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Guest Editorial: Special Issue on AI-Enabled Internet of Dependable and Controllable Things

Wei Yu, Wei Zhao, Anke Schmeink, Houbing Song, Guido Dartmann
2021 IEEE Internet of Things Journal  
The article titled "Toward secure and efficient deep learning inference in dependable IoT systems" proposes a new approach called SUPER-IoT to enhance the security and efficiency of AI applications in  ...  This study raises a valuable alarm for security in federated learning IoT systems.  ... 
doi:10.1109/jiot.2021.3053713 fatcat:wnsgkuohhvg4fitk6ixreddsly

An overview of next-generation architectures for machine learning: Roadmap, opportunities and challenges in the IoT era

Muhammad Shafique, Theocharis Theocharides, Christos-Savvas Bouganis, Muhammad Abdullah Hanif, Faiq Khalid, Rehan Hafiz, Semeen Rehman
2018 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE)  
This paper provides an overview of the current and emerging trends in designing highly efficient, reliable, secure and scalable machine learning architectures for such devices.  ...  Machine learning, and in particular deep learning, is the de facto processing paradigm for intelligently processing these immense volumes of data.  ...  FUTURE DIRECTIONS AND ROADMAP OF DEEP LEARNING FOR IOTS A.  ... 
doi:10.23919/date.2018.8342120 dblp:conf/date/0001TBHKHR18 fatcat:jb6ouvhtrrevlj3dehuyj6inaq

Table of Contents

2020 2020 IEEE 45th Conference on Local Computer Networks (LCN)  
Wireless Networks 325 IQoR: An Intelligent QoS-Aware Routing Mechanism with Deep Reinforcement Learning 329 Secure and Reliable Data Transmission in SDN-Based Backend Networks of Industrial IoT Detecting  ...  Web Security Studies 409 An Efficient Reputation Management Model Based on Game Theory for Vehicular Networks 413 LFQ: Online Learning of per-Flow Queuing Policies Using Deep Reinforcement Learning  ... 
doi:10.1109/lcn48667.2020.9314824 fatcat:ijv6a3vurbd2zjmdmkt7bxle4q

2020 Index IEEE Internet of Things Journal Vol. 7

2020 IEEE Internet of Things Journal  
., and Bose, R., Rateless-Code-Based Secure Cooperative Transmission Scheme for Industrial IoT; JIoT July 2020 6550-6565 Jamalipour, A., see Murali, S., JIoT Jan. 2020 379-388 James, L.A., see Wanasinghe  ...  ., +, JIoT July 2020 6035-6045 Toward Secure and Privacy-Preserving Distributed Deep Learning in Fog-Cloud Computing.  ...  ., +, JIoT Jan. 2020 99-115 Joint DNN Partition Deployment and Resource Allocation for Delay-Sensitive Deep Learning Inference in IoT.  ... 
doi:10.1109/jiot.2020.3046055 fatcat:wpyblbhkrbcyxpnajhiz5pj74a

Deep Learning-Based Security Behaviour Analysis in IoT Environments: A Survey

Yawei Yue, Shancang Li, Phil Legg, Fuzhong Li, Honghao Gao
2021 Security and Communication Networks  
Second, from the security perspective of IoT systems, we analyse the suitability of deep learning to improve security. Finally, we evaluate the performance of deep learning in IoT system security.  ...  First, from the view of system architecture and the methodologies used, we investigate applications of deep learning in IoT security.  ...  Memory efficiency and time efficiency would be two core concerns in implementing deep learning in real IoT systems.  ... 
doi:10.1155/2021/8873195 fatcat:oh4dcicpsfdcvmkfn5z2lgr2lm

Machine Learning Systems for Intelligent Services in the IoT: A Survey [article]

Wiebke Toussaint, Aaron Yi Ding
2020 arXiv   pre-print
Machine learning (ML) technologies are emerging in the Internet of Things (IoT) to provision intelligent services.  ...  With a multi-layered framework to classify and illuminate system design choices, this survey exposes fundamental concerns of developing and deploying ML systems in the rising cloud-edge-device continuum  ...  With the shift towards using deep learning on mobile [80] and embedded devices [137] , efficient inference is becoming an important challenge to address due to on-device energy and computing power constraints  ... 
arXiv:2006.04950v3 fatcat:xrjcioqkrrhpvgmwmutiajgfbe

Application of Deep Learning for Quality of Service Enhancement in Internet of Things: A Review

Nasser Kimbugwe, Tingrui Pei, Moses Ntanda Kyebambe
2021 Energies  
Therefore, this paper aims at finding out how Deep Learning has been applied to enhance QoS in IoT by preventing security and privacy breaches of the IoT-based systems and ensuring the proper and efficient  ...  Deep Learning for QoS in IoT.  ...  From these literature reviews, we note that QoS in IoT is mainly compromised when: (1) The security and privacy of IoT-based systems are breached, and (2) When IoT resources are not properly and efficiently  ... 
doi:10.3390/en14196384 fatcat:y6i4vh7fzzahbpa2avfi7em5rm

Guest Editors' Introduction to the Joint Special Section on Secure and Emerging Collaborative Computing and Intelligent Systems

