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한국인터넷정보학회> KSII Transactions on Internet and Information Systems (TIIS)

KSII Transactions on Internet and Information Systems (TIIS) update

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  • : 공학분야  >  기타(공학)
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수록정보
수록범위 : 1권1호(2007)~13권4호(2019) |수록논문 수 : 2,307
KSII Transactions on Internet and Information Systems (TIIS)
13권4호(2019년 04월) 수록논문
최근 권호 논문
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KCI등재 SCI SCOPUS

1A Review of Deep Learning Research

저자 : Ruihui Mu , Xiaoqin Zeng

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1738-1764 (27 pages)

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With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and online advertising and so on. This paper introduces deep learning techniques from various aspects, including common models of deep learning and their optimization methods, commonly used open source frameworks, existing problems and future research directions. Firstly, we introduce the applications of deep learning; Secondly, we introduce several common models of deep learning and optimization methods; Thirdly, we describe several common frameworks and platforms of deep learning; Finally, we introduce the latest acceleration technology of deep learning and highlight the future work of deep learning.

KCI등재 SCI SCOPUS

2A Survey of Genetic Programming and Its Applications

저자 : Milad Taleby Ahvanooey , Qianmu Li , Ming Wu , Shuo Wang

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1765-1794 (30 pages)

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Genetic Programming (GP) is an intelligence technique whereby computer programs are encoded as a set of genes which are evolved utilizing a Genetic Algorithm (GA). In other words, the GP employs novel optimization techniques to modify computer programs; imitating the way humans develop programs by progressively re-writing them for solving problems automatically. Trial programs are frequently altered in the search for obtaining superior solutions due to the base is GA. These are evolutionary search techniques inspired by biological evolution such as mutation, reproduction, natural selection, recombination, and survival of the fittest. The power of GAs is being represented by an advancing range of applications; vector processing, quantum computing, VLSI circuit layout, and so on. But one of the most significant uses of GAs is the automatic generation of programs. Technically, the GP solves problems automatically without having to tell the computer specifically how to process it. To meet this requirement, the GP utilizes GAs to a “population” of trial programs, traditionally encoded in memory as tree-structures. Trial programs are estimated using a “fitness function” and the suited solutions picked for re-evaluation and modification such that this sequence is replicated until a “correct” program is generated. GP has represented its power by modifying a simple program for categorizing news stories, executing optical character recognition, medical signal filters, and for target identification, etc. This paper reviews existing literature regarding the GPs and their applications in different scientific fields and aims to provide an easy understanding of various types of GPs for beginners.

KCI등재 SCI SCOPUS

3A method based on Multi-Convolution layers Joint and Generative Adversarial Networks for Vehicle Detection

저자 : Guang Han , Jinpeng Su , Chengwei Zhang

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1795-1811 (17 pages)

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In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

KCI등재 SCI SCOPUS

4Design and Implementation of Location and Activity Monitoring System Based on LoRa

저자 : Shengwei Lin , Ziqiang Ying , Kan Zheng

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1812-1824 (13 pages)

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The location and human activity are usually used as one of the important parameters to monitor the health status in healthcare devices. However, nearly all existing location and monitoring systems have the limitation of short-range communication and high power consumption. In this paper, we propose a new mechanism to collect and transmit monitoring information based on LoRa technology. The monitoring device with sensors can collect the real-time activity and location information and transmit them to the cloud server through LoRa gateway. The user can check all his history and current information through the specific designed mobile applications. Experiment was carried out to verify the communication, power consumption and monitoring performance of the entire system. Experimental results demonstrate that this system can collect monitoring and activity information accurately and provide the long rang coverage with low power consumption.

KCI등재 SCI SCOPUS

5Detection of Political Manipulation through Unsupervised Learning

저자 : Sihyung Lee

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1825-1844 (20 pages)

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Political campaigns circulate manipulative opinions in online communities to implant false beliefs and eventually win elections. Not only is this type of manipulation unfair, it also has long-lasting negative impacts on people's lives. Existing tools detect political manipulation based on a supervised classifier, which is accurate when trained with large labeled data. However, preparing this data becomes an excessive burden and must be repeated often to reflect changing manipulation tactics.
We propose a practical detection system that requires moderate groundwork to achieve a sufficient level of accuracy. The proposed system groups opinions with similar properties into clusters, and then labels a few opinions from each cluster to build a classifier. It also models each opinion with features deduced from raw data with no additional processing. To validate the system, we collected over a million opinions during three nation-wide campaigns in South Korea. The system reduced groundwork from 200K to nearly 200 labeling tasks, and correctly identified over 90% of manipulative opinions. The system also effectively identified transitions in manipulative tactics over time. We suggest that online communities perform periodic audits using the proposed system to highlight manipulative opinions and emerging tactics.

