Search results for "SJ"
showing 10 items of 2539 documents
In the Direction of Service Guarantees for Virtualized Network Functions
2022
The trend of consolidating network functions from specialized hardware to software running on virtualization servers brings significant advantages for reducing costs and simplifying service deployment. However, virtualization techniques have significant limitations when it comes to networking as there is no support for guaranteeing that network functions meet their service requirements. In this paper, we present a design for providing service guarantees to virtualized network functions based on rate control. The design is a combination of rate regulation through token bucket filters and the regular scheduling mechanisms in operating systems. It has the attractive property that traffic profi…
Face Mask Detection Using Deep Convolutional Neural Network and MobileNetV2-Based Transfer Learning
2022
The rapid spreading of Coronavirus disease 2019 (COVID-19) is a major health risk that the whole world is facing for the last two years. One of the main causes of the fast spreading of this virus is the direct contact of people with each other. There are many precautionary measures to reduce the spread of this virus; however, the major one is wearing face masks in public places. Detection of face masks in public places is a real challenge that needs to be addressed to reduce the risk of spreading the virus. To address these challenges, an automated system for face mask detection using deep learning (DL) algorithms has been proposed to control the spreading of this infectious disease effecti…
A Deep Learning-Based Framework for Feature Extraction and Classification of Intrusion Detection in Networks
2022
An intrusion detection system, often known as an IDS, is extremely important for preventing attacks on a network, violating network policies, and gaining unauthorized access to a network. The effectiveness of IDS is highly dependent on data preprocessing techniques and classification models used to enhance accuracy and reduce model training and testing time. For the purpose of anomaly identification, researchers have developed several machine learning and deep learning-based algorithms; nonetheless, accurate anomaly detection with low test and train times remains a challenge. Using a hybrid feature selection approach and a deep neural network- (DNN-) based classifier, the authors of this re…
An Efficient Online/Offline Signcryption Scheme for Internet of Things in Smart Home
2022
The delivery of unified intelligent services is accomplished through a networked environment comprised of a wide array of electronic devices. Through the use of Internet of Things (IoT) technology, smart homes collect data from their surroundings and use it to improve their tenants’ lives. Remote control, real-time monitoring, and a fire alarm are all characteristics of smart home security. Since smart homes hold personally identifying information about their residents, security is critical to ensure their reliability and prevent data breaches. In this paper, a certificateless online/offline signcryption (COOS) technique for IoT-enabled smart homes is proposed. The proposed solution takes a…
Post-Quantum Secure Identity-Based Encryption Scheme using Random Integer Lattices for IoT-enabled AI Applications
2022
Identity-based encryption is an important cryptographic system that is employed to ensure confidentiality of a message in communication. This article presents a provably secure identity based encryption based on post quantum security assumption. The security of the proposed encryption is based on the hard problem, namely Learning with Errors on integer lattices. This construction is anonymous and produces pseudo random ciphers. Both public-key size and ciphertext-size have been reduced in the proposed encryption as compared to those for other relevant schemes without compromising the security. Next, we incorporate the constructed identity based encryption (IBE) for Internet of Things (IoT) …
Internet of Things-Based Fire Alarm Navigation System: A Fire-Rescue Department Perspective
2022
In the past few years, fire alarm systems have become increasingly sophisticated and more capable and reliable. The two main objectives are the protection of life and property. As a result of state and local codes, fire protection has become more concerned with life safety over the past two decades. Several safety measures have been implemented to address the problems caused by the fires and reduce the number of fatalities and property damage. Our project is to develop and review a fire alarm navigation system and application that uses the internet of things. Fire alarm systems are designed to warn people about fires in advance so that they can evacuate the fire-affected area and take immed…
A New Correlation Coefficient for T-Spherical Fuzzy Sets and Its Application in Multicriteria Decision-Making and Pattern Recognition
2022
The goal of this paper is to design a new correlation coefficient for T -spherical fuzzy sets (TSFSs), which can accurately measure the nature of correlation (i.e., positive and negative) as well as the degree of relationship between TSFS. In order to formulate our proposed idea, we had taken inspiration from the statistical concept of the correlation coefficient. While doing so, we firstly introduce the variance and covariance of two TSFS and then constructed our scheme using these two newly defined notions. The numerical value of our proposed correlation coefficient lies within the interval − 1 , + 1 , as it should be from a statistical point of view, whereas the existing methods cannot m…
A Machine Learning in Binary and Multiclassification Results on Imbalanced Heart Disease Data Stream
2022
In medical filed, predicting the occurrence of heart diseases is a significant piece of work. Millions of healthcare-related complexities that have remained unsolved up until now can be greatly simplified with the help of machine learning. The proposed study is concerned with the cardiac disease diagnosis decision support system. An OpenML repository data stream with 1 million instances of heart disease and 14 features is used for this study. After applying to preprocess and feature engineering techniques, machine learning approaches like random forest, decision trees, gradient boosted trees, linear support vector classifier, logistic regression, one-vs-rest, and multilayer perceptron are u…
Efficient and Secure Key Management and Authentication Scheme for WBSNs Using CP-ABE and Consortium Blockchain
2022
Wireless body sensor networks (WBSNs) pose significant security and privacy risks. The Medical Server (MS) will only allow legitimate stakeholders access to confidential patient medical records when successful mutual authentication between all registered users and the MS has been confirmed using preset secret attributes. This paper proposes a novel approach to overcome the security and privacy problems in WBSNs by using CP-ABE and a consortium blockchain for key management and authentication. In this paper, a fixed-size session key is computed by utilizing several attribute base rules and AND/OR logic gate combinations. IEEE 802.15.6 is also used to transmit the encoded patient data from th…
A Machine Learning-Based Intelligence Approach for Multiple-Input/Multiple-Output Routing in Wireless Sensor Networks
2022
Computational intelligence methods play an important role for supporting smart networks operations, optimization, and management. In wireless sensor networks (WSNs), increasing the number of nodes has a need for transferring large volume of data to remote nodes without any loss. These large amounts of data transmission might lead to exceeding the capacity of WSNs, which results in congestion, latency, and packet loss. Congestion in WSNs not only results in information loss but also burns a significant amount of energy. To tackle this issue, a practical computational intelligence approach for optimizing data transmission while decreasing latency is necessary. In this article, a Softmax-Regre…