Conference Information

S/P-IoT 2022: International Workshop on Security and Privacy-preserving Solutions in the Internet of Things

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Submission Date:
2022-08-31
Notification Date:
2022-09-12
Conference Date:
2022-10-17
Location:
Online
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Call For Papers

S/P-IoT 2022 (International Workshop on Security and Privacy-preserving Solutions in the Internet of Things) is an academic conference held in Online on 2022-10-17. The paper submission deadline is 2022-08-31. Acceptance notifications are sent on 2022-09-12.

Scope In the last few years, the Internet of Things (IoT) has seen rapid developments due to device miniaturization and cost reduction. It aims to connect all objects through the Internet. These cooperative systems can provide fast, cost-effective, and safe solutions for many applications, including smart cities, autonomous vehicles, and drones. On the other hand, many IoT devices collect sensitive data, such as the number of people in an important building or brake oil amount in an autonomous vehicle, which should not be unintentionally disclosed, in addition to personal or confidential information. Due to the large number of devices in IoT systems, the possibility of information leakage or privacy breach is high. To prevent this, each device applies a privacy-preserving method, which is applied in order to hinder adversaries from finding the sensitive data and the identity of owners. Unfortunately, most IoT devices are in general battery-powered and/or are not capable of providing a fast and reliable reply to user applications. In this respect, energy consumption is also a big challenge while being able to preserve the privacy of IoT devices. This workshop aims to showcase the latest Original Research, Tutorial, and Review articles on these topics. Topics Possible topics for submissions include but are not limited to: S/P models for IoT-based smart cities Privacy-preserving models for IoT applications S/P in service deployment for IoT Software-defined networking support for S/P Semantic web support for S/P Cyber Security modelling for S/P AI-based solutions for Cyber Security
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