• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.4157-4175
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• 2020

Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1145-1157
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• 2020

A convolution neural networks (CNNs) has demonstrated outstanding performance compared to other algorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers have proposed a residual network to ease the training for recognition accuracy improvement. In this study, a novel face recognition model based on game theory for call-over in the classroom was proposed. In the proposed scheme, an image with multiple faces was used as input, and the residual network identified each face with a confidence score to form a list of student identities. Face tracking of the same identity or low confidence were determined to be the optimisation objective, with the game participants set formed from the student identity list. Game theory optimises the authentication strategy according to the confidence value and identity set to improve recognition accuracy. We observed that there exists an optimal mapping relation between face and identity to avoid multiple faces associated with one identity in the proposed scheme and that the proposed game-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.

• The Journal of Information Systems
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• 제29권2호
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• pp.149-171
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• 2020

Purpose With the advent of the 4th Industrial Revolution, related technologies such as IoT, big data, and artificial intelligence technologies are developing through not only specific companies but also a number of unspecified developers called open collaboration. For this reason, it is important to understand the nature of the collaboration that leads to successful open collaboration. Design/methodology/approach We focused the relationship between the collaboration characteristics and collaboration performance of developers who participating in open source software development, which is a representative open collaboration. Specifically, we create the country-specific network and draw the individual developers characteristics from the network such as collaboration scope and collaboration intensity. We compare and analyze the characteristics of developers across countries and explore whether there are differences between indicators. We develop a Web crawler for GitHub, a representative OSSD development site, and collected data of developers who located at China, Japan, Korea, the United States, and Canada. Findings China showed the characteristics of cooperation suitable for the form of weak tie theory, and consistent results were not drawn from other countries. This study confirmed the necessity of exploratory research on collaboration characteristics by country considering that there are differences in open collaboration characteristics or software development environments by country.

• The Transactions of the Korea Information Processing Society
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• 제4권11호
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• pp.2780-2785
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• 1997

Although KBANN(knowledge-based artificial neural network) has been shown to be more effective than other machine learning algorithms, KBANN doesn't have the theory refinement capability because the topology of the network can't be altered dynamically. Although TopGen algorithm was proposed to extend the ability of KABNN in this respect, it also had some defects due to the connection of hidden nodes from all input nodes and the use of beam search. An algorithm, which could solve this TopGen's defects by adding the hidden nodes connected from only related input nodes and using hill-climbing search with backtracking, is proposed.

• Journal of Platform Technology
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• 제9권1호
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• pp.3-14
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• 2021

Cognitive Radio network (CR) is a promising paradigm that helps the unlicensed user (Secondary User) to analyse the spectrum and coordinate the spectrum access to support the creation of common control channel (CCC). The cooperation of secondary users and broadcasting between them is done through transmitting messages in CCC. In case, if the control channels may get jammed and it may directly degrade the network's performance and under such scenario jammers will devastate the control channels. Hopping sequences may be one of the predominant approaches and it may be used to fight against this problem to confront jammer. The jamming attack can be alleviated using one of the game modelling approach and in this proposed scheme stochastic games has been analysed with more single users to provide the flexible control channels against intrusive attacks by mentioning the states of each player, strategies ,actions and players reward. The proposed work uses a modern player action and better strategic view on game theoretic modelling is stochastic game theory has been taken in to consideration and applied to prevent the jamming attack in CR network. The selection of decision is based on Q learning approach to mitigate the jamming nodes using the optimal MDP decision process

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• Journal of the Korean Society for Precision Engineering
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• 제21권11호
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• pp.31-37
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• 2004

• International Journal of Internet, Broadcasting and Communication
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• 제4권2호
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• pp.22-27
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• 2012

The design characteristics of circular vertical-cavity surface-emitting lasers are studied by using a newly developed equivalent network. Optical parameters, such as the stop-band or the reflectivity of periodic mirrors and the resonance wavelength, are explored for the design of these structures. To evaluate the differential quantum efficiency and the threshold current density, a transverse resonance condition of modal transmission-line theory is also utilized. This approach dramatically reduces the computational time as well as gives an explicit insight to explore the optical characteristics of circular vertical-cavity surface-emitting lasers (VCSELs).

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• Proceedings of the KIEE Conference
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.2959-2961
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• 1999

A position control algorithm for a inverted pendulum is studied. The proposed algorithm is based on a fuzzy theory and Generalized Radial Basis Function(GRBF). The conventional fuzzy methods need expert's knowledges or human experiences. The GRBF, which is an optimization algorithm, tunes automatically the input-output membership parameters and fuzzy rules. The simulation is presented to illustrate the approaches.