{"title":"Vehicle approaching model for T-junction during transition to autonomous vehicles","authors":"Tatsuro Hara, R. Kiyohara","doi":"10.1109/ICOIN.2018.8343130","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343130","url":null,"abstract":"Vehicle manufacturers are actively developing technologies for the realization of autonomous vehicles. Many of these have already been put into practical use such as cruise control and lane-keeping assist system. Autonomous vehicles are expected to solve many problems such as traffic accidents and traffic jams. However, this is based on the assumption that all vehicles are autonomous. Focusing on the transition period to autonomous vehicles, we design a driving model for a mixed environment comprising autonomous and non-autonomous vehicles. In this paper, we experiment and measure the distance needed for driver pedals for braking between vehicles and in front of a vehicle in mixed environment at a T-junction. Moreover, we discuss traffic jams at a T-junction.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131761145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sanghoon Lee, Ilhong Shin, E. Rhee, Sunghee Lee, Namkyung Lee
{"title":"A transformation analysis of 3D virtual object for projection mapping","authors":"Sanghoon Lee, Ilhong Shin, E. Rhee, Sunghee Lee, Namkyung Lee","doi":"10.1109/ICOIN.2018.8343085","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343085","url":null,"abstract":"The transformation relationships between real-world and 3D virtual objects are analyzed for projection mapping. Projector coordinates systems and OpenGL vertex transformation model are examined. Mainly, we analyzed lens distortion model and its inverse model, and proposed shader code for it.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131895998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Semi-automatic image and video annotation system for generating ground truth information","authors":"Chang-Mo Yang, Yusik Choo, Sungjoo Park","doi":"10.1109/ICOIN.2018.8343233","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343233","url":null,"abstract":"Recently, techniques for automatically interpreting images or videos through machine learning based on big data have been actively studied. In this paper, we propose a semiautomatic image and video annotation system to generate ground truth information, which is essential information for machine learning of images or videos. Unlike the conventional methods for generating simple ground truth information manually, the proposed system not only provides various ground truth information such as object information, motion information, and event information, but also uses a semi-automatic image and video annotation method for fast generation of ground truth information. The ground truth information generated by the proposed system is stored in the metadata database as a form of XML. The implementation results show that the proposed system provides not only fast ground truth annotation, but also more various ground truth information compared to the existing methods.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130284672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Security insurance of cloud computing services through cross roads of human-immune and intrusion-detection systems","authors":"Hamza Hammami, H. Brahmi, S. Yahia","doi":"10.1109/ICOIN.2018.8343106","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343106","url":null,"abstract":"Cloud computing has emerged as a new computer model that aims to provide reliable, customized and dynamic information technology environments oriented towards a better quality of service and availability of infrastructure without much financial burden. However, this advanced paradigm has immediately highlighted a serious security problem whose resolution is a real challenge. This challenge is explained by the importance of using services offered by cloud computing in distributed applications and by the interest to fully take advantage of their strengths. In this paper, we propose a novel intrusion detection system dedicated to the security of cloud computing resources and services. This system takes advantage from: (i) the intrusion detection system paradigm to implement an efficient security system; and (ii) the integration of human immune techniques, i.e. macrophage, B cells, T cells, and natural killer cells. The performed experiments show the high performance of our proposed system in terms of detection of novel attacks as well as of good detection rates and low false ones.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"1939 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128864551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Finger motion recognition robust to diverse arm postures using EMG and accelerometer","authors":"Kiwon Rhee, Hyun-Chool Shin","doi":"10.1109/ICOIN.2018.8343237","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343237","url":null,"abstract":"The electromyogram (EMG) based finger motion recognition accuracy may be degraded during the actual stage of practical applications due to various causes. Among them, the representative issue is the changes of the EMG signals of the identical finger motion by the different arm postures. We propose an EMG based finger motion recognition technique robust to diverse arm postures. The proposed method uses both the signals of the accelerometer and EMG simultaneously to recognize correct finger motions for each arm posture. We compared the experimental results with and without considering the corresponding arm postures to recognize finger motions. The average recognition of finger motions with the correct arm posture inference was 85.7% which is 31.6% higher than without considering the corresponding arm postures. In this study, accelerometer and EMG signals were used simultaneously, which decreased the effect of different arm postures on the EMG signals and therefore improved the recognition accuracy of finger motions.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127625123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jeffrey Spaulding, Jeman Park, Joongheon Kim, Aziz Mohaisen
{"title":"Proactive detection of algorithmically generated malicious domains","authors":"Jeffrey Spaulding, Jeman Park, Joongheon Kim, Aziz Mohaisen","doi":"10.1109/ICOIN.2018.8343077","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343077","url":null,"abstract":"Using an intrinsic feature of malicious domain name queries prior to their registration (perhaps due to clock drift), we devise a difference-based lightweight feature for malicious domain name detection. Using NXDomain query and response of a popular malware, we establish the effectiveness of our detector with 99% accuracy, and as early as more than 48 hours before they are registered. Our technique serves as a tool of detection where other techniques relying on entropy or domain generating algorithms reversing are impractical.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132760276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A study on the processing and reinforcement of message digest through two-dimensional array masking","authors":"Sun-young Park, Keecheon Kim","doi":"10.1109/ICOIN.2018.8343177","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343177","url":null,"abstract":"Hash algorithms have been widely used for cryptography. It has been impossible to decrypt the ciphertexts generated through hash algorithms, as an operation that damages the original text is performed. The vulnerability of SHA1 (an old hash algorithm) has been revealed, and there has been a great deal of data available for dictionary attacks. Although the industry has been gradually refraining from using SHA1, it remains in use in some existing systems for various reasons. In particular, when problems resulting from medical service interruption or mass update are directly related to a person's life, updating the encryption algorithm can be a burden. In this study, we aim to increase the complexity of ciphertexts by postprocessing hash ciphertext by masking message digest to a two-dimensional array constructed using an image processing technique. This will allow the use of hash ciphertexts with increased complexity in some medical devices that are forced to use old hash algorithms for various reasons.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"10 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132271823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Document level polarity classification with attention gated recurrent unit","authors":"Hoon-Keng Poon, W. Yap, Y. Tee, B. Goi, W. Lee","doi":"10.1109/ICOIN.2018.8343074","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343074","url":null,"abstract":"Reviews can be categorized into two extreme polarities, that is, positive or negative. These reviews from different consumers on a product or service can help a new consumer to make a good decision. Document level sentiment classification aims to understand user generated content or opinion towards certain products or services. In this paper, we propose a recurrent neural network model in classifying positive and negative reviews using gated recurrent unit and attention mechanism. Effectiveness of our proposed model is evaluated using Yelp Review dataset obtained from Yelp Dataset Challenge. Experimental results show that our proposed model can outperform existing models for document level sentiment classification.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A method for estimating process maliciousness with Seq2Seq model","authors":"Shun Tobiyama, Yukiko Yamaguchi, Hirokazu Hasegawa, Hajime Shimada, Mitsuaki Akiyama, Takeshi Yagi","doi":"10.1109/ICOIN.2018.8343120","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343120","url":null,"abstract":"In recent years, cyber-attacks become more sophisticated and the damage caused by these attacks also becomes serious problem. In these attacks, specially-crafted malware, which utilizes countermeasures such as post execution binary elimination or process injection, is used not to be noticed by a target. Therefore, it is hard to detect malware used in these attacks with binary-dependent method before the intrusion, and the countermeasure after intrusion is required. This paper proposes an infection detection method by estimating maliciousness of processes in Windows machines. In our proposal, we extract feature vector sequence from process behavior captured by Process Monitor with Seq2Seq model at first, and then estimate the process maliciousness by classifying with the other Seq2Seq model. We evaluated the performance of our proposal by 5-fold cross validation and compared the performance with the method using uni-gram feature.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134223188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The effect of datagram size and susceptible population on the epidemiology of fast self-propagating malware","authors":"L. Tidy, Steve Woodhead","doi":"10.1109/ICOIN.2018.8343148","DOIUrl":"https://doi.org/10.1109/ICOIN.2018.8343148","url":null,"abstract":"The cost of a security event caused by fast self-propagating malware (a worm) has been estimated to be up to US$2.6 billion. Additionally, network malware outbreaks have been observed that spread at a significant pace across the global internet, with an observed infection level of more than 90 percent of vulnerable hosts within 10 minutes. The threat posed by such fast-spreading malware is therefore significant, particularly given the fact that network operator / administrator intervention is not likely to take effect within the typical epidemiological timescale of such malware infections. The internet worm simulator (IWS) is a finite state machine (FSM) based simulator capable of simulating the largescale epidemiology of fast self-propagating malware. Deterministic mathematical models require significantly less computation, however, lack the detail of FSM based simulation. This article focusses on the effect of common worm attributes on the contact coefficient of an SI model. The trends observed are presented, and their impact discussed. It is intended that this work can be used by researchers and professionals, to aid their understanding of large-scale worm outbreaks.","PeriodicalId":228799,"journal":{"name":"2018 International Conference on Information Networking (ICOIN)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125745956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}