scholarly journals An Algorithm of Traffic Perception of DDoS Attacks against SOA Based on Time United Conditional Entropy

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Yuntao Zhao ◽  
Hengchi Liu ◽  
Yongxin Feng
Keyword(s):  
Conditional Entropy ◽  
System Security ◽  
The Novel ◽  
Ddos Attacks ◽  
Time Dimension ◽  
Ip Address ◽  
Ip Addresses ◽  
Traffic Characteristics ◽  
Novel Method ◽  
Simulation Results

DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destination IP addresses of DDoS attacks, traffic characteristics of services are analyzed based on conditional entropy. The algorithm is provided with perception ability of DDoS attacks on SOA services by introducing time dimension. Simulation results show that the novel method can realize DDoS traffic perception with analyzing abrupt variation of conditional entropy in time dimension.

Optimization of Bending Process of Large Marine Crankthrow by Computer Simulation

2007 ◽  
Vol 561-565 ◽  
pp. 1949-1952 ◽  
Author(s):  
Ming Yue Sun ◽  
Shan Ping Lu ◽  
Dian Zhong Li ◽  
Yi Yi Li
Keyword(s):  
Computer Simulation ◽  
Conventional Method ◽  
Transformation Method ◽  
Actual Process ◽  
The Novel ◽  
Fem Model ◽  
Maximum Resistance ◽  
Bending Process ◽  
Novel Method ◽  
Simulation Results

The conventional method of bending the large crankthrow was investigated by computer simulation combined with manufacturing trial, and the typical forging defects, such as constricted waist, folded cracks and horn mouth on forged blank were analyzed. On the basis of these results, a novel forging shape of preformed blank was proposed using anti-transformation method by computer simulation. The FEM simulated results show that all the above defects can be avoided by carrying out the novel method, furthermore, the maximum resistance of the novel bending deformation was reduced to 72% of conventional process, and the weight of forging blank can be decreased by 15%. Finally, the optimum forging shape was applied to the actual process, the simulation results were confirmed by manufacturing trial, and qualified forged piece was gained. The FEM model established can be used for further optimization of other types of crankthrow.

A Novel Method for Online Measuring the Short-Circuit Impedance of Distribution Transformers

2011 ◽  
Vol 301-303 ◽  
pp. 1072-1077
Author(s):  
Xia Li ◽  
Min You Chen ◽  
Shan Cheng
Keyword(s):  
Short Circuit ◽  
Equivalent Circuit Model ◽  
Current Data ◽  
The Novel ◽  
Distribution Transformers ◽  
Novel Method ◽  
Simulation Results ◽  
Data Acquisition Unit ◽  
Secondary Side ◽  
Circuit Impedance

The paper proposes a novel method for online measuring the short-circuit impendence of the distribution transformers (DT). The relation expression of the short-circuit impedance with respect to the voltage and current of the primary and secondary side has been developed through the analysis of the equivalent circuit model of a transformer, in which the voltage and current of the DT is collected by 12-channel-data-acquisition unit. And the online SCI is computed by fitting the obtained voltage and current data. The simulation results and comparison illustrated that the proposed method is simpler and more efficient with high accuracy. Besides, the proposed method integrates the linear fitting technique. The simulation results based on Matlab/smulink verified the feasibility and effectiveness of the novel method for online measuring the short-circuit impendence of the DT.

scholarly journals Detection and mitigation of SYN and HTTP flood DDoS attacks in software defined networks

2021 ◽  
Author(s):  
Amandeep Singh Dhaliwal
Keyword(s):  
Denial Of Service ◽  
False Positives ◽  
Ddos Attacks ◽  
Network Resources ◽  
Detection Mechanism ◽  
Ip Address ◽  
Security Scheme ◽  
Ip Addresses ◽  
Simple Detection ◽  
Mitigation Methods

