Securing Big Data Analytics for Cyber-Physical Systems
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Cybersecurity".
Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 11144
Special Issue Editors
Interests: cyber security and privacy; cyber-physical systems/Internet of Things; data and machine learning-driven applications
Special Issues, Collections and Topics in MDPI journals
Interests: big data analytics; cybersecurity, and networking in cyber physical systems and IoT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in edge computing, artificial intelligence, and big data technologies have given rise to cyber-physical systems (CPS)/Internet of Things (IoT), which are emerging paradigms to meet the demands of flexibility, agility, and ubiquitous accessibility of cyberspace. The proliferation of smart devices and applications in our everyday lives have generated increasingly tremendous data. With the help of central/edge servers or other devices, smart nodes are now capable of extracting insightful analytics from collected data, providing unprecedented opportunities of data-driven economy that finds applications in diverse sectors ranging from smart health and smart transportation to predictive maintenance and smart manufacturing, etc. Despite this ongoing advancement in CPS/IoT, there are growing concerns regarding the security and privacy of data owners when they grant smart applications direct access to sensors and their data. Particularly, CPS/IoT devices are vulnerable to different kinds of attacks such as Mirai Botnet, webcam hack, DDoS attacks, etc. The intrinsic heterogeneity of data, application, hardware, and software in CPS/IoT systems further expands the attack surface and escalates the challenges of deploying universal security strategies. Furthermore, IoT-based systems that handle both security and privacy-sensitive data (i.e., data in healthcare, energy, transportation critical infrastructure systems) need to promptly react to adversarial activities and prevent the disclosure of privacy-sensitive data. Therefore, how to secure data-driven analytics is an important issue in CPS/IoT systems. This special issue aims at the state-of-the-art research efforts on secure data-driven analytics for CPS/IoT. The topics of interest include, but are not limited to:
- Reliability, consistency, robustness and security of AI in CPS/IoT
- IoT data analytics for anomaly detection
- Security management of IoT devices based on data knowledge
- Adversarial example attacks and defense in IoT Systems
- Threat modelling and risk assessment in IoT
- Security of blockchain and decentralized schemes for IoT
- Deep learning-based security solutions for intelligent CPS and IoT
- Secure and privacy-preserving CPS and IoT architectures
- Security analysis and enhancement in edge and IoT
- Privacy protection in edge computing assisted with evolving IoT
- Evaluation platforms and hardware-in-the-loop testbeds for AI-enabled IoT environments
- Foundation and application of data science in CPS/IoT systems
Prof. Dr. Wei Yu
Dr. Weixian Liao
Dr. Fan Liang
Guest Editors
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Keywords
- Cyber-physical systems (CPS)
- Internet of Things (IoT)
- security and vulnerability analysis
- big data analytics
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