• Title/Summary/Keyword: Signed Networks

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Link Prediction Algorithm for Signed Social Networks Based on Local and Global Tightness

  • Liu, Miao-Miao;Hu, Qing-Cui;Guo, Jing-Feng;Chen, Jing
    • Journal of Information Processing Systems
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    • v.17 no.2
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    • pp.213-226
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    • 2021
  • Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.

An Empirical Study of Absolute-Fairness Maximal Balanced Cliques Detection Based on Signed Attribute Social Networks: Considering Fairness and Balance

  • Yixuan Yang;Sony Peng;Doo-Soon Park;Hye-Jung Lee;Phonexay Vilakone
    • Journal of Information Processing Systems
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    • v.20 no.2
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    • pp.200-214
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    • 2024
  • Amid the flood of data, social network analysis is beneficial in searching for its hidden context and verifying several pieces of information. This can be used for detecting the spread model of infectious diseases, methods of preventing infectious diseases, mining of small groups and so forth. In addition, community detection is the most studied topic in social network analysis using graph analysis methods. The objective of this study is to examine signed attributed social networks and identify the maximal balanced cliques that are both absolute and fair. In the same vein, the purpose is to ensure fairness in complex networks, overcome the "information cocoon" bottleneck, and reduce the occurrence of "group polarization" in social networks. Meanwhile, an empirical study is presented in the experimental section, which uses the personal information of 77 employees of a research company and the trust relationships at the professional level between employees to mine some small groups with the possibility of "group polarization." Finally, the study provides suggestions for managers of the company to align and group new work teams in an organization.

On Finding the Maximum Capacity Flow in Networks

  • Lee, Chong-Hyung;Park, Dong-Ho;Lee, Seung-Min
    • Proceedings of the Korean Reliability Society Conference
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    • 2002.06a
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    • pp.297-302
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    • 2002
  • An efficient method is developed to obtain the maximum capacity flow for a network when its simple paths are known. Most of the existing techniques need to convert simple paths into minimal cuts, or to determine the order of simple paths to be applied in the process to reach the correct result. In this paper, we propose a method based on the concepts of signed simple path and signed flow defined in the text. Our method involves a fewer number of arithmetic operations at each iteration, and requires fewer iterations in the whole process than the existing methods. Our method can be easily extended to a mixed network with a slight modification. Furthermore, the correctness of our method does not depend on the order of simple paths to be applied in the process.

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Absolute-Fair Maximal Balanced Cliques Detection in Signed Attributed Social Network (서명된 속성 소셜 네트워크에서의 Absolute-Fair Maximal Balanced Cliques 탐색)

  • Yang, Yixuan;Peng, Sony;Park, Doo-Soon;Lee, HyeJung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.9-11
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    • 2022
  • Community detection is a hot topic in social network analysis, and many existing studies use graph theory analysis methods to detect communities. This paper focuses on detecting absolute fair maximal balanced cliques in signed attributed social networks, which can satisfy ensuring the fairness of complex networks and break the bottleneck of the "information cocoon".

Detection of Maximal Balance Clique Using Three-way Concept Lattice

  • Yixuan Yang;Doo-Soon Park;Fei Hao;Sony Peng;Hyejung Lee;Min-Pyo Hong
    • Journal of Information Processing Systems
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    • v.19 no.2
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    • pp.189-202
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    • 2023
  • In the era marked by information inundation, social network analysis is the most important part of big data analysis, with clique detection being a key technology in social network mining. Also, detecting maximal balance clique in signed networks with positive and negative relationships is essential. In this paper, we present two algorithms. The first one is an algorithm, MCDA1, that detects the maximal balance clique using the improved three-way concept lattice algorithm and object-induced three-way concept lattice (OE-concept). The second one is an improved formal concept analysis algorithm, MCDA2, that improves the efficiency of memory. Additionally, we tested the execution time of our proposed method with four real-world datasets.

DEFECT INSPECTION IN SEMICONDUCTOR IMAGES USING HISTOGRAM FITTING AND NEURAL NETWORKS

  • JINKYU, YU;SONGHEE, HAN;CHANG-OCK, LEE
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.26 no.4
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    • pp.263-279
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    • 2022
  • This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods.

