Analytics, Privacy and Security for IoT and Big Data
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 19758
Special Issue Editors
Interests: artificial intelligence; big data; computer networks; computer security; information theory; IoT; multimedia forensics
Special Issues, Collections and Topics in MDPI journals
Interests: SCADA security; ubiquitous healthcare; information security; mobile computing; IoT
Special Issues, Collections and Topics in MDPI journals
Interests: distributed systems; information security; network management; network security; network systems; open source software; wireless networks
Special Issues, Collections and Topics in MDPI journals
Interests: computer and network security; multimedia forensics; error-correcting codes; information theory
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Internet of Things (IoT) is a network of smart devices with pervasive and autonomous communication through internet connectivity. It has emerged as a powerful and promising technology with significant technical, social, and economic impacts. However, just as IoT brings many opportunities, it also brings new threats that require holistic security thinking that spans new business models, technology and standards, and regulation. With the increase in deployment of IoT devices, the amount of data generated by these devices also increases, hence resulting in a need for large-scale data processing systems to process and extract information for efficient and impactful decision making that will improve quality of living. However, most of these smart devices fail to address even simple challenges for security and privacy: They do not protect the data they gather and transmit, they do not use encrypted connections, they use simplistic credentials, etc. Therefore, IoT raises significant challenges regarding security and privacy. Having large numbers of connected devices deployed everywhere around us, e.g., in homes, offices, buses, on the street, monitoring the everyday activities of citizens raises issues regarding user and data privacy.
On the other hand, even though it is desirable to use the large amount of data generated from IoT devices in designing intelligent systems for making informed decisions in applications such as image recognition, activity detection, etc., concerns regarding data security and privacy arise when sensitive information is involved. Mainly, the distribution of sensitive data in a multiparty computation environment may carry a high risk of secrecy leakage or data misuse when its usage is not satisfactorily vetted. Moreover, the sensitivity of intelligent systems to adversarial attacks may prevent large-scale deployment of these systems, thereby losing the advantages of a benign system.
The main objective of this Special Issue is to collect contributions by leading-edge researchers from academia and industry and show the latest research results in the rapidly developed field of analytics, privacy, and security for IoT and Big Data, therefore providing a valuable information venue to researchers as well as practitioners. Original and unpublished high-quality research results are solicited to explore various challenging topics which include but are not limited to:
Potential topics include but are not limited to:
- Authentication and access control for IOT;
- Big data analytics for threat and attack prediction;
- Big data forensics;
- Big data outsourcing;
- Big data security for IoT;
- Biometric technologies and systems for IoT;
- Blockchain in the IoT;
- Cross-domain trust management in smart networks;
- Data security and cryptosystems for IoT;
- Decentralized and distributed security architectures;
- Detection and prevention of IoT-based security attacks;
- Embedded security and privacy in IoT devices;
- Ethics and legal considerations in IoT;
- Forensics for IoT;
- GDPR in the IoT;
- Intrusion detection and prevention for mobile and IOT platforms;
- IoT security mechanisms targeting application layer protocols;
- IoT-based malware mitigation;
- Lightweight security solutions;
- MAC layer security protocols for IoT applications;
- Malware detection, analysis, and mitigation for IOT networks
- Mobile system security;
- On-device authentication, authorization, and access control in IoT;
- Physical layer security in the IoT;
- Privacy and anonymization techniques in IoT;
- Privacy and security for smart homes and smart cities;
- Resource-savvy intrusion detection for Networks of Things;
- Secure and privacy preserving data mining and aggregation in IoT applications;
- Secure authentication of IoT devices;
- Secure spectrum management solutions for wireless IoT communications;
- Secure wireless channel and traffic models;
- Security and privacy by design architectures for IoT;
- Security and privacy in big databases;
- Security and privacy in heterogeneous IoT;
- Security and privacy in IoT applications;
- Security of sensors and actuators;
- Trust management IoT architectures.
Prof. Dr. Luis Javier García Villalba
Prof. Dr. Tai-hoon Kim
Dr. Robson de Oliveira Albuquerque
Dr. Ana Lucila Sandoval Orozco
Guest Editors
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Keywords
- Artificial Intelligence
- Big data
- Big data applications
- Cloud computing
- Computer security
- Cybersecurity
- Data analysis
- Data privacy
- Internet of Things
- Interoperability
- Standardization
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