KCI등재 SCI SCOPUS

6Cognitive Virtual Network Embedding Algorithm Based on Weighted Relative Entropy

저자 : Yuze Su , Xiangru Meng , Zhiyuan Zhao , Zhentao Li

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1845-1865 (21 pages)

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Current Internet is designed by lots of service providers with different objects and policies which make the direct deployment of radically new architecture and protocols on Internet nearly impossible without reaching a consensus among almost all of them. Network virtualization is proposed to fend off this ossification of Internet architecture and add diversity to the future Internet. As an important part of network virtualization, virtual network embedding (VNE) problem has received more and more attention.
In order to solve the problems of large embedding cost, low acceptance ratio (AR) and environmental adaptability in VNE algorithms, cognitive method is introduced to improve the adaptability to the changing environment and a cognitive virtual network embedding algorithmbased on weighted relative entropy (WRE-CVNE) is proposed in this paper. At first, the weighted relative entropy (WRE) method is proposed to select the suitable substrate nodes and paths in VNE. In WRE method, the ranking indicators and their weighting coefficients are selected to calculate the node importance and path importance. It is the basic of the WRE-CVNE. In virtual node embedding stage, the WRE method and breadth first search (BFS) algorithm are both used, and the node proximity is introduced into substrate node ranking to achieve the joint topology awareness. Finally, in virtual link embedding stage, the CPU resource balance degree, bandwidth resource balance degree and path hop counts are taken into account. The path importance is calculated based on the WRE method and the suitable substrate path is selected to reduce the resource fragmentation. Simulation results show that the proposed algorithm can significantly improve AR and the long-term average revenue to cost ratio (LTAR/CR) by adjusting the weighting coefficients in VNE stage according to the network environment. We also analyze the impact of weighting coefficient on the performance of the WRE-CVNE. In addition, the adaptability of the WRE-CVNE is researched in three different scenarios and the effectiveness and efficiency of the WRE-CVNE are demonstrated.

KCI등재 SCI SCOPUS

7Designing Rich-Secure Network Covert Timing Channels Based on Nested Lattices

저자 : Weiwei Liu , Guangjie Liu , Xiaopeng Ji , Jiangtao Zhai , Yuewei Dai

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1866-1883 (18 pages)

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As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

KCI등재 SCI SCOPUS

8Interference-Aware Channel Assignment Algorithm in D2D overlaying Cellular Networks

저자 : Liqun Zhao , Hongpeng Wang , Xiaoxiong Zhong

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1884-1903 (20 pages)

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Device-to-Device (D2D) communications can provide proximity based services in the future 5G cellular networks. It allows short range communication in a limited area with the advantages of power saving, high data rate and traffic offloading. However, D2D communications may reuse the licensed channels with cellular communications and potentially result in critical interferences to nearby devices. To control the interference and improve network throughput in overlaid D2D cellular networks, a novel channel assignment approach is proposed in this paper. First, we characterize the performance of devices by using Poisson point process model. Then, we convert the throughput maximization problem into an optimal spectrum allocation problem with signal to interference plus noise ratio constraints and solve it, i.e., assigning appropriate fractions of channels to cellular communications and D2D communications. In order to mitigate the interferences between D2D devices, a cluster-based multi-channel assignment algorithm is proposed. The algorithm first cluster D2D communications into clusters to reduce the problem scale. After that, a multi-channel assignment algorithm is proposed to mitigate critical interferences among nearby devices for each D2D cluster individually. The simulation analysis conforms that the proposed algorithm can greatly increase system throughput.

KCI등재 SCI SCOPUS

9A Cooperative Jamming Based Joint Transceiver Design for Secure Communications in MIMO Interference Channels

저자 : Boyang Huang , Zhengmin Kong , Yanjun Fang , Xin Jin

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1904-1921 (18 pages)

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In this paper, we investigate the problem of secure communications in multiple-input-multiple-output interference networks from the perspective of physical layer security. Specifically, the legitimate transmitter-receiver pairs are divided into different categories of active and inactive. To enhance the security performances of active pairs, inactive pairs serve as cooperative jammers and broadcast artificial noises to interfere with the eavesdropper. Besides, active pairs improve their own security by using joint transceivers. The encoding of active pairs and inactive pairs are designed by maximizing the difference of mean-squared errors between active pairs and the eavesdropper. In detail, the transmit precoder matrices of active pairs and inactive pairs are solved according to game theory and linear programming respectively. Experimental results show that the proposed algorithm has fast convergence speed, and the security performances in different scenarios are effectively improved.

KCI등재 SCI SCOPUS

10IMT: A Memory-Efficient and Fast Updatable IP Lookup Architecture Using an Indexed Multibit Trie

저자 : Junghwan Kim , Myeong-cheol Ko , Moon Sun Shin , Jinsoo Kim

발행기관 : 한국인터넷정보학회 간행물 : KSII Transactions on Internet and Information Systems (TIIS) 13권 4호 발행 연도 : 2019 페이지 : pp. 1922-1940 (19 pages)

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IP address lookup is a function to determine nexthop for a given destination IP address. It takes an important role in modern routers because of its computation time and increasing Internet traffic. TCAM-based IP lookup approaches can exploit the capability of parallel searching but have a limitation of its size due to latency, power consumption, updatability, and cost. On the other hand, multibit trie-based approaches use SRAM which has relatively low power consumption and cost. They reduce the number of memory accesses required for each lookup, but it still needs several accesses. Moreover, the memory efficiency and updatability are proportional to the number of memory accesses. In this paper, we propose a novel architecture using an Indexed Multibit Trie (IMT) which is based on combined TCAM and SRAM. In the proposed architecture, each lookup takes at most two memory accesses. We present how the IMT is constructed so as to be memory-efficient and fast updatable. Experiment results with real-world forwarding tables show that our scheme achieves good memory efficiency as well as fast updatability.

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