• Journal of Internet Computing and Services
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• v.2 no.4
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• pp.41-53
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• 2001

Multi-distributed web cluster model built for high availability E-Business model exposes internal system nodes on its structural characteristics and has a potential that normal job performance is impossible due to the intentional prevention and attack by an illegal third party. Therefore, the security system which protects the structured system nodes and can correspond to the outflow of information from illegal users and unfair service requirements effectively is needed. Therefore the suggested distributed invasion detection system is the technology which detects the illegal requirement or resource access of system node distributed on open network through organic control between SC-Agents based on the shared memory of SC-Server. Distributed invasion detection system performs the examination of job requirement packet using Detection Agent primarily for detecting illegal invasion, observes the job process through monitoring agent when job is progressed and then judges the invasion through close cooperative works with other system nodes when there is access or demand of resource not permitted.

• Convergence Security Journal
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• v.13 no.4
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• pp.101-108
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• 2013

Sensor network configurations are for a specific situation or environment sensors capable of sensing, processing the collected information processors, and as a device is transmitting or receiving data. It is presently serious that sensor networks provide many benefits, but can not solve the wireless network security vulnerabilities, the risk of exposure to a variety of state information. u-Healthcare sensor networks, the smaller the sensor node power consumption, and computing power, memory, etc. restrictions imposing, wireless sensing through the kind of features that deliver value, so it ispossible that eavesdropping, denial of service, attack, routing path. In this paper, with a focus on sensing of the environment u-Healthcare system wireless security vulnerabilities factors u-Healthcare security framework to diagnose and design methods are presented. Sensor network technologies take measures for security vulnerabilities, but without the development of technology, if technology is not being utilized properly it will be an element of threat. Studies suggest that the u-Healthcare System in a variety of security risks measures user protection in the field of health information will be used as an important guide.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.939-946
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• 2011

The Internet banking service provides convenience than the traditional offline services. However, it still causes a number of security problems including hacking. In order to strengthen security, the financial institutions have provided such authentication methods as the official authentication certificate, the security token, the security card and OTP. However, the incidents related to hacking have continuously occurred. Especially, various weak points have been suggested for the authentication methods in regard to such types of hacking as the memory hacking or the MITM attack. So I needed was a new authentication method. In this study, the two-channel authentication method which provide two-way authentication on the user's PC and mobile device when executing the electronic financial transactions in the Internet banking environment is suggested. Also, by analyzing it in comparison with other existing methods, it is possible to check that the prospects of safety and credibility are strengthened.

• Journal of English Language & Literature
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• v.57 no.1
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• pp.107-127
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• 2011

Don DeLillo has shown considerable interest in terror, frequently depicting extreme dread of something terrible to happen, in his literary texts. Since more than three thousand innocent people in New York were killed by the 9-11 terrorist attack in 2001, the anticipation about what kind of fiction he would write as a New Yorker was high. DeLillo's novel Falling Man (2007) in fragmentary detail represents the scene of the terrorism from the perspective of Keith Neudecker, a lawyer who escapes the collapsing world trader center. Neudecker's post-traumatic stress disorder in the first chapter is followed by the free-associative portrayal of various impacts of the 9-11 terror on Neudecker's wife Lienne in the second chapter. The random mixture of the first person narratives from such diverse view-point characters as Neudecker's son Justin, relatives and friends, with dialogues and recollections yields a very close picture of the consequences of terrorism. Reading DeLillo's Falling Man in juxtaposition with a Japanese Canadian novel Obasan by Joy Kogawa, reminiscences of the maltreatment of Japanese Canadians during and after the second world war, surfaces the authorial intention of the two novels. They as trauma literature emerge to aim at curing the readers and proposing post-traumatic ethics. Laurie Vickroy's theory of trauma narrative and cure, E. Ann Kaplan's theory of trauma witness narrative and responsibility, and Emmanuel Levinas's theory of trauma memory and ethics offer theoretical grounds for the convincing analysis of the two texts.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.35-44
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• 2011