Distributed Denial of Service (DDoS) constitutes major threat to both traditional and SDN networks. An attacker can launch a DDoS attack to exhaust either the controller or other network resources, such as switches, or both. There are different DDoS attacks such as UDP flood, SYN flood, Ping of death, ICMP flood and HTTP flood. Among these, SYN and HTTP flood are the most common attacks these days. In this thesis, we focus on developing a security scheme to alleviate the DDoS attacks with spoofed and non-spoofed IP addresses in the SDN environment. First we use a simple detection mechanism that utilizes a time series window-based traffic statistic measurement to detect possible SYN flood and/or HTTP flood DDoS attacks. To reduce false positives, further investigation of traffic is done based on valid source IP address scheme and single flow packet scheme to separate legitimate traffic from attack traffic. Once the attack is detected, the security scheme deploys a number of mitigation methods to alleviate the attack. For the SYN flood attack, the mitigation method of Source IP address filtering is used to permit traffic only with valid source IP addresses to enter the network. For HTTP flood attack mitigation, a mitigation method is used to identify the attack sources and discard the traffic from those sources. We test our proposed scheme with other DDoS attacks such as ICMP flood attack and UDP flood attacks. We also compare our scheme with other security schemes found in the literature. The result shows that our proposed scheme can effectively protect controller and other network resources from some common DDoS attacks, and that our scheme allows more legitimate traffic connections with less false positives in comparison with other schemes.

A NOVEL METHOD TO ANALYZE PHASE DIAGRAMS FOR TRAFFICS ON THE CROSSROAD

2012 ◽  
Vol 23 (10) ◽  
pp. 1250068 ◽  
Author(s):  
QI-LANG LI ◽  
RUI JIANG ◽  
BING-HONG WANG ◽  
MU-REN LIU
Keyword(s):  
Computer Simulation ◽  
Phase Diagrams ◽  
Traffic Flow ◽  
Occupation Probability ◽  
Traffic Model ◽  
Probability Method ◽  
The Novel ◽  
Novel Method ◽  
Simulation Results ◽  
Good Agreement

Traffic flow at a single crossroad consisting of two perpendicular one-lane roads, treated earlier by Ishibashi and Fukui [J. Phys. Soc. Jpn.70, 2793 (2001); 70, 3747 (2001)], has been studied on the basis of the local occupation probability method. However, in this work, based on the novel theoretical analysis and computer simulations, we have studied this crossroad traffic model again and presented the same phase diagrams of traffic flow in the case of various maximum vehicle velocities. We have also derived the flow formulas in all regions in the phase diagrams, which are in good agreement with computer simulation results. Compared with the previous local occupation probability method, our analytical way is simpler and may be widely used for other traffic bottlenecks research.

IP Traceback using Flow Based Classification

2020 ◽  
Vol 13 (3) ◽  
pp. 482-490
Author(s):  
Yerram Bhavani ◽  
Vinjamuri Janaki ◽  
Rangu Sridevi
Keyword(s):  
Chinese Remainder Theorem ◽  
Denial Of Service ◽  
False Positives ◽  
Ddos Attacks ◽  
False Negatives ◽  
Ip Address ◽  
Attack Graph ◽  
Ip Traceback ◽  
Ip Addresses ◽  
Attack Path

