• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.8
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• pp.615-622
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• 2013

Fast and accurate signature extraction is essential to improve the performance of the payload signature-based traffic analysis methods. However the slow manual process in extracting signatures make difficult to deal with the rapidly changing application in current Internet environment. Therefore, in this paper we propose a system automatically generating signatures from ground-truth traffic data. In addition, we improve the efficiency of signature extraction by recognizing the application protocol using a protocol filters and generating signatures automatically according to the application-specific protocol contents. In order to verify the validity of the system proposed in this paper, we compared the signatures automatically generated from our system with the signatures manually created for a few popular applications.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.19-33
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• 2011

The need for application traffic classification becomes important for the effective use of network resources. The header-based identification method uses the header signature {IP address, port number, transport layer protocol TCP/UDP)}extracted from Internet application server to overcome some limitations overhead, payload encryption, etc.) of previous methods. A lots signature is extracted because this method uses header information of server. So, we need a maintenance method to keep essential signatures. In this paper, we represent the signature maintenance method using properties of identified traffic and history of the signature. Also, we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1234-1244
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• 2009

Nowadays, the traffic type and behavior are extremely diverse due to the appearance of various services and applications on Internet, which makes the need of application-level traffic classification important for the efficient management and control of network resources. Although lots of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in terms of accuracy and completeness. In this paper we propose an application traffic classification method using statistic signatures, defined as a directional sequence of packet size in a flow, which is unique for each application. The statistic signatures of each application are collected by our automatic grouping and extracting mechanism which is mainly described in this paper. By matching to the statistic signatures we can easily and quickly identify the application name of traffic flows with high accuracy, which is also shown by comprehensive excrement with our campus traffic data.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.16
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• pp.331-359
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• 2001

Uniform Electronic Transactions Act (1999) Drafted by the National Conference of Commissioners on Uniform State Laws. The Act allows the use of electronic records and electronic signatures in any transaction, except transactions subject to the Uniform Commercial Code. The fundamental purpose of this act is to remove perceived barriers to electronic commerce. The Act's a procedural statute. It does not mandate either electronic signatures or records, but provides a means to effectuate transactions when they are used. The primary objective is to establish the legal equivalence of electronic records and signatures with paper writings and manually-signed signatures. With regard to the general scope of the Act, the Act's coverage is inherently limited by the definition of "transaction." The Act does not apply to all writings and signatures, but only to electronic records and signatures relating to a transaction, defined as those interactions between people relating to business, commercial and governmental affairs. The exclusion of specific Articles of the Uniform Commercial Code reflects the recognition that, particularly in the case of Articles 5, 8 and revised Article 9, electronic transactions were addressed in the specific contexts of those revision processes. In the context of Articles 2 and 2A the UETA provides the vehicle for assuring that such transactions may be accomplished and effected via an electronic medium. At such time as Articles 2 and 2A are revised the extent of coverage in those Articles(Acts) may make application of this Act as a gap-filling law desirable. Similar considerations apply to the recently promulgated Uniform Computer Information Transactions Act (UCITA). Another fundamental premise of the Act is that it be minimalist and procedural. The general efficacy of existing law, in an electronic context, so long as biases and barriers to the medium are removed, confirms this approach. The Act defers to existing substantive law. Specific areas of deference to other law in this Act include: i) the meaning and effect of "sign" under existing law, ii) the method and manner of displaying, transmitting and formatting information in section 8, iii) rules of attribution in section 9, and iv) the law of mistake in section 10.

• Molecules and Cells
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• v.42 no.3
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• pp.237-244
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• 2019

