• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.600-616
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• 2021

SIMON and SPECK are two families of lightweight block ciphers that have excellent performance on hardware and software platforms. At CRYPTO 2019, Gohr first introduces the differential cryptanalysis based deep learning on round-reduced SPECK32/64, and finally reduces the remaining security of 11-round SPECK32/64 to roughly 38 bits. In this paper, we are committed to evaluating the safety of SIMON cipher under the neural differential cryptanalysis. We firstly prove theoretically that SIMON is a non-Markov cipher, which means that the results based on conventional differential cryptanalysis may be inaccurate. Then we train a residual neural network to get the 7-, 8-, 9-round neural distinguishers for SIMON32/64. To prove the effectiveness for our distinguishers, we perform the distinguishing attack and key-recovery attack against 15-round SIMON32/64. The results show that the real ciphertexts can be distinguished from random ciphertexts with a probability close to 1 only by 2^8.7 chosen-plaintext pairs. For the key-recovery attack, the correct key was recovered with a success rate of 23%, and the data complexity and computation complexity are as low as 2⁸ and 2^20.1 respectively. All the results are better than the existing literature. Furthermore, we briefly discussed the effect of different residual network structures on the training results of neural distinguishers. It is hoped that our findings will provide some reference for future research.

• Cross-Cultural Studies
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• v.26
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• pp.379-404
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• 2012

This study aims to investigate national image of South Korea held by russians. Surveys(based on Free-association Image) and discussion were conducted on LiveJournal (internet blog) with russian netizen. A national image is influenced by a subjective perspective rather than an objective one. Therefore, an image can differ substantially from reality. Futhermore, it takes a long time to change an established image, particularly to a positive image. According to the results, the image of South Korea were dominated by unstable political situations, especially factors related to North Korea. In addition, based on Free-association image, thinking about Korea or Korean, most russians recognize Korea(South) with North Korea. Above all Russians recognize Korea, basing their images on factor of the past or their neighbors-russian korean- or famous Korean brand like Samsung, LG, Hyndai, "Dosirak". Russian netizen did not recognize South Korea as one of leading countries in Asia, paying little attention to South Korea compared to China or Japan. We belive that it is necessary to consider these situations in future efforts to enhance the national image of South Korea.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.55-70
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• 2018

With the diversification of mobile devices, the development of web technologies, and the popularization of the cloud, an internet-centric web OS that is not dependent on devices has become necessary. Chromebooks are mobile devices in the form of convertible laptops featuring a web OS developed by Google. These Web OS mobile devices have advantages of multi-user characteristics of the same device and storage and sharing of data through internet and cloud, but it is easy to collect and analyze evidence from the forensic point of view because of excellent security and easy destruction of evidence not. In this paper, we propose an evidence collection procedure and an analysis method considering the cloud environment by dividing the Chromebook, which is a web OS mobile device popularized in the future, into user and administrator modes.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1361-1384
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• 2018

Recently, Cyber Physical System (CPS) is one of the core technologies for realizing Internet of Things (IoT). The CPS is a new paradigm that seeks to converge the physical and cyber worlds in which we live. However, the CPS suffers from certain CPS issues that could directly threaten our lives, while the CPS environment, including its various layers, is related to on-the-spot threats, making it necessary to study CPS security. Therefore, a survey-based in-depth understanding of the vulnerabilities, threats, and attacks is required of CPS security and privacy for IoT. In this paper, we analyze security issues, threats, and solutions for IoT-CPS, and evaluate the existing researches. The CPS raises a number challenges through current security markets and security issues. The study also addresses the CPS vulnerabilities and attacks and derives challenges. Finally, we recommend solutions for each system of CPS security threats, and discuss ways of resolving potential future issues.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3821-3841
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• 2019

