Decision Analysis of Statistically Detecting Distributed Denial-of-Service Flooding Attacks

2003 ◽  
Vol 02 (03) ◽  
pp. 397-405 ◽  
Author(s):  
Ming Li ◽  
Chi-Hung Chi ◽  
Weijia Jia ◽  
Wei Zhao ◽  
Wanlei Zhou ◽  
...  
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Denial Of Service ◽  
False Alarm Probability ◽  
Statistical Decision ◽  
Flooding Attacks ◽  
Decision Region ◽  
High Detection ◽  
Statistical Decision Making

There are two statistical decision making questions regarding statistically detecting sings of denial-of-service flooding attacks. One is how to represent the distributions of detection probability, false alarm probability and miss probability. The other is how to quantitatively express a decision region within which one may make a decision that has high detection probability, low false alarm probability and low miss probability. This paper gives the answers to the above questions. In addition, a case study is demonstrated.

A 3D Model Watermarking Algorithm

2013 ◽  
Vol 798-799 ◽  
pp. 708-711
Author(s):  
Xiu Hu Tan
Keyword(s):  
Detection Probability ◽  
3D Model ◽  
False Alarm Probability ◽  
3D Models ◽  
Model Potential ◽  
Least Mean Square ◽  
New Approach ◽  
Geometry Model ◽  
3D Geometry ◽  
High Detection

The popularity of 3D content is on the rise since it provides an immersive experience to viewers. In this paper, we present a new approach to watermarking 3D models based on optimization statistics. Through choosing the vertexes, we are able to obtain to the embedded watermark that has the least modified to topology transform of the 3D geometry model, and then project the watermark to the space that has the least mean square error value. So, we obtain that the robustness of the approach lies in hiding a watermark in the space that is least susceptible to the 3D model potential modification. Through analysis and constraint the conditions, we can obtain a high detection probability, a low false alarm probability. The robustness of our method is demonstrated by various attacks through computer simulation.

scholarly journals A Novel Sensing Strategy Based on Energy Detector for Spectrum Sensing

2019 ◽  
Vol 9 (21) ◽  
pp. 4634 ◽  
Author(s):  
Hai Huang ◽  
Jia Zhu ◽  
Junsheng Mu
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Energy Detector ◽  
Accuracy Improvement ◽  
Classical Scheme ◽  
Sensing Performance

Sensing strategy directly influences the sensing accuracy of a spectrum sensing scheme. As a result, the optimization of a sensing strategy appears to be of great significance for accuracy improvement in spectrum sensing. Motivated by this, a novel sensing strategy is proposed in this paper, where an improved tradeoff among detection probability, false-alarm probability and available throughput is obtained based on the energy detector. We provide the optimal sensing performance and exhibit its superiority in theory compared with the classical scheme. Finally, simulations validate the conclusions drawn in this paper.

Multi-Sensor N-P Criterion Fusion Detection Based on Weighting by SNR

2014 ◽  
Vol 1044-1045 ◽  
pp. 818-824
Author(s):  
Bo Fan Yang ◽  
Rui Wang ◽  
Gang Wang ◽  
Li Zhao
Keyword(s):  
Signal Detection ◽  
False Alarm ◽  
Sensor Fusion ◽  
Detection Probability ◽  
Detection System ◽  
False Alarm Probability ◽  
Radar Target ◽  
Low Snr ◽  
Simulation Results ◽  
Fusion Detection

Aiming at signal detection of radar target, concerning about on the basis of the influence of SNR on detection probability when false alarm probability is given based on N-P criterion, a kind of multi-sensor fusion detection based on SNR is put forward. It can improve system’s detection probability under the condition of required false alarm probability in the detection of low SNR signal. The simulation results show that the detection performance is significantly increased, no matter fusion detection system is composed of same sensors working in the same working point or different sensors.

scholarly journals A PRACH Preamble Generation and Detection Model for 5GNR Systems

2021 ◽  
pp. 98-105
Author(s):  
Puneeth K M ◽  
Poornima M S
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Additive White Gaussian Noise ◽  
Random Access ◽  
False Alarm Probability ◽  
Probability Of Detection ◽  
Detection Model ◽  
High Data ◽  
Access Channel ◽  
New Radio

The basic idea of 5th generation New Radio (5GNR) is to have very high data rate and to make it work efficiently for all Internet of Things (IOT) applications like healthcare, Automotive, Industrial etc. applications. This paper provides the Orthogonal Frequency Division Multiple Access (OFDM) baseband signal generation and detection method for Physical Random-Access Channel (PRACH). The proposed model provides four scenarios of preamble detection i.e., Preamble detection probability, Miss-detection probability, False alarm probability and null. We achieved the target of 99% of Probability of Detection and less than 0.1% of False-alarm probability at certain SNR as specified according to 3gpp standard requirements when tested in Additive White Gaussian Noise (AWGN) channel and Extended Typical Urban (ETU) channel.

scholarly journals Detection of Distributed Denial of Service Flooding Attack Using Odds Ratio

2021 ◽  
Vol 1 (2) ◽  
pp. 67-74
Author(s):  
Dalia Nashat ◽  
Fatma A. Hussain ◽  
Xiaohong Jiang
Keyword(s):  
Detection Probability ◽  
Odds Ratio ◽  
Detection Method ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Internet Routing ◽  
Denial Of Service Attack ◽  
Flooding Attack ◽  
Flooding Attacks ◽  
Service Attack

