Towards the Low False Alarms and High Detection Rate in Intrusions Detection System

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor’s regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

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

Handbook of Research on Network Forensics and Analysis Techniques - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-4100-4.ch019 ◽

2018 ◽

pp. 351-371 ◽

Cited By ~ 1

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.

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A Approach to Change Detection for HR Image

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.971-973.1449 ◽

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.

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346 HIGH DETECTION RATE OF INTRAPROSTATIC TRICHOMONADS CORELATES WITH IMUNE RESPONSE IN OBSTRUCTIVE BENIGN PROSTATIC HYPERPLASIA

European Urology Supplements ◽

10.1016/s1569-9056(09)60349-3 ◽

2009 ◽

Vol 8 (4) ◽

pp. 207

Author(s):

D. Mitteregger ◽

W. Aberle ◽

M. Makristathis ◽

J. Walochnik ◽

W. Brozek ◽

...

Keyword(s):

Benign Prostatic Hyperplasia ◽

Detection Rate ◽

Prostatic Hyperplasia ◽

High Detection Rate ◽

High Detection

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

Stroke ◽

10.1161/strokeaha.119.026354 ◽

2020 ◽

Vol 51 (1) ◽

pp. 262-267 ◽

Cited By ~ 1

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

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THE DOUBLE PULSAR SYSTEM J0737–3039

International Journal of Modern Physics A ◽

10.1142/s0217751x05030788 ◽

2005 ◽

Vol 20 (29) ◽

pp. 7035-7044 ◽

Cited By ~ 1

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.

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