The key objective of intrusion detection systems(IDS)is to protect the particular host or network by investigating and predicting the network traffic as an attack or *** IDS uses many methods of machine learning(ML)to...
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The key objective of intrusion detection systems(IDS)is to protect the particular host or network by investigating and predicting the network traffic as an attack or *** IDS uses many methods of machine learning(ML)to learn from pastexperience attack *** based and identify the new *** though these methods are effective,but they have to suffer from large computational costs due to considering all the traffic features,***,emerging technologies like the Internet of Things(Io T),big data,*** getting advanced day by day;as a result,network traffics are also increasing ***,the issue of computational cost needs to be addressed ***,in this research,firstly,the ML methods have been used with the feature selection technique(FST)to reduce the number of features by picking out only the important ones from NSL-KDD,CICIDS2017,and CIC-DDo S2019datasets later that helped to build IDSs with lower cost but with the higher performance which would be appropriate for vast scale *** experimental result demonstrated that the proposed model *** tree(DT)with Recursive feature elimination(RFE)performs better than other classifiers with RFE in terms of accuracy,specificity,precision,sensitivity,F1-score,and G-means on the investigated datasets.
In 2018, there were 1 million occurrences of non-melanoma cancer and 288,000 occurrences of malignant skin cancer (MM) recorded worldwide. Given the aging of the population and limited resources for medical care, a co...
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Antenna optimization using machine learning is a rapidly evolving field that leverages the power of artificial intelligence to design and improve antenna systems. Antenna optimization is a process of modifying antenna...
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Disastrous situations pose a formidable challenge, testing our resilience against nature's fury and the race against time to prevent the loss of human life. It is noted that in such situations that Microblogging p...
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With the profound use of digital contents in education and social media, multimedia content have become a prevalent means of communication and with such rapid increase, information security is still a major concern. T...
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Suicide is a significant public health issue that devastates individuals and society. Early warning systems are crucial in preventing suicide. The purpose of this research is to create a deep learning model to identif...
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In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the d...
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In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely *** verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented *** this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly *** verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.
All the software products developed will need testing to ensure the quality and accuracy of the product. It makes the life of testers much easier when they can optimize on the effort spent and predict defects for the ...
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The Quantum Internet of Things (QIoT) in the healthcare industry holds the promise of transforming patient care, diagnostics, and medical research. Quantum-enhanced sensors, communication, and computation offer unprec...
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The Quantum Internet of Things (QIoT) in the healthcare industry holds the promise of transforming patient care, diagnostics, and medical research. Quantum-enhanced sensors, communication, and computation offer unprecedented capabilities that can revolutionize how healthcare services are delivered and experienced. This paper explores the potential of QIoT in the context of smart healthcare, where interconnected quantum-enabled devices and systems create an ecosystem that enhances data security, enables real-time monitoring, and advances medical knowledge. We delve into the applications of quantum sensors in precise health monitoring, the role of quantum communication in secure telemedicine, and the computational power of quantum computing in drug discovery and personalized medicine. We discuss challenges such as technical feasibility, scalability, and regulatory considerations, along with the emerging trends and opportunities in this transformative field. By examining the intersection of quantum technologies and smart healthcare, this paper aims to shed light on the novel approaches and breakthroughs that could redefine the future of healthcare delivery and patient outcomes. IEEE
Recent advances in wireless sensor networks (WSNs) have brought the sensor based monitoring developments to the surface in many applications. In such a scenario, the security of communication is a major challenge in t...
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