Analysis of Sign Prediction Accuracy with Signed Graph Convolutional Network Methods in Sparse Networks (희소한 네트워크에서 부호가 있는 그래프 합성곱 네트워크 방법들의 부호 예측 정확도 분석)

  • Min-Jeong Kim;Yeon-Chang Lee;Sang-Wook Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.468-469
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    • 2023
  • 실세계 네트워크 데이터에서 노드들 간의 관계는 종종 친구/적 혹은 지지/반대와 같이 대조적인 부호를 갖는다. 이러한 네트워크를 분석하기 위해, 부호가 있는 네트워크 임베딩 (signed network embedding, 이하 SNE) 문제에 대한 관심이 급증하고 있다. 특히, 최근 들어 그래프 합성곱 네트워크 기술을 기반으로 하는 SNE 방법들에 대한 연구가 활발히 수행되어 오고 있다. 본 논문에서는, 부호가 있는 네트워크의 희소성 정도가 기존 SNE 방법들의 성능에 어떻게 영향을 미치는 지에 대해 분석하고자 한다. 4 개의 실세계 데이터 집합들을 이용한 실험을 통해, 우리는 기존 방법들의 부호 예측 정확도가 희소한 네트워크들에서는 상당히 감소하는 것을 확인하였다.

Efficient Public Verification on the Integrity of Multi-Owner Data in the Cloud

  • Wang, Boyang;Li, Hui;Liu, Xuefeng;Li, Fenghua;Li, Xiaoqing
    • Journal of Communications and Networks
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    • v.16 no.6
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    • pp.592-599
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    • 2014
  • Cloud computing enables users to easily store their data and simply share data with others. Due to the security threats in an untrusted cloud, users are recommended to compute verification metadata, such as signatures, on their data to protect the integrity. Many mechanisms have been proposed to allow a public verifier to efficiently audit cloud data integrity without receiving the entire data from the cloud. However, to the best of our knowledge, none of them has considered about the efficiency of public verification on multi-owner data, where each block in data is signed by multiple owners. In this paper, we propose a novel public verification mechanism to audit the integrity of multi-owner data in an untrusted cloud by taking the advantage of multisignatures. With our mechanism, the verification time and storage overhead of signatures on multi-owner data in the cloud are independent with the number of owners. In addition, we demonstrate the security of our scheme with rigorous proofs. Compared to the straightforward extension of previous mechanisms, our mechanism shows a better performance in experiments.

Performance Evaluation of Signal Detection Algorithms for MB-OFDM (MB-OFDM을 위한 신호 획득 알고리즘 성능 평가)

  • Kim, Hae-Lyong;Lee, Yu-Sung;Park, Hyun-Cheol
    • Proceedings of the IEEK Conference
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    • 2004.06a
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    • pp.15-18
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    • 2004
  • A high data rate Wireless Personal Area Networks (WPAN) system is a hot issue in wireless communication communities and being standardized. Multi-band Orthogonal Frequency Division Multiplexing (MB-OFDM) is one of the candidates for WPAN standard. In this paper, we discuss the PLCP (Physical Layer Convergence Protocol) structure for MB-OFDM. Also we evaluate the performance of two signal detection algorithms, which are the method of cross-correlation with the original preamble and the signed preamble. The latter has a low complexity with a little degradation.

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Cryptanalysis and Improvement of an Efficient Certificateless Signature Scheme

  • Li, Jiguo;Huang, Xinyi;Mu, Yi;Wu, Wei
    • Journal of Communications and Networks
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    • v.10 no.1
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    • pp.10-17
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    • 2008
  • In traditional digital signature schemes, certificates signed by a trusted party are required to ensure the authenticity of the public key. In Asiacrypt 2003, the concept of certificateless signature scheme was introduced. The advantage of certificateless public key cryptography successfully eliminates the necessity of certificates in the traditional public key cryptography and simultaneously solves the inherent key escrow problem suffered in identity-based cryptography. Recently, Yap et al. proposed an efficient certificateless signature scheme and claimed that their scheme is existentially unforgeable in the random oracle model. In this paper, we show that the certificateless signature scheme proposed by Yap et al. is insecure against public key replacement attacks. Furthermore, we propose an improved certificateless signature scheme, which is existentially unforgeable against adaptive chosen message attacks under the computational Diffie-Hellman assumption in the random oracle model and provide the security proof of the proposed scheme.