Cloud radio access networks (C-RANs) have been regarded in recent times as a promising concept in future 5G technologies where all DSP processors are moved into a central base band unit (BBU) pool in the cloud, and distributed remote radio heads (RRHs) compress and forward received radio signals from mobile users to the BBUs through radio links. In such dynamic environment, automatic decision-making approaches, such as artificial intelligence based deep reinforcement learning (DRL), become imperative in designing new solutions. In this paper, we propose a generic framework of autonomous cell activation and customized physical resource allocation schemes for energy consumption and QoS optimization in wireless networks. We formulate the problem as fractional power control with bandwidth adaptation and full power control and bandwidth allocation models and set up a Q-learning model to satisfy the QoS requirements of users and to achieve low energy consumption with the minimum number of active RRHs under varying traffic demand and network densities. Extensive simulations are conducted to show the effectiveness of our proposed solution compared to existing schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2838-2858
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• 2019

Traditional channel models for vehicle-to-vehicle (V2V) communication usually assume fixed velocity in static scattering environment. In the realistic scenarios, however, time-variant velocity for V2V results in non-stationary statistical properties of wireless channels. Dynamic scatterers with random velocities and directions have been always utilized to depict the non-stationary statistical properties of the channel. In this paper, a non-stationary geometry-based cooperative scattering channel model is proposed for multiple-input multiple-output (MIMO) V2V communication systems, where a birth-death process is used to capture the appearance and disappearance dynamic properties of moving scatterers that reflect the time-variant time correlation and Doppler spectrum characteristics. Moreover, our model has more straight and concise to study the impact of the vehicular traffic density on channel characteristics and thus avoid complicated procedure in deriving the analytical expressions of the channel parameters and functions. The numerical results validate our analysis and demonstrate that setting important parameters of our model can appropriately build up more purposeful measurement campaigns in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1884-1903
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• 2019

Device-to-Device (D2D) communications can provide proximity based services in the future 5G cellular networks. It allows short range communication in a limited area with the advantages of power saving, high data rate and traffic offloading. However, D2D communications may reuse the licensed channels with cellular communications and potentially result in critical interferences to nearby devices. To control the interference and improve network throughput in overlaid D2D cellular networks, a novel channel assignment approach is proposed in this paper. First, we characterize the performance of devices by using Poisson point process model. Then, we convert the throughput maximization problem into an optimal spectrum allocation problem with signal to interference plus noise ratio constraints and solve it, i.e., assigning appropriate fractions of channels to cellular communications and D2D communications. In order to mitigate the interferences between D2D devices, a cluster-based multi-channel assignment algorithm is proposed. The algorithm first cluster D2D communications into clusters to reduce the problem scale. After that, a multi-channel assignment algorithm is proposed to mitigate critical interferences among nearby devices for each D2D cluster individually. The simulation analysis conforms that the proposed algorithm can greatly increase system throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.912-928
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• 2019

Crowd behavior analysis research has revealed a central role in helping people to find safety hazards or crime optimistic forecast. Thus, it is significant in the future video surveillance systems. Recently, the growing demand for safety monitoring has changed the awareness of video surveillance studies from analysis of individuals behavior to group behavior. Group detection is the process before crowd behavior analysis, which separates scene of individuals in a crowd into respective groups by understanding their complex relations. Most existing studies on group detection are scene-specific. Crowds with various densities, structures, and occlusion of each other are the challenges for group detection in diverse crowded scenes. Therefore, we propose a group detection approach called Collective Interaction Filtering to discover people motion interaction from trajectories. This approach is able to deduce people interaction with the Expectation-Maximization algorithm. The Collective Interaction Filtering approach accurately identifies groups by clustering trajectories in crowds with various densities, structures and occlusion of each other. It also tackles grouping consistency between frames. Experiments on the CUHK Crowd Dataset demonstrate that approach used in this study achieves better than previous methods which leads to latest results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.131-137
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• 2018

People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author's product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user's opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.183-186
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• 2014

Increasingly important user based service on the smart media era, and increasing awareness about the user experience. As the connected Internet information systems increases, one of the problems happening between users and information systems such as Internet shopping-malls, portal sites, and corporate web sites is related with the information privacy concerns issues. Thus, we have reviewed extensive previous studies on information privacy in local and foreign information systems, marketing and other fields. The purpose of this study is to provide future directions of studies on information privacy concerns by analyzing past and recent trends of the studies. By considering these realities, we were conducted review on the influencing factors of information privacy concerns on behavior intention based the online environment. Based on these findings, several theoretical and practical implications were suggested and discussed.