• Convergence Security Journal
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• v.18 no.5_1
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• pp.33-43
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• 2018

In this paper, we want to solve the problems that users want to search the progress of attack, continuity of attack, association between attackers and victims, blocking priority and countermeasures by using visualization interface with multi-rotational axis and radial axis structure. It is possible to effectively monitor and track security events by arranging a time series event based on a multi-rotational axis structured by an event generation order, a subject of an event, an event type, and an emission axis, which is an objective time indicating progress of individual events. The proposed interface is a practical visualization interface that can apply attack blocking and defense measures by providing the progress and progress of the whole attack, the details and continuity of individual attacks, and the relationship between attacker and victim in one screen.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.15 no.1
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• pp.17-27
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• 2005

With the development of wire and wireless based networks, a various security protocols have been proposed to protect important resources and user information against attackers. However, many security protocols have found oかy to be later vulnerable to attacks. In this Paper, we introduce the formal methodology to verify the safety of security protocols in the design phase, and we take advantage of the formal methodology which uses Casper/CSP and FDR tools by introducing the verification example of EKE protocol and BCY protocol. Lastly, we propose a new BCY protocol after verifying it's safety.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.1
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• pp.103-114
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• 2008

Single Sign-On is an authentication scheme that enables a user to authenticate once and then to access to the resources of multiple software systems without re-authentication. As web services are being integrated into a single groupware, more web sites are adopting for user convenience. However, these Single Sign-On services are very dependent upon the cookies and thus, simple eavesdropping enables attackers to hiject the user's session. Even worse, the attacker who hijacked one session can move to another site through the Single Sign-On. In this paper, we show the vulnerabilities of the top ranked sites regarding this point of view and also propose a way to protect a user's session.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.187-194
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• 2008

This paper proposes an effective countermeasure to an intrinsic hardware vulnerability of the keyboard controller that causes sniffing problem on the password authentication system based on the keyboard input string. Through the vulnerability, some possible attacker is able to snoop whole the password string input from the keyboard even when any of the existing keyboard protection software is running. However, it will be impossible for attackers to gather the exact password strings if the proposed policy is applied to the authentication system though they can sniff the keyboard hardware protocol. It is expected that people can use secure Internet commerce after implementing and applying the proposed policy to the real environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.135-144
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• 2009

This paper deals with an information security problem that involves the strategies of both an attacker and an administrator of a web-based system. A game-theoretic model for the problem, based on an Stackelberg game environment, is presented. In the model, the administrator selects a set of anti-virus vaccines to cope with potential system attackers and the intruder chooses attacking modes that are most effective against the administrator's chosen set of vaccines. Moreover, the model considers a number of practical constraints, such as a budget limit on the vaccine purchase and a limit on the system performance. In addition, two different scenario analyses are provided, based on the results of the proposed model applied to a simulated pseudo-real-world data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.177-182
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• 2011

This paper introduces a possibility for attackers to acquire the keyboard scan codes through using the RESEND command provided by the keyboard hardware itself, based on the PS/2 interface that is a dominant interface for input devices. Accordingly, a keyboard sniffing program using the introduced vulnerability is implemented to prove the severeness of the vulnerability, which shows that user passwords can be easily exposed. As one of the intrinsic vulnerabilities found on the existing platforms, for which there were little considerations on the security problems when they were designed, it is required to consider a hardware approach to countermeasure the introduced vulnerability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4909-4926
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• 2020

Cyberattacks penetrate the server and perform various malicious acts such as stealing confidential information, destroying systems, and exposing personal information. To achieve this, attackers perform various malicious actions by infecting endpoints and accessing the internal network. However, the current countermeasures are only anti-viruses that operate in a signature or pattern manner, allowing initial unknown attacks. Endpoint Detection and Response (EDR) technology is focused on providing visibility, and strong countermeasures are lacking. If you fail to respond to the initial attack, it is difficult to respond additionally because malicious behavior like Advanced Persistent Threat (APT) attack does not occur immediately, but occurs over a long period of time. In this paper, we propose a technique that detects an unknown attack using an event log without prior knowledge, although the initial response failed with anti-virus. The proposed technology uses a combination of AutoEncoder and 1D CNN (1-Dimention Convolutional Neural Network) based on semi-supervised learning. The experiment trained a dataset collected over a month in a real-world commercial endpoint environment, and tested the data collected over the next month. As a result of the experiment, 37 unknown attacks were detected in the event log collected for one month in the actual commercial endpoint environment, and 26 of them were verified as malicious through VirusTotal (VT). In the future, it is expected that the proposed model will be applied to EDR technology to form a secure endpoint environment and reduce time and labor costs to effectively detect unknown attacks.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.286-293
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• 2021

Recently, the quick development rate of apps in the Android platform has led to an accelerated increment in creating malware applications by cyber attackers. Numerous Android malware detection tools have utilized conventional signature-based approaches to detect malware apps. However, these conventional strategies can't identify the latest apps on whether applications are malware or not. Many new malware apps are periodically discovered but not all malware Apps can be accurately detected. Hence, there is a need to propose intelligent approaches that are able to detect the newly developed Android malware applications. In this study, Radial Basis Function (RBF) networks are trained using known Android applications and then used to detect the latest and new Android malware applications. Initially, the optimal permission features of Android apps are selected using Information Gain Ratio (IGR). Appropriately, the features selected by IGR are utilized to train the RBF networks in order to detect effectively the new Android malware apps. The empirical results showed that RBF achieved the best detection accuracy (97.20%) among other common machine learning techniques. Furthermore, RBF accomplished the best detection results in most of the other measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1891-1908
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• 2021

Cyber deception defense mitigates Advanced Persistent Threats (APTs) with deploying deceptive entities, such as the Honeyfile. The Honeyfile distracts attackers from valuable digital documents and attracts unauthorized access by deliberately exposing fake content. The effectiveness of distraction and trap lies in the enticement of fake content. However, existing studies on the Honeyfile focus less on this perspective. In this work, we seek to improve the enticement of fake text content through enhancing its readability, indistinguishability, and believability. Hence, an enticing deceptive-content generator, EDGE, is presented. The EDGE is constructed with three steps: extracting key concepts with a semantics-aware K-means clustering algorithm, searching for candidate deceptive concepts within the Word2Vec model, and generating deceptive text content under the Integrated Readability Index (IR). Furthermore, the readability and believability performance analyses are undertaken. The experimental results show that EDGE generates indistinguishable deceptive text content without decreasing readability. In all, EDGE proves effective to generate enticing deceptive text content as deception defense against APTs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.20-34
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• 2021

Today, IoT devices are flooding, and traffic is increasing rapidly. The Internet of Things creates a variety of added value through connections between devices, while many devices are easily targeted by attackers due to security vulnerabilities. In the IoT environment, security diagnosis has problems such as having to provide different solutions for different types of devices in network situations where various types of devices are interlocked, personal leakage of security solutions themselves, and high cost, etc. To avoid such problems, a TCP-based active scan was presented. However, the TCP-based active scan has limitations that it is difficult to be applied to real-time systems due to long detection times. To complement this, this study uses UDP-based approaches. Specifically, a lightweight active scan algorithm that effectively identifies devices using UPnP protocols (SSDP, MDNS, and MBNS) that are most commonly used by manufacturers is proposed. The experimental results of this study have shown that devices can be distinguished by more than twice the true positive and recall at an average time of 1524 times faster than Nmap, which has a firm position in the field.