Accurate and Real‐Time Detection Method for the Exothermic Behavior of Enzymatic Nano‐Microregions Using Temperature‐Sensitive Amino‐AgInS 2 Quantum Dots

Cache side channel attacks extract secret information by monitoring the cache behavior of a victim. Normally, this attack targets an L3 cache, which is shared between a spy and a victim. Hence, a spy can obtain secret information without alerting the victim. To resist this attack, many detection techniques have been proposed. However, these approaches have limitations as they do not operate in real time. This article proposes a real-time detection method against cache side channel attacks. The proposed technique performs the detection of cache side channel attacks immediately after observing a variation of the CPU counters. For this, Intel PCM (Performance Counter Monitor) and machine learning algorithms are used to measure the value of the CPU counters. Throughout the experiment, several PCM counters recorded changes during the attack. From these observations, a detecting program was implemented by using these counters. The experimental results show that the proposed detection technique displays good performance for real-time detection in various environments.

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A real-time detection method of abnormal building energy consumption data coupled POD-LSE and FCD

Procedia Engineering ◽

10.1016/j.proeng.2017.10.334 ◽

2017 ◽

Vol 205 ◽

pp. 1657-1664 ◽

Cited By ~ 4

Author(s):

Zhongjiao Ma ◽

Jialin Song ◽

Jili Zhang

Keyword(s):

Energy Consumption ◽

Real Time ◽

Detection Method ◽

Building Energy ◽

Building Energy Consumption ◽

Consumption Data ◽

Real Time Detection

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DEVELOPMENT OF AN EVANESCENT FIELD SYSTEM FOR REAL-TIME DETECTION OF DNA HYBRIDIZATION

International Journal of Nanoscience ◽

10.1142/s0219581x02000851 ◽

2002 ◽

Vol 01 (05n06) ◽

pp. 663-666

Author(s):

DO-KYUN KIM ◽

YOUNG-SOO KWON ◽

EIICHI TAMIYA

Keyword(s):

Real Time ◽

Dna Hybridization ◽

Detection Method ◽

Evanescent Field ◽

Surface Excitation ◽

Oligonucleotide Hybridization ◽

Real Time Detection ◽

Field Excitation ◽

Hybridization Reaction

In this research, we report the characterization of the probe and target oligonucleotide hybridization reaction using the evanescent field microscopy. For detection of DNA hybridization assay, a high-density array of sensor probes were prepared by randomly distributing a mixture of particles immobilized with oligonucleotides for DNA chip applications. With the evanescent field excitation and real-time detection method, we suggest that a very sharp discrimination of bulk fluorescence against surface excitation in combination with high excitation intensities can be achieved.

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A Real-Time Detection Method for Abnormal Data of Internet of Things Sensors Based on Mobile Edge Computing

Mathematical Problems in Engineering ◽

10.1155/2021/6655346 ◽

2021 ◽

Vol 2021 ◽

pp. 1-7

Author(s):

Xuguang Liu

Keyword(s):

Time Series ◽

Anomaly Detection ◽

Data Processing ◽

Real Time ◽

Detection Method ◽

Edge Computing ◽

Sensor Data ◽

Detection Accuracy ◽

Spatiotemporal Correlation ◽

Real Time Detection

Aiming at the anomaly detection problem in sensor data, traditional algorithms usually only focus on the continuity of single-source data and ignore the spatiotemporal correlation between multisource data, which reduces detection accuracy to a certain extent. Besides, due to the rapid growth of sensor data, centralized cloud computing platforms cannot meet the real-time detection needs of large-scale abnormal data. In order to solve this problem, a real-time detection method for abnormal data of IoT sensors based on edge computing is proposed. Firstly, sensor data is represented as time series; K-nearest neighbor (KNN) algorithm is further used to detect outliers and isolated groups of the data stream in time series. Secondly, an improved DBSCAN (Density Based Spatial Clustering of Applications with Noise) algorithm is proposed by considering spatiotemporal correlation between multisource data. It can be set according to sample characteristics in the window and overcomes the slow convergence problem using global parameters and large samples, then makes full use of data correlation to complete anomaly detection. Moreover, this paper proposes a distributed anomaly detection model for sensor data based on edge computing. It performs data processing on computing resources close to the data source as much as possible, which improves the overall efficiency of data processing. Finally, simulation results show that the proposed method has higher computational efficiency and detection accuracy than traditional methods and has certain feasibility.

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Ultra-stable fluorescent film sensor based on quantum dots for the real-time detection of Cu2+

The Science of The Total Environment ◽

10.1016/j.scitotenv.2020.141412 ◽

2020 ◽

Vol 746 ◽

pp. 141412

Author(s):

Ting Han ◽

Hong Kang ◽

Sixia Ye ◽

Ye Yuan ◽

Yang Zhang ◽

...

Keyword(s):

Quantum Dots ◽

Real Time ◽

Film Sensor ◽

The Real ◽

Real Time Detection

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A real-time detection method of building energy efficiency based on image processing

Journal of Visual Communication and Image Representation ◽

10.1016/j.jvcir.2019.02.032 ◽

2019 ◽

Vol 60 ◽

pp. 295-304

Author(s):

Wei Cai ◽

Xiaodong Wen ◽

Saisai Wang ◽

Lijuan Wang

Keyword(s):

Image Processing ◽

Energy Efficiency ◽

Real Time ◽

Detection Method ◽

Building Energy ◽

Building Energy Efficiency ◽

Real Time Detection

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A Real-Time Method to Detect the Deformation Behavior during Laser Solid Forming of Thin-Wall Structure

Metals ◽

10.3390/met10040508 ◽

2020 ◽

Vol 10 (4) ◽

pp. 508 ◽

Cited By ~ 1

Author(s):

Hua Tan ◽

Yuguang Chen ◽

Zhe Feng ◽

Wei Hou ◽

Wei Fan ◽

...

Keyword(s):

Real Time ◽

Deformation Behavior ◽

Detection Method ◽

Dimensional Accuracy ◽

Deposition Process ◽

Wall Structure ◽

Thin Wall ◽

Time Deformation ◽

Laser Solid Forming ◽

Real Time Detection

Laser solid forming (LSF) is a promising additive manufacturing technology. In the LSF process, deformation behaviors dictate the accuracy of the produced parts. In this study, by using a laser displacement detector based on laser triangulation principle, an accurate and effective real-time detection method was established to monitor the real-time deformation behavior of the key position during the LSF of a thin-wall structure. The results confirmed that increasing thin-wall length results in increasing final deformation of the edge. The displacement fluctuation range and value in the middle of thin wall are both smaller than that of the positions near the end, while the entire displacement changing direction in the middle is opposite to that of the end positions. When the deposition process is paused, the deformation of the thin wall during the cooling stage will deviate the position of the deposited thin wall, resulting in the dislocation between the subsequent deposited part and that before the pause, which affect the dimensional accuracy of the thin wall structure. This non-contact real-time detection method also confirmed the ability to monitor the initiation of cracking during the LSF process, and a potential to be used for the on-line feedback control of deformation of detected key position of deposited structure.

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