scholarly journals Detection of Attacks in Pervasive Computing Using Gated Recurrent Unit Based on Bidirectional Weighted Feature Averaging

2021 ◽  
Author(s):  
P. Rajasekaran ◽  
V Magudeeswaran
Keyword(s):  
Pervasive Computing ◽  
Detection Rate ◽  
Performance Metrics ◽  
Personal Data ◽  
Cyber Attacks ◽  
High Detection Rate ◽  
The Social ◽  
High Detection ◽  
Different Types ◽  
Gated Recurrent Unit

Abstract In the era of information technology, the new types of cyber-attacks affect the performance of the network, which is very risky and cannot be restored quickly. In pervasive computing, there are more chances for such types of attacks since the personal data of the user is closely connected to the social environment. The research is performed using SNMP-MIB dataset, and feature selection are made by using the Enhanced Salp Swarm Optimization to select the optimal features to identify the attacks by using wrapper techniques. Then, various types of attacks are appropriately distinguished with proposed classifier Gated Recurrent Unit Neural Network based on Bidirectional Weighted Feature Averaging for high detection rate and accuracy. The value of performance metrics obtained from the proposed method outperforms the existing methods in terms of 99.9% accuracy, 99.8% in precision and detection rate is 99% in classifying different types of attacks.

A Comparative Review of Various Machine Learning Approaches for Improving the Performance of Stego Anomaly Detection

2018 ◽  
pp. 351-371 ◽  
Author(s):  
Hemalatha Jeyaprakash ◽  
KavithaDevi M. K. ◽  
Geetha S.
Keyword(s):  
Machine Learning ◽  
Anomaly Detection ◽  
Detection Rate ◽  
High Dimensional ◽  
Learning Approaches ◽  
Learning Tools ◽  
High Detection Rate ◽  
Comparative Review ◽  
High Detection

In recent years, steganalyzers are intelligently detecting the stego images with high detection rate using high dimensional cover representation. And so the steganographers are working towards this issue to protect the cover element dependency and to protect the detection of hiding secret messages. Any steganalysis algorithm may achieve its success in two ways: 1) extracting the most sensitive features to expose the footprints of message hiding; 2) designing or building an effective classifier engine to favorably detect the stego images through learning all the stego sensitive features. In this chapter, the authors improve the stego anomaly detection using the second approach. This chapter presents a comparative review of application of the machine learning tools for steganalysis problem and recommends the best classifier that produces a superior detection rate.

A Approach to Change Detection for HR Image

2014 ◽  
Vol 971-973 ◽  
pp. 1449-1453
Author(s):  
Zuo Wei Huang ◽  
Shu Guang Wu ◽  
Tao Xin Zhang
Keyword(s):  
Change Detection ◽  
Detection Rate ◽  
False Detection Rate ◽  
False Detection ◽  
High Detection Rate ◽  
High Detection ◽  
Self Adaptation ◽  
Ica Algorithm ◽  
Different Characteristics ◽  
Better Than

Hyperspectral remote sensing is the multi-dimensional information obtaining technology,which combines target detection and spectral imaging technology together, In order to accord with the condition of hyperspectral imagery，the paper developed an optimized ICA algorithm for change detection to describe the statistical distribution of the data. By processing these abundance maps, change of different classes of objects can be obtained..A approach is capable of self-adaptation, and can be applied to hyperspectral images with different characteristics. Experiment results demonstrate that the ICA-based hyperspectral change detection performs better than other traditional methods with a high detection rate and a low false detection rate.

scholarly journals Stroke Risk Analysis, a System With a High Detection Rate of Atrial Fibrillation in Stroke and Transient Ischemic Attack

Stroke ◽  
2020 ◽  
Vol 51 (1) ◽  
pp. 262-267 ◽  
Author(s):  
Meritxell Gomis ◽  
Antoni Dávalos ◽  
Francisco Purroy ◽  
Pere Cardona ◽  
Ana Rodríguez-Campello ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Risk Analysis ◽  
Transient Ischemic Attack ◽  
Detection Rate ◽  
Stroke Risk ◽  
High Detection Rate ◽  
High Detection ◽  
Ischemic Attack

THE DOUBLE PULSAR SYSTEM J0737–3039

2005 ◽  
Vol 20 (29) ◽  
pp. 7035-7044 ◽  
Author(s):  
D. R. LORIMER
Keyword(s):  
General Relativity ◽  
Neutron Star ◽  
Gravitational Wave ◽  
Detection Rate ◽  
Order Effects ◽  
Gravitational Wave Detector ◽  
High Detection Rate ◽  
Wave Detector ◽  
High Detection ◽  
Order Of Magnitude

The double pulsar system J0737 – 3039 – a 22.7 ms pulsar in a compact 2.4 hr orbit about a 2.7 s pulsar was one of the long-awaited "holy grails" of pulsar astronomy. After only two years of timing, the system is close to surpassing the original Hulse-Taylor binary as a test of general relativity. On-going timing should soon reveal second-order effects in the post-Newtonian parameters. In addition, the observed interactions of the radio beams of the two pulsars provide a unique laboratory for probing neutron star magnetospheres and relativistic winds. Finally, a revised estimate of the cosmic rate of double neutron star mergers including J0737 – 3039 boosts previous estimates by an order of magnitude and suggests a high detection rate for the advanced LIGO gravitational wave detector.

High detection rate of clinically relevant genomic abnormalities in plasma cells enriched from patients with multiple myeloma

2012 ◽  
Vol 51 (11) ◽  
pp. 997-1006 ◽  
Author(s):  
Marian Stevens-Kroef ◽  
Daniel Olde Weghuis ◽  
Sandra Croockewit ◽  
Leo Derksen ◽  
Jeroen Hooijer ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Detection Rate ◽  
Plasma Cells ◽  
High Detection Rate ◽  
High Detection
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