Understanding the mechanisms of cancer drug resistance is a critical challenge in cancer therapy. For many cancer drugs, various resistance mechanisms have been identified such as target alteration, alternative signaling pathways, epithelial-mesenchymal transition, and epigenetic modulation. Resistance may arise via multiple mechanisms even for a single drug, making it necessary to investigate multiple independent models for comprehensive understanding and therapeutic application. In particular, we hypothesize that different resistance processes result in distinct gene expression changes. Here, we present a web-based database, CDRgator (Cancer Drug Resistance navigator) for comparative analysis of gene expression signatures of cancer drug resistance. Resistance signatures were extracted from two different types of datasets. First, resistance signatures were extracted from transcriptomic profiles of cancer cells or patient samples and their resistance-induced counterparts for >30 cancer drugs. Second, drug resistance group signatures were also extracted from two large-scale drug sensitivity datasets representing ~1,000 cancer cell lines. All the datasets are available for download, and are conveniently accessible based on drug class and cancer type, along with analytic features such as clustering analysis, multidimensional scaling, and pathway analysis. CDRgator allows meta-analysis of independent resistance models for more comprehensive understanding of drug-resistance mechanisms that is difficult to accomplish with individual datasets alone (database URL: http://cdrgator.ewha.ac.kr).

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.330-336
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• 2022

This paper proposes a method to calibrate the electrode misplacement in underwater electric field sensor arrays (EFSAs) for accurate measurements of underwater electric field signatures. The electrode misplacement of an EFSA was estimated by measuring the electric field signatures generated by a known electric source and by comparing the measurements with the theoretical calculations under similar measurement conditions. When the EFSA measured the electric field signatures induced by an unknown electric source, the electric properties of the unknown electric source were approximated by considering the optimized estimation of the electrode misplacement of the EFSA. Finally, the measured electric field signatures were calibrated by calculating the theoretical electric field signatures to be measured with an ideally installed EFSA without electrode misplacement; the approximated electric properties of the unknown electric source were also taken into account. Simulations were conducted to test the proposed calibration method. The results showed that the electrode misplacement could be estimated. Further, the electric field measurements and the electric field-based localization of underwater vessels became more accurate after the application of the proposed calibration method. The proposed method will contribute to applications such as the detection and localization of underwater electric sources, which require accurate measurements of underwater electric field signatures.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.674-679
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• 1994

Acoustic signal such as speech and scattered sound, are generally a nonstationary process whose frequency contents vary at any instant of time. For time-varying signal, whether a nonstationary or a deterministic transient signal, a traditional frequency domain representation does not reveal the contents of signal characteristics and may lead to erroneous results such as the loss of desired characteristics features or the mis-interpretation for a wrong conclusion. A time-frequency domain representation is needed to characterize such signatures. Pseudo Wigner-Ville distribution (PWVD) is ideally suited for portraying nonstationary signal time-frequency domain and carried out by adapting the fast Fourier transform algorithm. In this paper, the important properties of PWVD were investigated using both stationary and nonstationry signatures by numerical examples PWVD was applied to acoustic sigtnatures to demonstrate its application for time-ferquency domain analysis.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.719-731
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• 2021

This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.

• The KIPS Transactions:PartC
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• v.17C no.1
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• pp.99-108
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• 2010

The traffic classification is a preliminary but essentialstep for stable network service provision and efficient network resource management. While various classification methods have been introduced in literature, the payload signature-based classification is accepted to give the highest performance in terms of accuracy, completeness, and practicality. However, the collection and maintenance of up-to-date signatures is very difficult and time consuming process to cope with the dynamics of Internet traffic over time. In this paper, We propose an automatic payload signature generation mechanism which reduces the time for signature generation and increases the granularity of signatures. Furthermore, We describe a signature update system to keep the latest signatures over time. By experiments with our campus network traffic we proved the feasibility of our mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1572-1593
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• 2018

The diversity and fast growth of Internet traffic volume are highly influenced by mobile and computer applications being developed. Moreover, the developed applications are too dynamic to be identified and monitored by network administrators. Several approaches have been proposed to identify network applications, however, are still not robust enough to identify modern applications. This paper proposes both, TSA (Traffic collection, Signature generation and Applications identification) system and a derived algorithm so called CSP (Contiguous Sequential Patterns) to identify applications for management and security in IP networks. The major focus of this paper is the CSP algorithm which is automated in two modules (Signature generation and Applications identification) of the proposed system. The proposed CSP algorithm generates DNA-like unique signatures capable of identifying applications and their individual services. In this paper, we show that the algorithm is suitable for generating efficient signatures to identify applications and application services in high accuracy.