Computer networks are vulnerable to many types of attacks while the Distributed Denial of Service attack (DDoS) serves as one of the top concerns for security professionals. The DDoS flooding attack denies the services by consuming the server resources to prevent the legitimate users from using their desired services. The hardness of detecting this attack lies in sending a stream of packets to the server with spoofed IP addresses, so that the internet routing infrastructure cannot distinguish the spoofed packets. Based on the odds ratio (OR) statistical measurement, in this work we propose a new detection method for the DDoS flooding attacks. By exploring the odds ratio to determine the risk factor of any incoming traffic to the server, the legitimate and attack traffic packets can be easily differentiated. Experimental results demonstrate the efficiency of the presented detection method in terms of its detection probability and detection time.

scholarly journals An analysis of energy detector based on improved approximations of the chi-square distributions

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Felipe G. M. Elias ◽  
Evelio M. G. Fernández
Keyword(s):  
False Alarm ◽  
Detection Probability ◽  
Total Error ◽  
Detection Threshold ◽  
False Alarm Probability ◽  
Optimal Number ◽  
Energy Detector ◽  
Chi Square ◽  
Total Error Rate ◽  
Wide Range

AbstractClosed-form expressions for the detection probability, the false alarm probability and the energy detector constant threshold are derived using approximations of the central chi-square and non-central chi-square distributions. The approximations used show closer proximity to the original functions when compared to the expressions used in the literature. The novel expressions allow gains up to 6% and 16% in terms of measured false alarm and miss-detection probability, respectively, if compared to the Central Limit Theorem approach. The throughput of cognitive network is also enhanced when these novel expressions are implemented, providing gains up to 9%. New equations are also presented that minimize the total error rate to obtain the detection threshold and the optimal number of samples. The analytical results match the results of the simulation for a wide range of SNR values.

Cepstrum-Based Spectrum Hole Search in Different Fading Scenario in Cognitive Radio Network

2017 ◽  
pp. 49-62
Author(s):  
Srijibendu Bagchi
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Channel Fading ◽  
Spectral Density Estimation ◽  
Power Spectral ◽  
Detection Probabilities ◽  
Spectrum Scarcity ◽  
Spectrum Hole

Cognitive radio is now acknowledged as a potential solution to meet the spectrum scarcity problem in radio frequency range. To achieve this objective proper identification of vacant frequency band is necessary. In this article a detection methodology based on cepstrum estimation has been proposed that can be done through power spectral density estimation of the received signal. The detection has been studied under different channel fading conditions along with Gaussian noise. Two figures of merit are considered here; false alarm probability and detection probability. For a specific false alarm probability, the detection probabilities are calculated for different sample size and it has been established through numerical results that the proposed detector performs quite well in different channel impairments.

scholarly journals Robust Spectrum Sensing Demonstration Using a Low-Cost Front-End Receiver

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Daniele Borio ◽  
Emanuele Angiuli ◽  
Raimondo Giuliani ◽  
Gianmarco Baldini
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
High Frequency ◽  
Detection Probability ◽  
Low Cost ◽  
False Alarm Probability ◽  
Primary Users ◽  
Front End ◽  
Challenging Tasks

Spectrum Sensing (SS) is an important function in Cognitive Radio (CR) to detect primary users. The design of SS algorithms is one of the most challenging tasks in CR and requires innovative hardware and software solutions to enhance detection probability and minimize low false alarm probability. Although several SS algorithms have been developed in the specialized literature, limited work has been done to practically demonstrate the feasibility of this function on platforms with significant computational and hardware constraints. In this paper, SS is demonstrated using a low cost TV tuner as agile front-end for sensing a large portion of the Ultra-High Frequency (UHF) spectrum. The problems encountered and the limitations imposed by the front-end are analysed along with the solutions adopted. Finally, the spectrum sensor developed is implemented on an Android device and SS implementation is demonstrated using a smartphone.

A Blind Watermarking Method Based on Space Reconstruction

2013 ◽  
Vol 444-445 ◽  
pp. 712-716
Author(s):  
Xiu Hu Tan
Keyword(s):  
Detection Probability ◽  
Image Watermarking ◽  
Digital Signal ◽  
False Alarm Probability ◽  
Blind Watermarking ◽  
Statistical Property ◽  
Feature Spaces ◽  
High Detection ◽  
Hidden Data ◽  
Reversible Image Watermarking

Watermarking embeds information into a digital signal like audio, image, or video. Reversible image watermarking can restore the original image without any distortion after the hidden data is extracted. In this paper, we propose a blind watermarking method based on space reconstruction. Through calculating the statistical property of the digital image, we are able to separately obtain the feature spaces. Passing spaces decomposing and reconstructing of the feature spaces, constructing the embedding matrix, we obtain that the robustness of the approach lies in hiding a watermark in the subspace that is the least susceptible to potential modification; and realize the optimization statistics of the embedding watermark. Through analysis and constraint the conditions of subspace, the algorithm we proposed can obtain a high detection probability and security, a low false alarm probability. The robustness of the watermarking method is demonstrated by a kind of attacks through computer simulation.

A Reliable Spectrum Sensing Strategy Based on Multiple-Antenna Technique

2013 ◽  
Vol 765-767 ◽  
pp. 2305-2308
Author(s):  
Shou Tao Lv ◽  
Ze Yang Dai ◽  
Jian Liu
Keyword(s):  
Performance Analysis ◽  
False Alarm ◽  
Closed Form ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Multiple Antenna ◽  
Single Antenna ◽  
Simulation Results ◽  
Present Simulation

In this paper, we propose a reliable spectrum sensing strategy based on multiple-antenna technique, called RSS-MAT, to combat the channel uncertainties. We derive the closed-form expressions of the false alarm probability and detection probability for RSS-MAT. Finally, we present simulation results to validate our performance analysis. As expected, the simulation results show that RSS-MAT outperforms the spectrum sensing strategy with single antenna.

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