Yuan Hong, Valerie Issarny, Surya Nepal, Mudhakar Srivatsa
2021 IEEE Transactions on Emerging Topics in Computing  
The Internet coupled with recent advances in computing and information technologies, such as IoT, mobile edge/cloud computing, cyber-physical-social systems, and artificial intelligence/machine learning  ...  /deep learning, have paved the way for creating next-generation smart and intelligent systems and applications that can have transformative impact in our society while accelerating rapid scientific discoveries  ...  In this joint special section, two papers in deep learning and security have been accepted to TETC.  ... 
doi:10.1109/tetc.2021.3076338 fatcat:zajlttxulzbi3n7gzkkpra5z6e

Federated Deep Learning for Cyber Security in the Internet of Things: Concepts, Applications, and Experimental Analysis

Mohamed Amine Ferrag, Othmane Friha, Leandros Maglaras, Helge Janicke, Lei Shu
2021 IEEE Access  
in federated learning-based security and privacy systems.  ...  [148] Edge- based AI security + Determine the efficiency of federated learning-based IoT intrusion detection systems.  ...  His research interests include wireless network security, network coding security, and applied cryptography.  ... 
doi:10.1109/access.2021.3118642 fatcat:222fgsvt3nh6zcgm5qt4kxe7c4

2021 Index IEEE Internet of Things Journal Vol. 8

2021 IEEE Internet of Things Journal  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Note that the item title is found only under the primary entry in the Author Index.  ...  ., +, JIoT June 15, 2021 9531-9538 Toward Secure and Efficient Deep Learning Inference in Dependable IoT Systems.  ... 
doi:10.1109/jiot.2022.3141840 fatcat:42a2qzt4jnbwxihxp6rzosha3y

Adversarial Machine Learning based Partial-model Attack in IoT [article]

Zhengping Luo, Shangqing Zhao, Zhuo Lu, Yalin E. Sagduyu, Jie Xu
2020 arXiv   pre-print
Because machine learning has been applied in many IoT systems, the security implications of machine learning need to be studied following an adversarial machine learning approach.  ...  These results show that the machine learning engine of IoT system is highly vulnerable to attacks even when the adversary manipulates a small portion of IoT devices, and the outcome of these attacks severely  ...  Acknowledgement: The work at USF was supported in part by NSF CNS-1717969.  ... 
arXiv:2006.14146v2 fatcat:bw6ftipcdjdbpdqacq2bdofn54

RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems

Emna Baccour, Aiman Erbad, Amr Mohamed, Mounir Hamdi, Mohsen Guizani
2021 IEEE Access  
In our work, we opt for per-layer distribution in order to design a system with a reduced number of participants and a lower dependency between them, while guaranteeing the pervasive deep learning and  ...  CONCLUSION In this paper, we re-thought the execution of deep learning inference, requiring high memory and computation demands, in order to fit it to the limited-resources characterizing the IoT units  ...  He has over 25 years of experience in wireless networking research and industrial systems development.  ... 
doi:10.1109/access.2021.3070627 fatcat:ypqpga35nfha7inu7ns37majyq

Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges [article]

Latif U. Khan, Walid Saad, Zhu Han, Ekram Hossain, Choong Seon Hong
2021 arXiv   pre-print
In this paper, first, we present the recent advances of federated learning towards enabling federated learning-powered IoT applications.  ...  However, given the presence of massively distributed and private datasets, it is challenging to use classical centralized learning algorithms in the IoT.  ...  Wang et al., [31] Accelerating AI tasks by edge communication and computing systems, efficiency of In-Edge AI for real-time mobile communication system toward 5G, incentive and business model of In-Edge  ... 
arXiv:2009.13012v2 fatcat:4oqifqi5czfyxiqe7gjewmuzsq

Securing IoT Environment using Machine Learning Techniques

2020 International Journal of Engineering and Advanced Technology  
Machine learning approach could be very effective to address security challenges in IoT environment.  ...  In recent related papers, the researcher have used machine learning techniques, approaches or methods for securing things in IoT environment.  ...  We infers, blue star is belong to red circles class. The efficiency of this algorithm is depend upon value of K.  ... 
doi:10.35940/ijeat.c5339.029320 fatcat:qairowwpsrboxaz3tytelcjs5i

Deep Learning Approaches for Intrusion Detection

Azar Abid Salih, Siddeeq Y. Ameen, Subhi R. M. Zeebaree, Mohammed A. M. Sadeeq, Shakir Fattah Kak, Naaman Omar, Ibrahim Mahmood Ibrahim, Hajar Maseeh Yasin, Zryan Najat Rashid, Zainab Salih Ageed
2021 Asian Journal of Research in Computer Science  
This paper investigates and presents Deep Learning (DL) techniques for improving the Intrusion Detection System (IDS).  ...  Intrusion detection is one of the leading research problems in network and computer security.  ...  The comparison among different deep learning techniques is conducted to show the efficiency of deep learning in intrusion detection.  ... 
doi:10.9734/ajrcos/2021/v9i430229 fatcat:phpioi3zinck7o7izh6nqbdwz4
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