posted by user: vitalyford || 948 views || tracked by 2 users: [display]

DLIS 2022 : Deep Learning for IoT Security - Frontiers in Big Data Journal

FacebookTwitterLinkedInGoogle

Link: https://www.frontiersin.org/research-topics/24532/deep-learning-for-iot-security
 
When N/A
Where N/A
Abstract Registration Due Nov 30, 2021
Submission Deadline Jan 31, 2022
Categories    machine learning   deep learning   IOT   security
 

Call For Papers

With the availability of high-speed internet and smart sensors, IoT applications like smart homes, smart cities, connected healthcare, smart vehicular network, smart retail and supply chain, etc., are emerging with rapid speed. It is estimated that there were more than 26.66 billion IoT devices active in 2020, and this is expected to grow to 75 billion by 2025. Every second, a massive amount of data is being generated, shared, and processed. IoT applications are changing how people learn and work, while heterogeneity, ubiquity, and a massive scale of IoT are exposing us to increasingly serious security threats at the same time. The security vulnerabilities in IoT are made evident by several high-profile hacks in recent years, including the late 2016 Mirai malware DDoS attacks and the 2017 casino fish tank IoT thermometer hacking.

With the popularity of big data, the use of deep learning has been growing in a wide range of cybersecurity applications like intrusion and malware detection, user authentication (biometrics), user privacy, etc. Deep learning can be used to process and learn from the underlying IoT data to improve the threat assessment and attack identification as well as recognize breaches within the IoT ecosystem. Deep learning can also be applied to identify advanced threats such as organization profiling, infrastructure vulnerabilities, and potential interdependent vulnerabilities and exploits. Deep learning can significantly change the cybersecurity landscape. For example, traditional signature-based techniques for malware detection cannot keep up with the pace of new attacks and variants. New attacks and sophisticated malware have been able to bypass network and end-point detection to deliver cyber-attacks at alarming rates. The enormous scale of the latest ransomware attacks continues to remind us how difficult it is to protect networks from being infiltrated. Deep learning can be leveraged to learn the new defense mechanisms using all available data and address the growing cybersecurity problem.

This Research Topic focuses on recent advances in research and development in securing the IoT landscape using deep learning. The objective of this collection is to bring together researchers from both deep learning and cybersecurity domains to provide a venue to share ideas and foster knowledge on IoT security challenges and solutions.

Papers can be from any of the following areas, including but not limited to:
● Vehicular ad-hoc network, smart home, healthcare, and smart meter security
● Real-time/anti-adversarial/efficient deep learning security protocols/solutions
● Intrusion detection and prevention
● Malware detection
● Data security and privacy
● Anomaly detection in authentication, authorization, and data requests
● Adversarial machine learning and the robustness ofAI models against malicious actions
● Interpretability and explainability of deep learning models
● Privacy-preserving deep learning algorithms
● Trustworthy deep learning
● Deep graph learning
● Fog-based IoT security
● Sensor network security
● Cloud-based IoT security

Related Resources

Federated Learning in IOT Cybersecurity 2021   PeerJ Computer Science - Federated Learning for Cybersecurity in Internet of Things
CVPR 2022   Computer Vision and Pattern Recognition
JCRAI 2021-Ei Compendex & Scopus 2021   2021 International Joint Conference on Robotics and Artificial Intelligence (JCRAI 2021)
CFDSP 2022   2022 International Conference on Frontiers of Digital Signal Processing (CFDSP 2022)
ICADCML 2022   3rd International Conference on Advances in Distributed Computing and Machine Learning - 2022
AISTATS 2022   25th International Conference on Artificial Intelligence and Statistics
blockchain_ml_iot 2021   Network and Electronics (MDPI) Joint Special Issue - Blockchain and Machine Learning for IoT: Security and Privacy Challenges
FAIML 2022   2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2022)
IoTBDS 2022   7th International Conference on Internet of Things, Big Data and Security
ICCSEA 2021   11th International Conference on Computer Science, Engineering and Applications