Background:Distributed Denial of Service (DDoS) attack is a major threat over the internet. The IP traceback mechanism defends against DDoS attacks by tracing the path traversed by attack packets. The existing traceback techniques proposed till now are found with few short comings. The victim required many number of packets to trace the attack path. The requirement of a large number of packets resulted in more number of combinations and more false positives.Methods:To generate a unique value for the IP address of the routers in the attack path Chinese Remainder theorem is applied. This helped in combining the exact parts of the IP address at the victim. We also applied K-Nearest Neighbor (KNN) algorithm to classify the packets depending on their traffic flow, this reduced the number of packets to reconstruct the attack path.Results:The proposed approach is compared with the existing approaches and the results demonstrated that the attack graph is effectively constructed with higher precision and lower combination overhead under large scale DDoS attacks. In this approach, packets from diverse flows are separated as per flow information by applying KNN algorithm. Hence, the reconstruction procedure could be applied on each group separately to construct the multiple attack paths. This results in reconstruction of the complete attack graph with fewer combinations and false positive rate.Conclusion:In case of DDoS attacks the reconstruction of the attack path plays a major role in revealing IP addresses of the participated routers without false positives and false negatives. Our algorithm FRS enhances the feasibility of information pertaining to even the farthest routers by incorporating a flag condition while marking the packets. The rate of false positives and false negatives are drastically reduced by the application of Chinese Remainder Theorem on the IP addresses of the router. At the victim, the application of KNN algorithm reduced the combination overhead and the computation cost enormously.

scholarly journals Detection and mitigation of SYN and HTTP flood DDoS attacks in software defined networks

2021 ◽  
Author(s):  
Amandeep Singh Dhaliwal
Keyword(s):  
Denial Of Service ◽  
False Positives ◽  
Ddos Attacks ◽  
Network Resources ◽  
Detection Mechanism ◽  
Ip Address ◽  
Security Scheme ◽  
Ip Addresses ◽  
Simple Detection ◽  
Mitigation Methods

Distributed Denial of Service (DDoS) constitutes major threat to both traditional and SDN networks. An attacker can launch a DDoS attack to exhaust either the controller or other network resources, such as switches, or both. There are different DDoS attacks such as UDP flood, SYN flood, Ping of death, ICMP flood and HTTP flood. Among these, SYN and HTTP flood are the most common attacks these days. In this thesis, we focus on developing a security scheme to alleviate the DDoS attacks with spoofed and non-spoofed IP addresses in the SDN environment. First we use a simple detection mechanism that utilizes a time series window-based traffic statistic measurement to detect possible SYN flood and/or HTTP flood DDoS attacks. To reduce false positives, further investigation of traffic is done based on valid source IP address scheme and single flow packet scheme to separate legitimate traffic from attack traffic. Once the attack is detected, the security scheme deploys a number of mitigation methods to alleviate the attack. For the SYN flood attack, the mitigation method of Source IP address filtering is used to permit traffic only with valid source IP addresses to enter the network. For HTTP flood attack mitigation, a mitigation method is used to identify the attack sources and discard the traffic from those sources. We test our proposed scheme with other DDoS attacks such as ICMP flood attack and UDP flood attacks. We also compare our scheme with other security schemes found in the literature. The result shows that our proposed scheme can effectively protect controller and other network resources from some common DDoS attacks, and that our scheme allows more legitimate traffic connections with less false positives in comparison with other schemes.

Novel Initialization Method for Nonlinear Kalman Filters

2013 ◽  
Vol 834-836 ◽  
pp. 1047-1050
Author(s):  
Yu Zhe Wang ◽  
Hang Su ◽  
Yu Cao ◽  
Han Liu
Keyword(s):  
Kalman Filter ◽  
Kalman Filters ◽  
Estimation Error ◽  
The Novel ◽  
Ordinary Method ◽  
Nonlinear Kalman Filter ◽  
Novel Method ◽  
Simulation Results ◽  
The Impact

A novel initialization method for nonlinear Kalman filter was proposed aimed at the defects of the ordinary initialization method. This method was stricter than the ordinary method in theory and could guarantee scientific compare between nonlinear Kalman filters based on Gaussian assumptions. Simulation results showed that the novel method greatly reduced the impact of initialization and reflected more the estimation error due to the type of nonlinear Kalman filters rather than initialization.