The PP-1/64-128 block cipher support variety data block and secret key size. Also, it is suitable for hardware implementation and can much easier to apply Concurrent Error Detection(CED) for cryptographic chips compared to other block ciphers, because it has same encryption and decryption process. In this paper, we proposed truncated differential cryptanalysis of PP-1/64-128. the attack on PP-1/64-128 block cipher requires $2^{50.16}$ chosen plaintexts, $2^{46.16}$ bytes memory spaces and $2^{50.45}$ PP-1/64-128 encryption to retrieve secret key. This is the best result of currently known PP-1/64-128 differential cryptanalysis.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.101-108
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• 2022

We propose an intrusion detection model that detects denial-of-service(DoS) and distributed reflection denial-of-service(DRDoS) attacks, based on the empirical data of each internet of things(IoT) device by training system and network metrics that can be commonly collected from various IoT devices. First, we collect 37 system and network metrics from each IoT device considering IoT attack scenarios; further, we train them using six types of machine learning models to identify the most effective machine learning models as well as important metrics in detecting and distinguishing IoT attacks. Our experimental results show that the Random Forest model has the best performance with accuracy of over 96%, followed by the K-Nearest Neighbor model and Decision Tree model. Of the 37 metrics, we identified five types of CPU, memory, and network metrics that best imply the characteristics of the attacks in all the experimental scenarios. Furthermore, we found out that packets with higher transmission speeds than larger size packets represent the characteristics of DoS and DRDoS attacks more clearly in IoT networks.

• Convergence Security Journal
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• v.23 no.3
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• pp.37-47
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• 2023

The growth of the metaverse has been accelerated by the increased demand for non-face-to-face interactions due to COVID-19 and advancements in technologies such as blockchain and NFTs. However, with the emergence of various metaverse platforms and the corresponding rise in users, criminal cases such as ransomware attacks, copyright infringements, and sexual offenses have occurred within the metaverse. Consequently, the need for artifacts that can be utilized as digital evidence within metaverse systems has increased. However, there is a lack of information about artifacts that can be used as digital evidence. Furthermore, metaverse security evaluation and forensic analysis are also insufficient, and the absence of attack scenarios and related guidelines makes forensics challenging. To address these issues, this paper presents artifacts that can be used for user behavior analysis and timeline analysis through dynamic analysis of Roblox, a representative metaverse gaming solution. Based on analyzing interrelationship between identified artifacts through memory forensics and log file analysis, this paper suggests the potential usability of artifacts in metaverse crime scenarios. Moreover, it proposes improvements by analyzing the current legal and regulatory aspects to address institutional deficiencies.

• Safety and Health at Work
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• v.11 no.2
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• pp.178-186
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• 2020

Background: Cognitive impairment is a public health burden. Our objective was to investigate associations between work hours and cognitive function. Methods: Multi-Ethnic Study of Atherosclerosis (MESA) participants (n = 2,497; 50.7% men; age range 44-84 years) reported hours per week worked in all jobs in Exams 1 (2000-2002), 2 (2002-2004), 3 (2004-2005), and 5 (2010-2011). Cognitive function was assessed (Exam 5) using the Cognitive Abilities Screening Instrument (version 2), a measure of global cognitive functioning; the Digit Symbol Coding, a measure of processing speed; and the Digit Span test, a measure of attention and working memory. We used a prospective approach and linear regression to assess associations for every 10 hours of work. Results: Among all participants, associations of hours worked with cognitive function of any type were not statistically significant. In occupation-stratified analyses (interaction p = 0.051), longer work hours were associated with poorer global cognitive function among Sales/Office and blue-collar workers, after adjustment for age, sex, physical activity, body mass index, race/ethnicity, educational level, annual income, history of heart attack, diabetes, apolipoprotein E-epsilon 4 allele (ApoE4) status, birth-place, number of years in the United States, language spoken at MESA Exam 1, and work hours at Exam 5 (β = -0.55, 95% CI = -0.99, -0.09) and (β = -0.80, -1.51, -0.09), respectively. In occupation-stratified analyses (interaction p = 0.040), we also observed an inverse association with processing speed among blue-collar workers (adjusted β = -0.80, -1.52, -0.07). Sex, race/ethnicity, and ApoE4 did not significantly modify associations between work hours and cognitive function. Conclusion: Weak inverse associations were observed between work hours and cognitive function among Sales/Office and blue-collar workers.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.683-694
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• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.