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- 저자 : Naixue Xiong (검색결과 14 건)
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Jucheng Yang,Naixue Xiong,Vasilakos, A. V.,Zhijun Fang,Dongsun Park,Xianghua Xu,Sook Yoon,Shanjuan Xie,Yong Yang IEEE 2011 IEEE systems journal Vol.5 No.4
<P>In cloud computing communications, information security entails the protection of information elements (e.g., multimedia data), only authorized users are allowed to access the available contents. Fingerprint recognition is one of the popular and effective approaches for priori authorizing the users and protecting the information elements during the communications. However, traditional fingerprint recognition approaches have demerits of easy losing rich information and poor performances due to the complex inputs, such as image rotation, incomplete input image, poor quality image enrollment, and so on. In order to overcome these shortcomings, in this paper, a new fingerprint recognition scheme based on a set of assembled invariant moment (geometric moment and Zernike moment) features to ensure the secure communications is proposed. And the proposed scheme is also based on an effective preprocessing, the extraction of local and global features and a powerful classification tool, thus it is able to handle the various input conditions encountered in the cloud computing communication. The experimental results show that the proposed method has a higher matching accuracy comparing with traditional or individual feature based methods on public databases.</P>
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Dynamic power management in new architecture of wireless sensor networks
Lin, Chuan,Xiong, Naixue,Park, Jong Hyuk,Kim, Tai-hoon John Wiley Sons, Ltd. 2009 International Journal of Communication Systems Vol.22 No.6
<P>Dynamic power management (DPM) technology has been widely used in sensor networks. Though many specific technical challenges remain and deserve much further study, the primary factor currently limiting progress in sensor networks is not these challenges but is instead the lack of an overall sensor network architecture. In this paper, we first develop a new architecture of sensor networks. Then we modify the sleep state policy developed by Sinha and Chandrakasan in (IEEE Design Test Comput. 2001; 18(2):62–74) and deduce that a new threshold satisfies the sleep-state transition policy. Under this new architecture, nodes in deeper sleep states consume lower energy while asleep, but require longer delays and higher latency costs to awaken. Implementing DPM with considering the battery status and probability of event generation will reduce the energy consumption and prolong the whole lifetime of the sensor networks. We also propose a new energy-efficient DPM, which is a modified sleep state policy and combined with optimal geographical density control (OGDC) (Wireless Ad Hoc Sensor Networks 2005; 1(1–2):89–123) to keep a minimal number of sensor nodes in the active mode in wireless sensor networks. Implementing dynamic power management with considering the battery status, probability of event generation and OGDC will reduce the energy consumption and prolong the whole lifetime of the sensor networks. Copyright © 2008 John Wiley & Sons, Ltd.</P>
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Qiongqiong Fu,Liping Gao,Naixue Xiong 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.5
With the real-time group editing system, a group of users can view and edit the shared document by communication networks anytime and anywhere. Under the circumstance, it is surely inevitable that many operations from different users are going to conflict. Thus, two issues, the conflict resolution and the consistency maintenance, are the most important for designing and completing the system. In the past, the address space transformation algorithm, invented from the research about the real-time text editing system, could maintain consistency among more sites. The Multi Version conflict resolution approach could preserve users’ intentions but not all when conflicts occur. This paper proposes a new solution of conflict resolution, named Intention Combination Conflict Resolution strategy with the document model of AST based on the idea of Multi Version approach. This solution can not only preserve all users’ editing consistency by intention combination, but also keep all versions of operational objects including conflict operations’ combination effects. In addition, the effectiveness of related algorithms is analyzed, and the availability of the strategy is described by a case and proved by our experiment.
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Fast Face Gender Recognition by Using Local Ternary Pattern and Extreme Learning Machine
( Jucheng Yang ),( Yanbin Jiao ),( Naixue Xiong ),( Dongsun Park ) 한국인터넷정보학회 2013 KSII Transactions on Internet and Information Syst Vol.7 No.7
Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.
