The Internet of Things (IoT) is a rapidly growing technology that connects and integrates billions of smart devices, generating vast volumes of data and impacting various aspects of daily life and industrial systems. However, the inherent characteristics of IoT devices, including limited battery life, universal connectivity, resource-constrained design, and mobility, make them highly vulnerable to cybersecurity attacks, which are increasing at an alarming rate. As a result, IoT security and privacy have gained significant research attention, with a particular focus on (...) developing anomaly detection systems. In recent years, machine learning (ML) has made remarkable progress, evolving from a lab novelty to a powerful tool in critical applications. ML has been proposed as a promising solution for addressing IoT security and privacy challenges. In this article, we conducted a study of the existing security and privacy challenges in the IoT environment. Subsequently, we present the latest ML-based models and solutions to address these challenges, summarizing them in a table that highlights the key parameters of each proposed model. Additionally, we thoroughly studied available datasets related to IoT technology. Through this article, readers will gain a detailed understanding of IoT architecture, security attacks, and countermeasures using ML techniques, utilizing available datasets. We also discuss future research directions for ML-based IoT security and privacy. Our aim is to provide valuable insights into the current state of research in this field and contribute to the advancement of IoT security and privacy. (shrink)

In this dialogue, Mileva and Albert start to talk about physics and its subject matter, the physical. They end up in a situation that permits causal dependence between separate ontological domains. In this possible world, they continue talking. First, they Socratically agree that the physical is physical and only physical. Then, they call the physical an ontologically homogeneous domain. They then generalise the principle that the physical is causally unaffected by anything non-physical, into the principle that ontologically homogeneous domains do (...) not cause ontologically homogeneous domains. From a modern point of view talking about black hole singularities, they continue discussing the Chandrasekhar limit and the collapse of the physical laws as we know them. Mileva carries a burden and Albert stands up and carries it with her. The burden is an implication of the generalised principle. Relying on parsimony, only ontologically homogeneous domains are forbidden to cause ontologically homogeneous domains. This leaves the door open for ontologically heterogeneous domains to cause ontologically homogeneous domains. Also relying on parsimony, only ontologically homogeneous domains are forbidden to be caused by ontologically homogeneous domains and this allows ontologically heterogeneous domains to be caused by ontologically homogeneous domains. Ontologically heterogeneous domains, thus, are allowed to causally link ontologically homogeneous domains. Albert realises that the mathematical could qualify as an ontologically homogeneous domain and that the theoretical difficulties that are foreseen beyond the Chandrasekhar limit could be addressed by expanding physics into a context that contains also an ontologically heterogeneous domain. The theoretical difficulties beyond the Chandrasekhar limit would be due to an emergent mathematical-physical domain. Mileva concludes that Albert’s theory is not faulty but regional. A global theory would have to include the explanation of the mathematical-physical. (shrink)

Black holes are one of the fascinating objects in the universe with gravitational pull strong enough to capture light within them. Through this article we have attempted to provide an insight to the black holes, on their formation and theoretical developments that made them one of the unsolved mysteries of universe.