• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.141-145
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• 2008

Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.156-163
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• 2004

In this paper, we propose an adaptive face region detection and real-time face identification algorithm using face feature evaluation function. The proposed algorithm can detect exact face region adaptively by using skin color information for races as well as intensity and elliptical masking method. And also, it improves face recognition efficiency using geometrical face feature and geometric evaluation function between features. The proposed algorithm can be used for the development of biometric and security system areas. In the experiment, the superiority of the proposed method has been tested using real image, the proposed algorithm shows more improved recognition efficiency as well as face region detection efficiency than conventional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5156-5161
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• 2013

In distributed spatial data stream processing, processed tuples of downstream nodes are replicated to the upstream node in order to increase the utilization of distributed nodes and to recover the whole system for the case of system failure. However, while the data input rate increases and multiple downstream nodes share the operation result of the upstream node, the data which stores to output queues as a backup can be lost since the deletion operation delay may be occurred by the delay of the tuple processing of upstream node. In this paper, the adaptive upstream backup scheme based on operation throughput in distributed spatial data stream system is proposed. This method can cut down the average load rate of nodes by efficient spatial operation migration as it processes spatial temporal data stream, and it can minimize the data loss by fluid change of backup mode. The experiments show the proposed approach can prevent data loss and can decrease, on average, 20% of CPU utilization by node monitoring.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.673-681
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• 2005

As it is the most important to make sure security and reliability for nuclear Power Plant, it's considered the most crucial issues to develop a fault detective and diagnostic system in spite of multiple hardware redundancy in itself. To develop an algorithm for a fault diagnosis in the nuclear PWR steam generator, this paper proposes a method based on ART2(adaptive resonance theory 2) neural network that senses and classifies troubles occurred in the system. The fault diagnosis system consists of fault detective part to sense occurred troubles, parameter estimation part to identify changed system parameters and fault classification part to understand types of troubles occurred. The fault classification part Is composed of a fault classifier that uses ART2 neural network. The Performance of the proposed fault diagnosis a18orithm was corroborated by applying in the steam generator.

• The KIPS Transactions:PartC
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• v.16C no.2
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• pp.151-164
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• 2009

The importance of sensor networks as a base of ubiquitous computing realization is being highlighted, and espicially the security is recognized as an important research isuue, because of their characteristics.Several efforts are underway to provide security services in sensor networks, but most of them are preventive approaches based on cryptography. However, sensor nodes are extremely vulnerable to capture or key compromise. To ensure the security of the network, it is critical to develop security Intrusion Detection System (IDS) that can survive malicious attacks from "insiders" who have access to keying materials or the full control of some nodes, taking their charateristics into consideration. In this perper, we design a distributed and adaptive IDS architecture on sensor networks, respecting both of energy efficiency and IDS efficiency. Utilizing a modified HEED algorithm, a clustering algorithm, distributed IDS nodes (dIDS) are selected according to node's residual energy and degree. Then the monitoring results of dIDSswith detection codes are transferred to dIDSs in next round, in order to perform consecutive and integrated IDS process and urgent report are sent through high priority messages. With the simulation we show that the superiorities of our architecture in the the efficiency, overhead, and detection capability view, in comparison with a recent existent research, adaptive IDS.

• Convergence Security Journal
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• v.24 no.3
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• pp.95-104
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• 2024

The performance capability of the future battlefield depends on whether the next-generation technology of the Fourth Industrial Revolution, called ABCMS (AI, Bigdata, Cloud, Mobile, Security), can be applied to secure innovative defense capabilities It is no exaggeration to say. In addition, the future military operation environment is rapidly changing into a net work-oriented war (NCW) in which all weapon systems mutually share battlefield information and operate in real-time within a single integrated information and communication network based on the network and is expanding to the scope of operation of the manned and unmanned complex combat system. In particular, communication networks responsible for high-speed and hyperconnectivity require high viability and efficiency in power operation based on multi-tier (defense mobile, satellite, M/W, wired) networks for the connection of multiple combat elements and smooth distribution of information. From this point of view, this study is different from conventional single-media, single-path transmission with fixed specifications, It is an artificial intelligence-based transmission technology using RNN (Recurrent Neural Networks) algorithm and load distribution during traffic congestion using available communication wired and wireless infrastructure multimedia simultaneously and It is the development of MMMP-Multi-Media Multi-Path adaptive network technology.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.9-17
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• 2007

Super-distribution is essential for revitalization of digital contents industry in DRM system. Since existing DRM systems emphasize on security for intellectual property rights, it became restrictions to content distribution and the consumer rights. This paper suggests license management mechanism which strengthen super-distribution between consumers. It is to manage distribution history for each content by inserting consumer's identification information in content head. Client can verify security by comparing header and license after issuing license. It classifies the type of distribution and license, and then applies adaptive distribution methods. It can revitalize contents distribution by releasing proper license for super-distribution.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.91-100
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• 2022

To support early intervention, it is necessary to develop programming system tools that enable accurate, valid, and reliable assessments and can help achieve reasonable, generalizable, and measurable goals. This study examined the Assessment, Evaluation, and Programming System (AEPS) used by associations of children with disabilities in Saudi Arabia to assess its suitability for children with intellectual disabilities. A group of 16 specialists with different professional backgrounds (including special education, physiotherapy, occupational therapy, speech therapy and psychology) from 11 associations of children with disabilities took part in semi-structured personal interviews. The study concluded that AEPS is generally suited for use with children with intellectual disabilities. However, its suitability depends on the type and severity of the child's disability. The more severe the disability, the less effective the AEPS is likely to be. On the basis of this finding the researchers formed interdisciplinary teams to organise and integrate the children's learning and assess the benefits of AEPS, including its accuracy and ability to achieve adaptive, cognitive, and social targets, enhance family engagement and learning and develop basic development skills. This study also identified obstacles associated with the use of AEPS. These include the lack of comprehensiveness and accuracy of the goal, lack of precision and non-applicability to large movements and the fact that it cannot be used with all children with intellectual disabilities. In addition, the research showed that non-cooperation within the family is a major obstacle to the implementation of the AEPS. The results of this study have several implications.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1859-1862
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• 2003

Security of digital images attracts much attention recently, and many image encryption methods have been proposed. This paper proposed an image encryption methodology to hide the image information. The target data of it is the result from quantization in the wavelet domain. This method encrypts only part of the image data rather than the whole data of the original image. For ciphering the quantization index we use a novel image encryption Algorithm called BRIE(Bit Recirculation Image Encryption). which was proposed by J. C. Yen and J. I. Guo in 1999. According to a chaotic binary sequence generated by BRIE, the block which is produced by quantization index is cyclically shifted in the right or left direction. Finally, simulation results are included to demonstrate its effectiveness.