Data Instrumentation from IoT Network Traffic as Support for Security Management

The Internet of Things revolutionizes human life by inaugurating scenarios such as smart homes. However, IoT devices contain much sensitive information about users and devices from a security and privacy perspective. Through traffic-based attacks, adversaries map changes in traffic rates to a partic...

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Bibliographic Details
Published in:IEEE eTransactions on network and service management 2023-06, Vol.20 (2), p.1-1
Main Authors: Vergutz, Andressa, dos Santos, Bruna V., Kantarci, Burak, Nogueira, Michele
Format: Article
Language:English
Subjects:
Communications traffic
Cybersecurity
Feature extraction
Instruments
Internet of Things
IoT
network data instrumentation
Network security
Privacy
Security
Security management
Smart buildings
smart home
Smart homes
Telecommunication traffic
Traffic information
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Summary:The Internet of Things revolutionizes human life by inaugurating scenarios such as smart homes. However, IoT devices contain much sensitive information about users and devices from a security and privacy perspective. Through traffic-based attacks, adversaries map changes in traffic rates to a particular in-home user's actions. An efficient IoT data instrumentation may protect users against traffic-based attacks by giving valuable information to adaptive network security solutions. Nonetheless, no work performs data instrumentation or uses feature exploration to reveal relevant features to assist network security management. Thus, this article introduces IoTReGuard, an IoT Method to Reveal and Guard IoT Network Traffic Features. IoTReguard aims to explore network traffic features to reveal the most relevant ones and hide them to protect users' privacy. By IoT network feature exploration and data instrumentation, IoTReGuard provides valuable information on network traffic features to mask critical features. Results showed that IoTReGuard reduced from 70% to 20% of F1-Score on identifying the IoT devices, improving user privacy.
ISSN:1932-4537
1932-4537
DOI:10.1109/TNSM.2022.3233673