The public’s health is seriously at risk from the coronavirus pandemic. Millions of people have already died as a result of this devastating illness, which affects countless people daily worldwide. Unfortunately, no ...
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Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information *** use of cloud computing has realized the rapid increase of infor...
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Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information *** use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing *** cloud is nowadays highly affected by internal threats of the *** applications such as banking,hospital,and business are more likely affected by real user *** intruder is presented as a user and set as a member of the *** becoming an insider in the network,they will try to attack or steal sensitive data during information sharing or *** major issue in today's technological development is identifying the insider threat in the cloud *** data are lost,compromising cloud users is *** and security are not ensured,and then,the usage of the cloud is not *** solutions are available for the external security of the cloud ***,insider or internal threats need to be *** this research work,we focus on a solution for identifying an insider attack using the artificial intelligence *** insider attack is possible by using nodes of weak users’*** will log in using a weak user id,connect to a network,and pretend to be a trusted ***,they can easily attack and hack information as an insider,and identifying them is very *** types of attacks need intelligent solutions.A machine learning approach is widely used for security *** date,the existing lags can classify the attackers *** information hijacking process is very absurd,which motivates young researchers to provide a solution for internal *** our proposed work,we track the attackers using a user interaction behavior pattern and deep learning *** usage of mouse movements and clicks and keystrokes of the real user is stored in a *** deep belief neural
Computed Tomography(CT)scan and Magnetic Resonance Imaging(MRI)technologies are widely used in medical *** the last few months,due to the increased use of CT scans,millions of patients have had their CT scans ***,as a...
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Computed Tomography(CT)scan and Magnetic Resonance Imaging(MRI)technologies are widely used in medical *** the last few months,due to the increased use of CT scans,millions of patients have had their CT scans ***,as a result,images showing the Corona Virus for diagnostic purposes were digitally transmitted over the *** major problem for the world health care system is a multitude of attacks that affect copyright protection and other ethical issues as images are transmitted over the *** a result,it is important to apply a robust and secure watermarking technique to these ***,watermarking schemes have been developed for various image formats,***,.bmp,***,but their impact on NIfTI(Neuroimaging Informatics Technology Initiative)images is not noteworthy.A watermarking scheme based on the Lifting Wavelet Transform(LWT)and QR factorization is presented in this *** LWT and QR are combined,the NIfTI image maintains its inherent sensitivity and mitigates the watermarking scheme’s *** watermarks are added to the host image in this *** the performance of the graphics card is done by using PSNR,SSIM,Q(a formula which measures image quality),SNR,and Normalized *** watermarking scheme withstands a variety of noise attacks and conversions,including image compression and decompression.
The utilization of the Internet of Things (IOT) has shown significant potential in various aspects of daily life, yet its application in addressing social issues remains underdeveloped. India, with a substantial numbe...
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The energy control of a Wireless Sensor Network (WSN) often leads to an unbalanced state between the battery storage system, energy extraction through photovoltaic systems energy, and energy utilization in the WSN. Th...
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The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020,provide critical research criteria to assess the vulnerabilities of our cur...
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The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020,provide critical research criteria to assess the vulnerabilities of our current health *** paper addresses our preparedness for the management of such acute health emergencies and the need to enhance awareness,about public health and healthcare *** view of this unprecedented health crisis,distributed ledger and AI technology can be seen as one of the promising alternatives for fighting against such epidemics at the early stages,and with the higher *** the implementation level,blockchain integration,early detection and avoidance of an outbreak,identity protection and safety,and a secure drug supply chain can be *** the opposite end of the continuum,artificial intelligence methods are used to detect corona effects until they become too serious,avoiding costly drug *** paper explores the application of blockchain and artificial intelligence in order to fight with COVID-19 epidemic *** paper analyzes all possible newly emerging cases that are employing these two technologies for combating a pandemic like COVID-19 along with major challenges which cover all technological and motivational *** paper has also discusses the potential challenges and whether further production is required to establish a health monitoring system.
Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions,device monitoring, and collection of information. Due to limited energ...
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Wireless Sensor Network (WSN) is an independent device that comprises a discrete collection of Sensor Nodes (SN) to sense environmental positions,device monitoring, and collection of information. Due to limited energy resourcesavailable at SN, the primary issue is to present an energy-efficient framework andconserve the energy while constructing a route path along with each sensor ***, many energy-efficient techniques focused drastically on energy harvesting and reduced energy consumption but failed to support energy-efficient routingwith minimal energy consumption in WSN. This paper presents an energy-efficientrouting system called Energy-aware Proportional Fairness Multi-user Routing(EPFMR) framework in WSN. EPFMR is deployed in the WSN environment usingthe instance time. The request time sent for the route discovery is the foremost stepdesigned in the EPFMR framework to reduce the energy consumption rate. Theproportional fairness routing in WSN selects the best route path for the packet flowbased on the relationship between the periods of requests between different *** path discovered for packet flow also measure energy on multi-user route pathusing the Greedy Instance Fair Method (GIFM). The GIFM in EPFMR developsnode dependent energy-efficient localized route path, improving the *** energy-aware framework maximizes the throughput rate and performs experimental evaluation on factors such as energy consumption rate during routing,Throughput, RST, node density and average energy per packet in WSN. The RouteSearching Time (RST) is reduced using the Boltzmann Distribution (BD), and as aresult, the energy is minimized on multi-user WSN. Finally, GIFM applies aninstance time difference-based route searching on WSN to attain an optimal energyminimization system. Experimental analysis shows that the EPFMR framework canreduce the RST by 23.47% and improve the throughput by 6.79% compared withthe state-of-the-art works.
Deep neural networks (DNNs) have emerged as the most effective programming paradigm for computer vision and natural language processing applications. With the rapid development of DNNs, efficient hardware architecture...
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Deep neural networks (DNNs) have emerged as the most effective programming paradigm for computer vision and natural language processing applications. With the rapid development of DNNs, efficient hardware architectures for deploying DNN-based applications on edge devices have been extensively studied. Emerging nonvolatile memories (NVMs), with their better scalability, nonvolatility, and good read performance, are found to be promising candidates for deploying DNNs. However, despite the promise, emerging NVMs often suffer from reliability issues, such as stuck-at faults, which decrease the chip yield/memory lifetime and severely impact the accuracy of DNNs. A stuck-at cell can be read but not reprogrammed, thus, stuck-at faults in NVMs may or may not result in errors depending on the data to be stored. By reducing the number of errors caused by stuck-at faults, the reliability of a DNN-based system can be enhanced. This article proposes CRAFT, i.e., criticality-aware fault-tolerance enhancement techniques to enhance the reliability of NVM-based DNNs in the presence of stuck-at faults. A data block remapping technique is used to reduce the impact of stuck-at faults on DNNs accuracy. Additionally, by performing bit-level criticality analysis on various DNNs, the critical-bit positions in network parameters that can significantly impact the accuracy are identified. Based on this analysis, we propose an encoding method which effectively swaps the critical bit positions with that of noncritical bits when more errors (due to stuck-at faults) are present in the critical bits. Experiments of CRAFT architecture with various DNN models indicate that the robustness of a DNN against stuck-at faults can be enhanced by up to 105 times on the CIFAR-10 dataset and up to 29 times on ImageNet dataset with only a minimal amount of storage overhead, i.e., 1.17%. Being orthogonal, CRAFT can be integrated with existing fault-tolerance schemes to further enhance the robustness of DNNs aga
Wireless Sensor Networks (WSNs) are essential for various applications, but their architecture makes them vulnerable to attacks. While traditional security methods like authentication and encryption offer some protect...
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Nowadays, the risk estimators are to be applied based on the population characteristics of their country, which is termed as race attribute. There were specific tools to determine the risk of cardiovascular disease. A...
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