• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.751-765
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• 2012

Key establishment protocols are fundamental for establishing secure communication channels over public insecure networks. Security must be given the topmost priority in the design of a key establishment protocol. In this work, we provide a security analysis on two recent key establishment protocols: Harn and Lin's group key transfer protocol and Dutta and Barua's group key agreement protocol. Our analysis shows that both the Harn-Lin protocol and the Dutta-Barua protocol have a flaw in their design and can be easily attacked. The attack we mount on the Harn-Lin protocol is a replay attack whereby a malicious user can obtain the long-term secrets of any other users. The Dutta-Barua protocol is vulnerable to an unknown key-share attack. For each of the two protocols, we present how to eliminate their security vulnerabilities. We also improve Dutta and Barua's proof of security to make it valid against unknown key share attacks.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.1
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• pp.32-37
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• 2002

The presence of hydrogen in industrial plants is a source of damage. Hydrogen attack is one such form of degradation and often causing large tube ruptures that necessitate an immediate shutdown. Hydrogen attack may reduce the fracture toughness as well as the strength of steels. This reduction is caused partially by the presence of cavities and microcracks at the grain boundaries. In the past several techniques have been used with limited results. This paper describes the application of an ultrasonic velocity and attenuation in hydrogen damage. Ultrasonic tests showed a decrease in wave velocity and an increase in attenuation. Such results demonstrate the potential for ultrasonic nondestructive testing to quantify damage. Based on this study, reliable recommendation is suggested to detect hydrogen attack.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.185-190
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• 2009

As the use of RSA based on chinese remainder theorem(CRT-RSA) is being generalized, the security of CRT-RSA has been important. Since Bellcore researchers introduced the fault attacks on CRT-RSA, various countermeasures have been proposed. In 1999, Shamir firstly proposed a countermeasure using checking procedure. After Shamir's countermeasure was introduced, various countermeasures based on checking procedure have been proposed. However, Shamir's countermeasure was known to be vulnerable to the modified operand attack by Joey et al. in 2001, and the checking procedure was known to be vulnerable to the modified opcode attack by Yen et al. in 2003. Yen et al. proposed a new countermeasure without checking procedure, but their countermeasure was known to be also vulnerable to the modified operand attack by Yen and Kim in 2007. In this paper, we point out that pre, but countermeasures were vulnerable to the modified operand attack or the modified opcode attack.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.1-8
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• 2020

Recently, the number of APT(Advanced Persistent Threats) attack using malware has been increasing, and research is underway to prevent and detect them. While it is important to detect and block attacks before they occur, it is also important to make an effective response through an accurate analysis for attack case and attack type, these respond which can be determined by analyzing the attack group of such attacks. Therefore, this paper propose a framework based on genetic algorithm for analyzing malware and understanding attacker group's features. The framework uses decompiler and disassembler to extract related code in collected malware, and analyzes information related to author through code analysis. Malware has unique characteristics that only it has, which can be said to be features that can identify the author or attacker groups of that malware. So, we select specific features only having attack group among the various features extracted from binary and source code through the authorship clustering method, and apply genetic algorithm to accurate clustering to infer specific features. Also, we find features which based on characteristics each group of malware authors has that can express each group, and create profiles to verify that the group of authors is correctly clustered. In this paper, we do experiment about author classification using genetic algorithm and finding specific features to express author characteristic. In experiment result, we identified an author classification accuracy of 86% and selected features to be used for authorship analysis among the information extracted through genetic algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.9-17
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• 2019

As the IoT environment becomes more popular, the safety of the M2M environment, which establishes the communication environment between objects and objects without human intervention, becomes important. Due to the nature of the wireless communication environment, there is a possibility of exposure to security threats in various aspects such as data exposure, falsification, tampering, deletion and privacy, and secure communication security technology is considered as an important requirement. In this paper, we propose a new method for group key generation and exchange using trap hash collision hash in existing 'M2M communication environment' using hash collision, And a mechanism for confirming the authentication of the device and the gateway after the group key is generated. The proposed method has attack resistance such as spoofing attack, meson attack, and retransmission attack in the group communication section by using the specificity of the collision message and collision hash, and is a technique for proving safety against vulnerability of hash collision.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.3
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• pp.271-276
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• 2023

