Water is a significant resource in day-to-day life, and it usually requires technological association for comprehensive management. Smart Water Grids (SWG) typically use cyberphysical systems (CPS) to monitor several ...
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Side-channel attacks exploit the physical leakages from hardware components, such as power consumption, to break secure cryptographic algorithms and retrieve their secret key. Evaluating implementations of cryptograph...
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In this paper, we consider an industrial internet of things (IIoT) network operating under a carrier sense multiple access with collision avoidance (CSMA/CA) protocol. Latency-sensitive packets generated at multiple s...
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This study raises a novel data security solution that focuses on dynamic authentication of e-documents transmitted in wireless domain. This is mainly achieved by concealing multiple signatures dynamically in circular ...
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Public clouds favor sharing of storage resources,in which many tenants acquire bandwidth and storage capacity from a shared storage *** provide high availability,data are often encoded to provide fault tolerance with ...
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Public clouds favor sharing of storage resources,in which many tenants acquire bandwidth and storage capacity from a shared storage *** provide high availability,data are often encoded to provide fault tolerance with low storage *** this,efficiently organizing an encoded storage system for shared I/Os is critical for application *** is usually hard to achieve as different applications have different stripe configurations and fault tolerance *** this paper,we first study the block trace from the Alibaba cloud,and find that I/O patterns of modern applications prefer the resource sharing *** on this,we propose a globally shared resource paradigm for encoded storage system in the public *** globally shared resource paradigm can provide balanced load and fault tolerance for numerous disk pool sizes and arbitrary application stripe ***,we demonstrate with two case studies that our theory can help address the device-specific problems of HDD and SSD RAID arrays with slight modifications:comparing the existing resource partition and resource sharing methods,our theory can promote the rebuild speed of the HDD RAID arrays by 2.5,and reduce the P99 tail latency of the SSD arrays by up to two orders of magnitude.
Image enhancement refers to the process of manipulating an image to improve the visual information it contains. Images can degrade due to various factors, such as operator incompetence or low-quality picture- recordin...
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This study investigates the interruption identification problem for organization safe havens;the main goal is to classify network behavior as normal or abnormal while minimizing misclassification. In this investigatio...
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Some reconstruction-based anomaly detection models in multivariate time series have brought impressive performance advancements but suffer from weak generalization ability and a lack of anomaly *** limitations can res...
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Some reconstruction-based anomaly detection models in multivariate time series have brought impressive performance advancements but suffer from weak generalization ability and a lack of anomaly *** limitations can result in the misjudgment of models,leading to a degradation in overall detection *** paper proposes a novel transformer-like anomaly detection model adopting a contrastive learning module and a memory block(CLME)to overcome the above *** contrastive learning module tailored for time series data can learn the contextual relationships to generate temporal fine-grained *** memory block can record normal patterns of these representations through the utilization of attention-based addressing and reintegration *** two modules together effectively alleviate the problem of ***,this paper introduces a fusion anomaly detection strategy that comprehensively takes into account the residual and feature *** a strategy can enlarge the discrepancies between normal and abnormal data,which is more conducive to anomaly *** proposed CLME model not only efficiently enhances the generalization performance but also improves the ability of anomaly *** validate the efficacy of the proposed approach,extensive experiments are conducted on well-established benchmark datasets,including SWaT,PSM,WADI,and *** results demonstrate outstanding performance,with F1 scores of 90.58%,94.83%,91.58%,and 91.75%,*** findings affirm the superiority of the CLME model over existing stateof-the-art anomaly detection methodologies in terms of its ability to detect anomalies within complex datasets accurately.
Wireless Sensor Network (WSN) is a wireless self-organizing network based on sensor nodes. Small batteries or power supply with weak computing power are usually used, so how to effectively control the energy consumpti...
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Proper categorization of medicinal and non-medicinal herbs is essential for further application in healthcare and the herbal industries. In our work, we proposed MediClass-RF, the Random Forest-based optimized framewo...
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