A novel method for the determination of linting propensity of paper

TAPPI Journal ◽  
2012 ◽  
Vol 11 (10) ◽  
pp. 9-17
Author(s):  
ALESSANDRA GERLI ◽  
LEENDERT C. EIGENBROOD
Keyword(s):  
Ash Content ◽  
The Novel ◽  
Offset Printing ◽  
Excellent Correlation ◽  
End Conditions ◽  
Bottom Side ◽  
Novel Method ◽  
Total Fraction

A novel method was developed for the determination of linting propensity of paper based on printing with an IGT printability tester and image analysis of the printed strips. On average, the total fraction of the surface removed as lint during printing is 0.01%-0.1%. This value is lower than those reported in most laboratory printing tests, and more representative of commercial offset printing applications. Newsprint paper produced on a roll/blade former machine was evaluated for linting propensity using the novel method and also printed on a commercial coldset offset press. Laboratory and commercial printing results matched well, showing that linting was higher for the bottom side of paper than for the top side, and that linting could be reduced on both sides by application of a dry-strength additive. In a second case study, varying wet-end conditions were used on a hybrid former machine to produce four paper reels, with the goal of matching the low linting propensity of the paper produced on a machine with gap former configuration. We found that the retention program, by improving fiber fines retention, substantially reduced the linting propensity of the paper produced on the hybrid former machine. The papers were also printed on a commercial coldset offset press. An excellent correlation was found between the total lint area removed from the bottom side of the paper samples during laboratory printing and lint collected on halftone areas of the first upper printing unit after 45000 copies. Finally, the method was applied to determine the linting propensity of highly filled supercalendered paper produced on a hybrid former machine. In this case, the linting propensity of the bottom side of paper correlated with its ash content.

A Strong Tracking Cubature Kalman Filter for Nonlinear Estimation

2013 ◽  
Vol 313-314 ◽  
pp. 1115-1119
Author(s):  
Yong Qi Wang ◽  
Feng Yang ◽  
Yan Liang ◽  
Quan Pan
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Scaling Factor ◽  
Estimation Accuracy ◽  
Nonlinear State Estimation ◽  
Cubature Kalman Filter ◽  
Novel Method ◽  
Simulation Results ◽  
Tracking Filter ◽  
Nonlinear State

In this paper, a novel method based on cubature Kalman filter (CKF) and strong tracking filter (STF) has been proposed for nonlinear state estimation problem. The proposed method is named as strong tracking cubature Kalman filter (STCKF). In the STCKF, a scaling factor derived from STF is added and it can be tuned online to adjust the filtering gain accordingly. Simulation results indicate STCKF outperforms over EKF and CKF in state estimation accuracy.

scholarly journals REMAXINT: a two-mode clustering-based method for statistical inference on two-way interaction

2021 ◽  
Author(s):  
Zaheer Ahmed ◽  
Alberto Cassese ◽  
Gerard van Breukelen ◽  
Jan Schepers
Keyword(s):  
Null Hypothesis ◽  
Type I Error ◽  
Type I ◽  
The Novel ◽  
Simulation Studies ◽  
Test Statistic ◽  
Clustering Model ◽  
Novel Method ◽  
Main Effects ◽  
Empirical Case Studies

AbstractWe present a novel method, REMAXINT, that captures the gist of two-way interaction in row by column (i.e., two-mode) data, with one observation per cell. REMAXINT is a probabilistic two-mode clustering model that yields two-mode partitions with maximal interaction between row and column clusters. For estimation of the parameters of REMAXINT, we maximize a conditional classification likelihood in which the random row (or column) main effects are conditioned out. For testing the null hypothesis of no interaction between row and column clusters, we propose a $$max-F$$ m a x - F test statistic and discuss its properties. We develop a Monte Carlo approach to obtain its sampling distribution under the null hypothesis. We evaluate the performance of the method through simulation studies. Specifically, for selected values of data size and (true) numbers of clusters, we obtain critical values of the $$max-F$$ m a x - F statistic, determine empirical Type I error rate of the proposed inferential procedure and study its power to reject the null hypothesis. Next, we show that the novel method is useful in a variety of applications by presenting two empirical case studies and end with some concluding remarks.

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