, Gurtaj
Almohaimeed, Abdulrahman
Gampa, Srikanth
Singh, Gurtaj
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Authors
Almohaimeed, Abdulrahman
Gampa, Srikanth
Singh, Gurtaj
Gampa, Srikanth
Singh, Gurtaj
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Time Period
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Original Date
Digitization Date
Issue Date
2019-05
Type
Conference paper
Genre
Keywords
Internet of Things (IoT),k-Anonymity,k-Nearest Neighbors,Privacy,Published data,Software-Defined Networking (SDN)
Subjects (LCSH)
Citation
A. Almohaimeed, S. Gampa and G. Singh, "Privacy-Preserving IoT Devices," 2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT), Farmingdale, NY, USA, 2019, pp. 1-5
Abstract
With the recent exponential increase in network-based devices, it is expected that billions of devices will be connected to the Internet. In enabling this growth, effectively securing Internet of Things (IoT) devices while maintaining performance levels presents major challenges. As IoT attackers always rely on previously collected data to initiate their attacks, they must continuously expose communication links to capture transmitted data and to collect sensitive information. In this paper, we propose an IoT privacy model that will protect a device's identity during data transmission by applying a Moving Target Defense (MTD). It aims to increase the complexity and uncertainty of potential attacks. According to the results of our experiment, the proposed model helps to ensure that if any data leakage occurs during transmission, the sensitive data collected by attackers will not be valid for the initiation of new connections.
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Publisher
IEEE
Journal
Book Title
Series
2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT);