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한국정보처리학회> JIPS(Journal of Information Processing Systems)> A Hierarchical Bilateral-Diffusion Architecture for Color Image Encryption

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A Hierarchical Bilateral-Diffusion Architecture for Color Image Encryption

Menglong Wu , Yan Li , Wenkai Liu
  • : 한국정보처리학회
  • : JIPS(Journal of Information Processing Systems) 18권1호
  • : 연속간행물
  • : 2022년 02월
  • : 59-74(16pages)
JIPS(Journal of Information Processing Systems)

DOI


목차

1. Introduction
2. Preliminary Work
3. Proposed Methodology
4. Experimental Results and Computational Speed Analysis
5. Security Analysis
6. Conclusion
Acknowledgement
References

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초록 보기

During the last decade, the security of digital images has received considerable attention in various multimedia transmission schemes. However, many current cryptosystems tend to adopt a single-layer permutation or diffusion algorithm, resulting in inadequate security. A hierarchical bilateral diffusion architecture for color image encryption is proposed in response to this issue, based on a hyperchaotic system and DNA sequence operation. Primarily, two hyperchaotic systems are adopted and combined with cipher matrixes generation algorithm to overcome exhaustive attacks. Further, the proposed architecture involves designing pixelpermutation, pixel-diffusion, and DNA (deoxyribonucleic acid) based block-diffusion algorithm, considering system security and transmission efficiency. The pixel-permutation aims to reduce the correlation of adjacent pixels and provide excellent initial conditions for subsequent diffusion procedures, while the diffusion architecture confuses the image matrix in a bilateral direction with ultra-low power consumption. The proposed system achieves preferable number of pixel change rate (NPCR) and unified average changing intensity (UACI) of 99.61% and 33.46%, and a lower encryption time of 3.30 seconds, which performs better than some current image encryption algorithms. The simulated results and security analysis demonstrate that the proposed mechanism can resist various potential attacks with comparatively low computational time consumption.

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간행물정보

  • : 공학분야  > 전자공학
  • : KCI등재
  • : SCOPUS
  • : 격월
  • : 1976-913x
  • : 2092-805X
  • : 학술지
  • : 연속간행물
  • : 2005-2022
  • : 989


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1Implementation of Quality Management System for Wild-Simulated Ginseng Using Blockchain

저자 : Youngjun Sung , Yoojae Won

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 173-187 (15 pages)

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A special government agency has been charged with implementing quality management to guarantee the quality of wild-simulated ginseng. However, these processes are carried out by use of documents, and this has resulted in information omission and high document management costs. To solve this problem, this study analyzed the existing quality management process by using a smart contract for the existing offline form and proposed a new quality management system for storing and managing all log data in the blockchain. This system reduced documentation management costs about quality management and recorded information in the previous step through the quality management steps, thus forming a step-by-step record chain. Experiments were conducted by implementing this system, which improved data integrity and reliability. Additionally, sensitive information, such as personal information, was included in the system by use of the off-chain technology.

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2Path-Based Computation Encoder for Neural Architecture Search

저자 : Ying Yang , Xu Zhang , Hu Pan

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 188-196 (9 pages)

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Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

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3A Manually Captured and Modified Phone Screen Image Dataset for Widget Classification on CNNs

저자 : Sungchul Byun , Seong-soo Han , Chang-sung Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 197-207 (11 pages)

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The applications and user interfaces (UIs) of smart mobile devices are constantly diversifying. For example, deep learning can be an innovative solution to classify widgets in screen images for increasing convenience. To this end, the present research leverages captured images and the ReDraw dataset to write deep learning datasets for image classification purposes. First, as the validation for datasets using ResNet50 and EfficientNet, the experiments show that the dataset composed in this study is helpful for classification according to a widget's functionality. An implementation for widget detection and classification on RetinaNet and EfficientNet is then executed. Finally, the research suggests the Widg-C and Widg-D datasets―a deep learning dataset for identifying the widgets of smart devices―and implementing them for use with representative convolutional neural network models.

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4Models and Methods for the Evaluation of Automobile Manufacturing Supply Chain Coordination Degree Based on Collaborative Entropy

저자 : Qiang Xiao , Hongshuang Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 208-222 (15 pages)

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Through the analysis of the coordination mechanism of the supply chain system of China's automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China's automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China's automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.

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5Automated Print Quality Assessment Method for 3D Printing AI Data Construction

저자 : Hyun-ju Yoo , Nammee Moon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 223-234 (12 pages)

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The evaluation of the print quality of 3D printing has traditionally relied on manual work using dimensional measurements. However, the dimensional measurement method has an error value that depends on the person who measures it. Therefore, we propose the design of a new print quality measurement method that can be automatically measured using the field-of-view (FOV) model and the intersection over union (IoU) technique. First, the height information of the modeling is acquired from a camera; the output is measured by a sensor; and the images of the top and isometric views are acquired from the FOV model. The height information calculates the height ratio by calculating the percentage of modeling and output, and compares the 2D contour of the object on the image using the FOV model. The contour of the object is obtained from the image for 2D contour comparison and the IoU is calculated by comparing the areas of the contour regions. The accuracy of the automated measurement technique for determining, which derives the print quality value was calculated by averaging the IoU value corrected by the measurement error and the height ratio value.

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6A Fast Inter-prediction Mode Decision Algorithm for HEVC Based on Spatial-Temporal Correlation

저자 : Weixin Yao , Dan Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 235-244 (10 pages)

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Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

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7A Deep Learning Approach for Identifying User Interest from Targeted Advertising

저자 : Wonkyung Kim , Kukheon Lee , Sangjin Lee , Doowon Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 245-257 (13 pages)

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In the Internet of Things (IoT) era, the types of devices used by one user are becoming more diverse and the number of devices is also increasing. However, a forensic investigator is restricted to exploit or collect all the user's devices; there are legal issues (e.g., privacy, jurisdiction) and technical issues (e.g., computing resources, the increase in storage capacity). Therefore, in the digital forensics field, it has been a challenge to acquire information that remains on the devices that could not be collected, by analyzing the seized devices. In this study, we focus on the fact that multiple devices share data through account synchronization of the online platform. We propose a novel way of identifying the user's interest through analyzing the remnants of targeted advertising which is provided based on the visited websites or search terms of logged-in users. We introduce a detailed methodology to pick out the targeted advertising from cache data and infer the user's interest using deep learning. In this process, an improved learning model considering the unique characteristics of advertisement is implemented. The experimental result demonstrates that the proposed method can effectively identify the user interest even though only one device is examined.

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8Implementation of Image Transmission Based on Vehicle-to-Vehicle Communication

저자 : Changhao Piao , Xiaoyue Ding , Jia He , Soohyun Jang , Mingjie Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 258-267 (10 pages)

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Weak over-the-horizon perception and blind spot are the main problems in intelligent connected vehicles (ICVs). In this paper, a V2V image transmission-based road condition warning method is proposed to solve them. The encoded road emergency images which are collected by the ICV are transmitted to the on-board unit (OBU) through Ethernet. The OBU broadcasts the fragmented image information including location and clock of the vehicle to other OBUs. To satisfy the channel quality of the V2X communication in different times, the optimal fragment length is selected by the OBU to process the image information. Then, according to the position and clock information of the remote vehicles, OBU of the receiver selects valid messages to decode the image information which will help the receiver to extend the perceptual field. The experimental results show that our method has an average packet loss rate of 0.5%. The transmission delay is about 51.59 ms in low-speed driving scenarios, which can provide drivers with timely and reliable warnings of the road conditions.

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9An Approach to Applying Multiple Linear Regression Models by Interlacing Data in Classifying Similar Software

저자 : Hyun-il Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 268-281 (14 pages)

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The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

KCI등재 SCOPUS

10A BERT-Based Automatic Scoring Model of Korean Language Learners' Essay

저자 : Jung Hee Lee , Ji Su Park , Jin Gon Shon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 2호 발행 연도 : 2022 페이지 : pp. 282-291 (10 pages)

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This research applies a pre-trained bidirectional encoder representations from transformers (BERT) handwriting recognition model to predict foreign Korean-language learners' writing scores. A corpus of 586 answers to midterm and final exams written by foreign learners at the Intermediate 1 level was acquired and used for pre-training, resulting in consistent performance, even with small datasets. The test data were pre-processed and fine-tuned, and the results were calculated in the form of a score prediction. The difference between the prediction and actual score was then calculated. An accuracy of 95.8% was demonstrated, indicating that the prediction results were strong overall; hence, the tool is suitable for the automatic scoring of Korean written test answers, including grammatical errors, written by foreigners. These results are particularly meaningful in that the data included written language text produced by foreign learners, not native speakers.

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1Delivering Augmented Information in a Session Initiation Protocol-Based Video Telephony Using Real-Time AR

저자 : Sung-bong Jang , Young-woong Ko

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 1-11 (11 pages)

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Online video telephony systems have been increasingly used in several industrial areas because of coronavirus disease 2019 (COVID-19) spread. The existing session initiation protocol (SIP)-based video call system is being usefully utilized, however, there is a limitation that it is very inconvenient for users to transmit additional information during conversation to the other party in real time. To overcome this problem, an enhanced scheme is presented based on augmented real-time reality (AR). In this scheme, augmented information is automatically searched from the Internet and displayed on the user's device during video telephony. The proposed approach was qualitatively evaluated by comparing it with other conferencing systems. Furthermore, to evaluate the feasibility of the approach, we implemented a simple network application that can generate SIP call requests and answer with AR object pre-fetching. Using this application, the call setup time was measured and compared between the original SIP and pre-fetching schemes. The advantage of this approach is that it can increase the convenience of a user's mobile phone by providing a way to automatically deliver the required text or images to the receiving side.

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2Lightweight Single Image Super-Resolution by Channel Split Residual Convolution

저자 : Buzhong Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 12-25 (14 pages)

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In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.

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3Systematic Review on Chatbot Techniques and Applications

저자 : Dong-min Park , Seong-soo Jeong , Yeong-seok Seo

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 26-47 (22 pages)

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Chatbots were an important research subject in the past. A chatbot is a computer program or an artificial intelligence program that participates in a conversation via auditory or textual methods. As the research on chatbots progressed, some important issues regarding them changed over time. Therefore, it is necessary to review the technology with a focus on recent advancements and core research technologies. In this paper, we introduce five different chatbot technologies: natural language processing, pattern matching, semantic web, data mining, and context-aware computer. We also introduce the latest technology for the chatbot researchers to recognize the present situation and channelize it in the right direction.

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4A Windowed-Total-Variation Regularization Constraint Model for Blind Image Restoration

저자 : Ganghua Liu , Wei Tian , Yushun Luo , Juncheng Zou , Shu Tang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 48-58 (11 pages)

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Blind restoration for motion-blurred images is always the research hotspot, and the key for the blind restoration is the accurate blur kernel (BK) estimation. Therefore, to achieve high-quality blind image restoration, this thesis presents a novel windowed-total-variation method. The proposed method is based on the spatial scale of edges but not amplitude, and the proposed method thus can extract useful image edges for accurate BK estimation, and then recover high-quality clear images. A large number of experiments prove the superiority.

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5A Hierarchical Bilateral-Diffusion Architecture for Color Image Encryption

저자 : Menglong Wu , Yan Li , Wenkai Liu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 59-74 (16 pages)

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During the last decade, the security of digital images has received considerable attention in various multimedia transmission schemes. However, many current cryptosystems tend to adopt a single-layer permutation or diffusion algorithm, resulting in inadequate security. A hierarchical bilateral diffusion architecture for color image encryption is proposed in response to this issue, based on a hyperchaotic system and DNA sequence operation. Primarily, two hyperchaotic systems are adopted and combined with cipher matrixes generation algorithm to overcome exhaustive attacks. Further, the proposed architecture involves designing pixelpermutation, pixel-diffusion, and DNA (deoxyribonucleic acid) based block-diffusion algorithm, considering system security and transmission efficiency. The pixel-permutation aims to reduce the correlation of adjacent pixels and provide excellent initial conditions for subsequent diffusion procedures, while the diffusion architecture confuses the image matrix in a bilateral direction with ultra-low power consumption. The proposed system achieves preferable number of pixel change rate (NPCR) and unified average changing intensity (UACI) of 99.61% and 33.46%, and a lower encryption time of 3.30 seconds, which performs better than some current image encryption algorithms. The simulated results and security analysis demonstrate that the proposed mechanism can resist various potential attacks with comparatively low computational time consumption.

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6User-to-User Matching Services through Prediction of Mutual Satisfaction Based on Deep Neural Network

저자 : Jinah Kim , Nammee Moon

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 75-88 (14 pages)

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With the development of the sharing economy, existing recommender services are changing from user-item recommendations to user-user recommendations. The most important consideration is that all users should have the best possible satisfaction. To achieve this outcome, the matching service adds information between users and items necessary for the existing recommender service and information between users, so higher-level data mining is required. To this end, this paper proposes a user-to-user matching service (UTU-MS) employing the prediction of mutual satisfaction based on learning. Users were divided into consumers and suppliers, and the properties considered for recommendations were set by filtering and weighting. Based on this process, we implemented a convolutional neural network (CNN)-deep neural network (DNN)-based model that can predict each supplier's satisfaction from the consumer perspective and each consumer's satisfaction from the supplier perspective. After deriving the final mutual satisfaction using the predicted satisfaction, a top recommendation list is recommended to all users. The proposed model was applied to match guests with hosts using Airbnb data, which is a representative sharing economy platform. The proposed model is meaningful in that it has been optimized for the sharing economy and recommendations that reflect user-specific priorities.

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7Multistage Pulse Jamming Suppression Algorithm for Satellite Navigation Receiver

저자 : Xiaobo Yang , Jining Feng , Ying Xu

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 89-96 (8 pages)

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A novel multistage pulse jamming suppression algorithm was proposed to solve the anti-pulse jamming problem encountered in navigation receivers. Based on the characteristics of the short duration of pulse jamming and distribution characteristics of satellite signals, the pulse jamming detection threshold was derived. From the experiments, it was found that the randomness of pulse jamming affects jamming suppression. On this basis, the principle of the multistage anti-pulse jamming algorithm was established. The effectiveness of the anti-jamming algorithm was verified through experiments. The characteristics of the algorithm include simple determination of jamming detection threshold, easy programming, and complete suppression of pulse jamming.

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8Improved Dynamic Programming in Local Linear Approximation Based on a Template in a Lightweight ECG Signal-Processing Edge Device

저자 : Seungmin Lee , Daejin Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 97-114 (18 pages)

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Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

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9A Novel Framework Based on CNN-LSTM Neural Network for Prediction of Missing Values in Electricity Consumption Time-Series Datasets

저자 : Syed Nazir Hussain , Azlan Abd Aziz , Jakir Hossen , Nor Azlina Ab Aziz , G. Ramana Murthy , Fajaruddin Bin Mustakim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 115-129 (15 pages)

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Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.

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10Identifying Critical Factors for Successful Games by Applying Topic Modeling

저자 : Mookyung Kwak , Ji Su Park , Jin Gon Shon , Abstract

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 1호 발행 연도 : 2022 페이지 : pp. 130-145 (16 pages)

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Games are widely used in many fields, but not all games are successful. Then what makes games successful? The question gave us the motivation of this paper, which is to identify critical factors for successful games with topic modeling technique. It is supposed that game reviews written by experts sit on abundant insights and topics of how games succeed. To excavate these insights and topics, latent Dirichlet allocation, a topic modeling analysis technique, was used. This statistical approach provided words that implicate topics behind them. Fifty topics were inferred based on these words, and these topics were categorized by stimulation-response-desiregoal (SRDG) model, which makes a streamlined flow of how players engage in video games. This approach can provide game designers with critical factors for successful games. Furthermore, from this research result, we are going to develop a model for immersive game experiences to explain why some games are more addictive than others and how successful gamification works.

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