A review of machine learning applications in IoT-integrated modern power systems
M Farhoumandi, Q Zhou, M Shahidehpour - The Electricity Journal, 2021 - Elsevier
A review of machine learning applications in IoT-integrated modern power systems -
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Intrusion detection systems in RPL-based 6LoWPAN: A systematic literature review
Drastic reduction in the manufacturing cost of sensors and actuators has resulted in
considerable growth in the number of smart objects. The so-called Internet of Things (IoT) …
considerable growth in the number of smart objects. The so-called Internet of Things (IoT) …
A survey on deep learning for challenged networks: Applications and trends
Computer networks are dealing with growing complexity, given the ever-increasing volume
of data produced by all sorts of network nodes. Performance improvements are a non-stop …
of data produced by all sorts of network nodes. Performance improvements are a non-stop …
Intelligent radio signal processing: A survey
Intelligent signal processing for wireless communications is a vital task in modern wireless
systems, but it faces new challenges because of network heterogeneity, diverse service …
systems, but it faces new challenges because of network heterogeneity, diverse service …
Machine learning for smart environments in B5G networks: Connectivity and QoS
SH Alsamhi, FA Almalki, H Al-Dois… - Computational …, 2021 - Wiley Online Library
The number of Internet of Things (IoT) devices to be connected via the Internet is
overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and …
overgrowing. The heterogeneity and complexity of the IoT in terms of dynamism and …
CPS attacks mitigation approaches on power electronic systems with security challenges for smart grid applications: A review
This paper presents an inclusive review of the cyber-physical (CP) attacks, vulnerabilities,
mitigation approaches on the power electronics and the security challenges for the smart …
mitigation approaches on the power electronics and the security challenges for the smart …
Deep learning anomaly detection for cellular IoT with applications in smart logistics
The number of connected Internet of Things (IoT) devices within cyber-physical infrastructure
systems grows at an increasing rate. This poses significant device management and security …
systems grows at an increasing rate. This poses significant device management and security …
[HTML][HTML] Classifier performance evaluation for lightweight IDS using fog computing in IoT security
In this article, a Host-Based Intrusion Detection System (HIDS) using a Modified Vector
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …
Darknet traffic classification using machine learning techniques
LA Iliadis, T Kaifas - … conference on modern circuits and systems …, 2021 - ieeexplore.ieee.org
A Darknet is an overlay network within the Internet, and packets' traffic originating from it is
usually termed as suspicious. In this paper common machine learning classification …
usually termed as suspicious. In this paper common machine learning classification …
Semantic query-featured ensemble learning model for SQL-injection attack detection in IoT-ecosystems
M Gowtham, HB Pramod - IEEE Transactions on Reliability, 2021 - ieeexplore.ieee.org
Structured query language (SQL) has emerged as one of the most used databases, serving
an array of Internet-of-Things (IoTs)-enabled services including web-transactions, grid …
an array of Internet-of-Things (IoTs)-enabled services including web-transactions, grid …