Backgrounds/Aims: Laparoscopic cholecystectomy within one week of acute cholecystitis is considered safe and advantageous. Surgery beyond first week is reserved for non-resolving attack or complications. To compare clinical outcomes of patients undergoing laparoscopic cholecystectomy in the first week and between two to six weeks of an attack of acute cholecystitis. Methods: In an analysis of a prospectively maintained database, all patients who underwent laparoscopic cholecystectomy for acute cholecystitis were divided into two groups: group A, operated within one week; and group B, operated between two to six weeks of an attack. Main variables studied were mean operative time, conversion to open cholecystectomy, morbidity profile, and duration of hospital stay. Results: A total of 116 patients (74 in group A and 42 in group B) were included. Mean interval between onset of symptoms & surgery was five days (range, 1-7 days) in group A and 12 days (range, 8-20 days) in group B. Operative time and incidence of subtotal cholecystectomy were higher in group B (statistically not significant). Mean postoperative stay was 2 days in group A and 3 days in group B. Laparoscopy was converted to open cholecystectomy in two patients in each group. There was no incidence of biliary injury. One patient in group B died during the postoperative period due to continued sepsis and multiorgan failure. Conclusions: In tertiary care setting, with adequate surgical expertise, laparoscopic cholecystectomy can be safely performed in patients with acute cholecystitis irrespective of the time of presentation.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.165-171
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• 2018

The most threatening attack that has become a hot topic of recent IT security is APT Attack.. So far, there is no way to respond to APT attacks except by using artificial intelligence techniques. Here, we have implemented a machine learning algorithm for analyzing cyber threat data using machine learning method, using a data set that collects cyber attack cases using Scikit Learn, a big data machine learning framework. The result showed an attack classification accuracy close to 70%. This result can be developed into the algorithm of the security control system in the future.

• The Journal of Internal Korean Medicine
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• v.21 no.1
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• pp.135-145
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• 2000

Objective : This study has been made to analysis of clinical type of vertigo prodromic Cerebral Vascular Disease in stroke patients who admitted to sangji oriental hospital department of circulatoty internal medicine in the period from July. 1999 to October 1999. Methods : A Questionaire was done after explanationin details to patients and agreement of patients. The inquire was done as follows. Sex and age, risk factor of stroke, type of stroke, existence of vertigo last three years before stroke attack, the beginning age of vertigo and period of prevalence, frequency, continuance time of vertigo, predilection season and time, factor of causing vertigo, accompanying symptoms of vertigo, severity of vertigo. Result and Conclusion : The existence of Rotation sense(Rotation group and non-Rotation group) and the type of Stroke is no difference significantly but the Rotation vertigo group and non-Rotation vertigo group is difference significantly in distribution. The sixties in age of vertigo attack, previous vertigo before 3 year Stroke attack, irregular in predilection season of vertigo, have a high frequency significantly in distribution and previous period of vertigo has no significantly difference in distribution. One or two per a month in frequency of vertigo, below 5 minute in continuance time of vertigo, irregular in predilection time of vertigo, stand up and sit down in causing vertigo position have a high frequency significantly in distribution.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.14-21
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• 2005

Even though mainly statistical methods have been used in anomaly network intrusion detection, to detect various attack types, machine learning based anomaly detection was introduced. Machine learning based anomaly detection started from research applying traditional learning algorithms of artificial intelligence to intrusion detection. However, detection rates of these methods are not satisfactory. Especially, high false positive and repeated alarms about the same attack are problems. The main reason for this is that one packet is used as a basic learning unit. Most attacks consist of more than one packet. In addition, an attack does not lead to a consecutive packet stream. Therefore, with grouping of related packets, a new approach of group-based learning and detection is needed. This type of approach is similar to that of multiple-instance problems in the artificial intelligence community, which cannot clearly classify one instance, but classification of a group is possible. We suggest group generation algorithm grouping related packets, and a learning algorithm based on a unit of such group. To verify the usefulness of the suggested algorithm, 1998 DARPA data was used and the results show that our approach is quite useful.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.4
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• pp.355-366
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• 2007

In this paper, we propose a new blind group identification protocol and a hidden group signature protocol as its application. These protocols involve many provers and one verifier such that (1) the statement of all the provers are proved simultaneously, (2) and also all the provers using computationally limited devices (e.g. smart cards) have no need of computing the bilinear pairings, (3) but only the verifier uses the bilinear pairings. A. Saxena et al. proposed a two-round blind (group) identification protocol in 2005 using the bilinear pairings. But it reveals weakness in the active-intruder attack, and all the provers as well as the verifier must have devices computing bilinear pairings. Comparing their results, our protocol is secure from the active-intruder attack and has more fit for smart cards. In particular, it is secure under only the assumption of the hardness of the Discrete-Logarithm Problem in bilinear groups.