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Pricing Strategies of Social Commerce Platform under Network Externalities
Wei Zhang,Wei Ma,Zhonghua Li,Naixue Xiong 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.12
Although the theory of two-sided markets is popular nowadays, little attention was paid on self-network externalities and UGC (User Generated Content) produced by buyers which are the major features of social commerce two-sided markets. This article studies percentages of buyers who generated UGC, self-network externalities of buyers and cross-group externalities between two groups. The three factors influence the pricing strategy of social commerce platforms based on two-sided markets. With analyzing the special characteristics of social commerce, the study unveils that the optimal price of buyers charged by social commerce platform shows a negative correlation with self-network externalities and it also shows a negative correlation with the probability of UGC generated by buyers. The study also shows that the equilibrium price of buyers declines with the augment of cross-group externalities of buyers to sellers, and the equilibrium price of sellers declines with the augment of cross-group work externalities of sellers to buyers. The social commerce platforms on the basis of interest graph, lower UGC threshold and more interactive among customers gain the competitive advantages. Compared to other platforms, the two-sided social commerce platforms give consumers and retailers more subsidies.
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Generative Adversarial Networks: A Literature Review
( Jieren Cheng ),( Yue Yang ),( Xiangyan Tang ),( Naixue Xiong ),( Yuan Zhang ),( Feifei Lei ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.12
The Generative Adversarial Networks, as one of the most creative deep learning models in recent years, has achieved great success in computer vision and natural language processing. It uses the game theory to generate the best sample in generator and discriminator. Recently, many deep learning models have been applied to the security field. Along with the idea of “generative” and “adversarial”, researchers are trying to apply Generative Adversarial Networks to the security field. This paper presents the development of Generative Adversarial Networks. We review traditional generation models and typical Generative Adversarial Networks models, analyze the application of their models in natural language processing and computer vision. To emphasize that Generative Adversarial Networks models are feasible to be used in security, we separately review the contributions that their defenses in information security, cyber security and artificial intelligence security. Finally, drawing on the reviewed literature, we provide a broader outlook of this research direction.
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Secure Similarity Search over Encrypted Cloud Images
Yi Zhu,Xingming Sun,Zhihua Xia,Naixue Xiong 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.8
With the growing popularity of cloud computing, more and more data owners are willing to outsource their data to the cloud. However, private data should be encrypted before outsourcing for security requirements, which obsoletes data utilization like content-based image retrieval. In this paper, we propose a secure similarity image search scheme, which allows data owners to outsource their encrypted image database to the cloud server without revealing the real content of images. The proposed scheme supports both global and local feature based image retrieval under various distance metrics, such as earth mover's distance. Firstly, the data owner extracts either global features or local features from images to represent the images. Then, these features are used to generate a searchable index. Finally, both image database and searchable index are encrypted before outsourcing to the cloud server. When a query image coming, the data user extracts feature from the query image and generates the search trapdoor. The trapdoor is then sent to the cloud server and used to compare the similarity with the searchable index. Extensive experiments are conducted to show the efficiency and applicability of our proposed similarity image search system.
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Exploring finger vein based personal authentication for secure IoT
Lu, Yu,Wu, Shiqian,Fang, Zhijun,Xiong, Naixue,Yoon, Sook,Park, Dong Sun North-Holland 2017 Future generations computer systems Vol.77 No.-
<P><B>Abstract</B></P> <P>Personal authentication is getting harder and harder in the internet of things (IoT). Existing methods used for personal authentication, such as passwords and the two-factor authentication (2FA), are inadequate and ineffective due to human error and other attacks. To support more secure IoT, this paper proposes a finger vein based personal authentication method by exploring competitive orientations and magnitudes from finger vein images. Finger vein recognition has been proven to be a reliable and promising solution for biometric-based personal authentication. The stable and rich piecewise line features in finger vein images can be used to clearly represent finger vein patterns for personal authentication. In this paper, we propose an efficient local descriptor for finger vein feature extraction, namely the histogram of competitive orientations and magnitudes (HCOM). For a finger vein image, two types of local histograms are extracted and fused together to efficiently and adequately represent the competitive information: the histogram of competitive orientations (HCO) and the local binary pattern histogram generated from the image of competitive magnitudes (named as HCMLBP). The extensive experimental results from the application of the proposed method to the public finger vein database MMCBNU_6000, demonstrate that the proposed method outperforms state-of-the-art orientation coding (OC)-based methods and other commonly used local descriptors. Additionally, the proposed method can be used for finger vein image enhancement.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The proposed method can efficiently extract competitive orientations and magnitudes. </LI> <LI> The proposed method outperforms the OC-based methods and common local descriptors. </LI> <LI> The proposed method has small feature size and fast speed. </LI> <LI> The proposed method can be used for finger vein image enhancement. </LI> </UL> </P>
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