• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.891-900
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• 2015

Cloud Computing has recently begun to emerge as a new attack target. The malice DDoS attacks are ongoing to delay and disturb the various services of the Cloud Computing. In this paper, we propose the Hornet-Cloud using security Honeypot technique and resources of Cloud Computing, and design the concept of active-interaction and security functions of Hornet-Cloud simply.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.49-55
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• 2012

Recently, with the rapid development of android-based smartphones, it is becomes a major security issue that the case of Android platform is an open platform. so it is easy to be a target of mobile virus penetration and hacking. Even there are a variety of security mechanisms to prevent the vulnerable points of the Android platform but the reason of most of the security mechanisms were designed at application-level that highly vulnerable to the attacks directly to the operating system or attacks using the disadvantages of an application's. It is necessary that the complementary of the android platform kernel blocks the kernel vulnerability and the application vulnerability. In this paper, we proposed a secure system using linux-based android kernel applied to LIDS(Linux Intrusion Detection and Defense System) and applied a smart phone with s5pc110 chip. As a result, the unauthorized alteration of the application was prevented with a proposed secure system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.545-558
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• 2020

The gaze-based input provides feedback to confirm that the typing is correct when the user types the text. Many studies have already demonstrated that feedback can increase the usability of gaze-based inputs. However, because the information of the typed text is revealed through feedback, it can be a target for shoulder-surfing attacks. Appropriate feedback needs to be used to improve security without compromising the usability of the gaze-based input using the original feedback. In this paper, we propose a new gaze-based input method, FFI(Fake Flickering Interface), to resist shoulder-surfing attacks. Through experiments and questionnaires, we evaluated the usability and security of the FFI compared to the gaze-based input using the original feedback.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.1-6
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• 2019

As the value of technical information increases, hacking attacks are trying to steal technical information through hacking. Recently, hacking of cryptocurrency exchanges is much easier to monetize than existing technical information, making it a major attack target for hackers. In the case of technical information, it is required to seize the technical information and sell it to the black market for cashing.In the case of cryptocurrency, most hacking attacks are concentrated on cryptocurrency exchanges because it is easy to cash out and not easy to track when successful hacking. Although technology cannot be hacked, cryptocurrency transactions traded on cryptocurrency exchanges are not recorded on the blockchain which is simply internal exchanges, so insiders may manipulate the quotes and leave gaps or leak out. Therefore, this research analyzes the recent hacking attacks of cryptocurrency exchanges and proposes solutions to secure cryptocurrency trading.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.83-92
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• 2017

Reconnaissance is performed gathering information from a series of scanning probes where the objective is to identify attributes of target hosts. Network reconnaissance of IP addresses and ports is prerequisite to various cyber attacks. In order to increase the attacker's workload and to break the attack kill chain, a few proactive techniques based on the network-based moving target defense (NMTD) paradigm, referred to as IP address mutation/randomization, have been presented. However, there are no commercial or trial systems deployed in real networks. In this paper, we propose a threat model and the request for requirements for developing NMTD techniques. For this purpose, we first examine the challenging problems in the NMTD mechanisms that were proposed for the legacy TCP/IP network. Secondly, we present a threat model in terms of attacker's intelligence, the intended information scope, and the attacker's location. Lastly, we provide seven basic requirements to develop an NMTD mechanism for the legacy TCP/IP network: 1) end-host address mutation, 2) post tracking, 3) address mutation unit, 4) service transparency, 5) name and address access, 6) adaptive defense, and 7) controller operation. We believe that this paper gives some insight into how to design and implement a new NMTD mechanism that would be deployable in real network.

• Korean Security Journal
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• no.49
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• pp.157-183
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• 2016

Countries across the globe, including those in Europe, are waging a "war against terrorism" as international terrorist groups such as ISIS and lone-wolf terrorists have unleashed various large-scale attacks on rail infrastructure. Anti-South Korean sentiment exists in Muslim-majority countries because the nation has cooperated with the US for its military interventions in the Middle East, and ISIS has threatened to target South Korea four times since September 9, 2015. In addition, North Korea has been left isolated in the international community with its missile and nuclear tests, while further escalating inter-Korean tension and threatening to strike major facilities and attack important figures in the South. These situations imply that South Korea is no longer immune to terrorist attacks. If the nation fails to prevent or deter such terrorist attacks against rail networks, massive casualties, property damage and social confusion would be unavoidable, deteriorating national and international trust in its counter-terrorism policies. This may lead to a national crisis involving decreases in the number of tourists, dampened interest of foreign investors, and capital flight. This study aims to propose policy measures to enhance railroad security checks, based on the work of railroad police officers, for the sake of protecting citizens and public safety. The suggestions include an incremental expansion of railroad security checks; growth of the railroad police force and adjustment of their policing distribution with other police officers; enhancement of security systems across important rail networks; improvement of the Railroad Safety Act; Southeast Asia, including the corresponding strengthening of the national crackdown illegal immigrants, and plans for pre-emptive and regular cooperation among organizations related to the promotion of security checks and the prevention of terrorist attacks.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.145-153
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• 2014

The improvements of embedded processors make future technologies including wireless sensor network and internet of things feasible. These applications firstly gather information from target field through wireless network. However, this networking process is highly vulnerable to malicious attacks including eavesdropping and forgery. In order to ensure secure and robust networking, information should be kept in secret with cryptography. Well known approach is public key cryptography and this algorithm consists of finite field arithmetic. There are many works considering high speed finite field arithmetic. One of the famous approach is Montgomery multiplication. In this study, we investigated Montgomery multiplication for public key cryptography on embedded microprocessors. This paper includes helpful information on Montgomery multiplication implementation methods and techniques for various target devices including 8-bit and 16-bit microprocessors. Further, we expect that the results reported in this paper will become part of a reference book for advanced Montgomery multiplication methods for future researchers.

• Convergence Security Journal
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• v.21 no.1
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• pp.93-100
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• 2021

Damage caused by intelligent cyber attacks not only disrupts system operations and leaks information, but also entails massive economic damage. Recently, cyber attacks have a distinct goal and use advanced attack tools and techniques to accurately infiltrate the target. In order to minimize the damage caused by such an intelligent cyber attack, it is necessary to block the cyber attack at the beginning or during the attack to prevent it from invading the target's core system. Recently, technologies for predicting cyber attack paths and analyzing risk level of cyber attack using big data or artificial intelligence technologies are being studied. In this paper, a cyber attack path analysis method using attack tree and RFI is proposed as a basic algorithm for the development of an automated cyber attack path prediction system. The attack path is visualized using the attack tree, and the priority of the path that can move to the next step is determined using the RFI technique in each attack step. Based on the proposed mechanism, it can contribute to the development of an automated cyber attack path prediction system using big data and deep learning technology.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.975-986
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• 2022

Deep learning is attracting great attention, showing excellent performance in image processing, but is vulnerable to adversarial attacks that cause the model to misclassify through perturbation on input data. Adversarial examples generated by adversarial attacks are minimally perturbated where it is difficult to identify, so visual features of the images are not generally changed. Unlikely deep learning models, people are not fooled by adversarial examples, because they classify the images based on such visual features of images. This paper proposes adversarial attack detection method using Symbolic Representation, which is a visual and symbolic features such as color, shape of the image. We detect a adversarial examples by comparing the converted Symbolic Representation from the classification results for the input image and Symbolic Representation extracted from the input images. As a result of measuring performance on adversarial examples by various attack method, detection rates differed depending on attack targets and methods, but was up to 99.02% for specific target attack.