• Korean Journal of Applied Biomechanics
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• v.27 no.1
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• pp.1-7
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• 2017

Objective: The purpose of this study was to analyze the relationship between ground reaction force (GRF) and attack time according to the position of hand segments during counter attack in Kendo. Method: The participants consisted of 10 kendo athletes (mean age: $21.50{\pm}1.95yr$, mean height: $175.58{\pm}5.02cm$, mean body weight: $70.96{\pm}9.47kg$) who performed standard head strikes (A) and counter attack with a preferred hand position of +10 cm (B), 0 cm (C), and -10 cm (D). One force-plate (AMTI-OR-7., USA) was used to collect GRF data at a sample rate of 1,000 Hz. The variables analyzed were the attack time, medial-lateral GRF, anterior-posterior GRF (AP GRF), peak vertical force (PVF), and loading rate. Results: The total attack time was shorter in types A and C than in types C and D. The AP GRF, PVF, and loading rate had significantly higher forces in types C and D than in types A and C. The attack time (bilateral and unilateral leg support and total) was positively correlated with the GRF variables (vertical GRF and loading rate) during the counter attack in Kendo (r = 0.779 [$R^2=0.607$], p < 0.001). Conclusion: The positions of the hand segments can be changed by various conditions of the opponent in Kendo competitions; however, the position preferred by an individual can promote the successful ratio of the counter attack.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.201-212
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• 2009

Even though the spread spectrum method is known as most robust algorithm to general attacks, it has a drawback to the time axis attack. In this paper, I proposed a robust audio copyright protection algorithm which is robust to the time axis attack and has advantages of the spread spectrum method. Time axis attack includes the audio length variation attack with same pitch and the audio frequency variation attack. In order to detect the embedded watermark by the spread spectrum method, the detection algorithm should know the exact rate of the time axis attack. Even if there is a method to know the rate, it needs heavy computational resource and it is not possible to implement. In this paper, solving this problem, the audio signal is transformed into time-invariant domain, and the spread spectrum watermark is embedded into the audio in the domain. Therefore the proposed algorithm has the advantages of the spread spectrum method and it is also robust to the time axis attack. The time-invariant domain process is that the audio is arranged by log scale time axis, and then, the Fourier transform is taken to the audio in the log scale time axis. As a result, the algorithm can get the time-invariant watermark signal.

• ETRI Journal
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• v.44 no.2
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• pp.346-354
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• 2022

The SYN flooding attack is widely used in cyber attacks because it paralyzes the network by causing the system and bandwidth resources to be exhausted. This paper proposed a self-information approach for detecting the SYN flooding attack and provided a detection algorithm with a hierarchical policy on a detection time domain. Compared with other detection methods of entropy measurement, the proposed approach is more efficient in detecting the SYN flooding attack, providing low misjudgment, hierarchical detection policy, and low time complexity. Furthermore, we proposed a detection algorithm with limiting system resources. Thus, the time complexity of our approach is only (log n) with lower time complexity and misjudgment rate than other approaches. Therefore, the approach can detect the denial-of-service/distributed denial-of-service attacks and prevent SYN flooding attacks.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.3
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• pp.253-270
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• 2015

Two major simultaneous attack strategies have been introduced, as one of cooperative attack of multiple missiles. One strategy is an undesignated time attack, in which the missiles communicate among themselves to synchronize the arrival times by reducing the mutual differences of times-to-go of multiple missiles during the homing. The other is a designated time attack, in which a common impact time is commanded to all members in advance, and thereafter each missile tries to home on the target on time independently. For this individual homing, Impact-Time-Control Guidance (ITCG) law is required. After introducing cooperative proportional navigation (CPN) for the first strategy, this article presents a new closed-form ITCG guidance solution for the second strategy. It is based on the linear formulation, employing base trajectories driven by PNG with various navigation constants. Nonlinear simulation of several engagement situations demonstrates the performance and feasibility of the proposed ITCG law.

• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.243-250
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• 2008

Recently, researched RFID authentication protocols still have vulnerability of attack, such as location tracking attack, replay attack. spoofing attack etc. This paper designed method of making one time random number in DB server side unlike previously researched protocols, and it protects RFID communication from location tracking, replay attack and spoofing attack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1802-1819
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• 2017

Correlation-enhanced collision attack has been proposed by Moradi et al. for several years. However, in practical operations, this method costs lots of time on trace acquisition, storage and averaging due to its bytewise collision detection. In this paper, we propose a bitwise collision attack based on second-order distance model. In this method, only 9 average traces are enough to finish a collision attack. Furthermore, two candidate models are given in this study to distinguish collisions, and the corresponding practical experiments are also performed. The experimental results indicate that the operation time of our attack is only 8% of that of correlation-enhanced collision attack, when the two success rates are both above 0.9.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7B
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• pp.592-600
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• 2008

In this paper, a Hybrid Scaling based DTW (HS-DTW) mechanism is proposed for detection of periodic shrew TCP attacks. A low-rate TCP attack which is a type of shrew DoS (Denial of Service) attacks, was reported recently, but it is difficult to detect the attack using previous flooding DoS detection mechanisms. A pattern matching method with DTW (Dynamic Time Warping) as a type of defense mechanisms was shown to be reasonable method of detecting and defending against a periodic low-rate TCP attack in an input traffic link. This method, however, has the problem that a legitimate link may be misidentified as an attack link, if the threshold of the DTW value is not reasonable. In order to effectively discriminate between attack traffic and legitimate traffic, the difference between their DTW values should be large as possible. To increase the difference, we analyze a critical problem with a previous algorithm and introduce a scaling method that increases the difference between DTW values. Four kinds of scaling methods are considered and the standard deviation of the sampling data is adopted. We can select an appropriate scaling scheme according to the standard deviation of an input signal. This is why the HS-DTW increases the difference between DTW values of legitimate and attack traffic. The result is that the determination of the threshold value for discrimination is easier and the probability of mistaking legitimate traffic for an attack is dramatically reduced.

• Journal of Multimedia Information System
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• v.7 no.2
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• pp.125-136
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• 2020

Nowadays, cloud computing is becoming more popular among companies. However, the characteristics of cloud computing such as a virtualized environment, constantly changing, possible to modify easily and multi-tenancy with a distributed nature, it is difficult to perform attack detection with traditional tools. This work proposes a solution which aims to collect traffic packets data by using Flume and filter them with Spark Streaming so it is possible to only consider suspicious data related to HTTP Slow Rate Denial-of-Service attacks and reduce the data that will be stored in Hadoop Distributed File System for analysis with the FP-Growth algorithm. With the proposed system, we also aim to address the difficulties in attack detection in cloud environment, facilitating the data collection, reducing detection time and enabling an almost real-time attack detection.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.514-518
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• 2003

In this paper, we investigate three dimensional optimal evasive maneuver patterns for air-to-surface attack missiles against proportionally navigated anti-air defense missiles. Interception error of the defense missile can be generated by evasive maneuver of the attack missile during the time of flight for which the defense missile intercepts the attack missile. Time varying weighted sum of the inverse of these interception errors forms a performance index to be minimized. Direct parameter optimization technique using CFSQP is adopted to get the attack missile's optimal evasive maneuver patterns according to parameter changes of both the attack missile and the defense missile such as maneuver limit and time constant of autopilot approximated by the 1st order lag system. The overall shape of resultant optimal evasive maneuver to enhance the survivability of air-to-surface missiles against proportionally navigated anti-air missiles is a kind of deformed barrel roll.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.6
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• pp.151-158
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• 2019

FLUSH+RELOAD attack exposes the most serious security threat among cache side channel attacks due to its high resolution and low noise. This attack is exploited by a variety of malicious programs that attempt to leak sensitive information. In order to prevent such information leakage, it is necessary to detect FLUSH+RELOAD attack in real time. In this paper, we propose a novel run-time detection technique for FLUSH+RELOAD attack by utilizing PCM (Performance Counter Monitor) of processors. For this, we conducted four kinds of experiments to observe the variation of each counter value of PCM during the execution of the attack. As a result, we found that it is possible to detect the attack by exploiting three kinds of important factors. Then, we constructed a detection algorithm based on the experimental results. Our algorithm utilizes machine learning techniques including a logistic regression and ANN(Artificial Neural Network) to learn from different execution environments. Evaluation shows that the algorithm successfully detects all kinds of attacks with relatively low false rate.