2023 15th International Conference on Knowledge and Smart Technology (KST)最新文献

{"title":"Hey Alexa … Examining Factors Influencing the Educational Use of AI-Enabled Voice Assistants During the COVID-19 Pandemic","authors":"Rohani Rohan, Debajyoti Pal, Suree Funilkul","doi":"10.1109/KST57286.2023.10086856","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086856","url":null,"abstract":"The COVID-19 pandemic has resulted in a rapid growth of online learning. While majority of the current research focus on different learning management systems, massive open online courses, or even specific softwares like Zoom and Microsoft Teams, the use of artificial-intelligence (AI) based voice assistants (VAs) for the purpose of online education is very rare. In this work we propose, validate, and test a research model that explains the continuance usage of VAs by students for learning purpose during their home quarantine period. We consider novel pandemic-specific psychological factors like loneliness and self-quarantine, together with anthropomorphic factors like voice attractiveness of the VAs for proposing the research model. The factors of satisfaction and continuance usage are borrowed from Expectation Confirmation Theory. Partial Least Squares Structural Equation Modelling is used for testing the proposed model.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129866318","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":"Honeypot-Assisted Masquerade Detection with Character-Level Machine Learning","authors":"Ryusei Higuchi, H. Ochiai, H. Esaki","doi":"10.1109/KST57286.2023.10086831","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086831","url":null,"abstract":"Intrusions into the shell of Linux operating systems through ssh, telnet, etc. are critical. It is important to detect the access of newly-emerging attackers, distinguishing them from the legitimate users. We propose the use of honeypots for collecting the trend of malicious commands, and to train character-level machine learning models for masquerade detection. In this paper, we provide a profiling of 1,314,834 commands collected in 173 days with our honeypot in 2021. We also provide our evaluation with Logistic Regression and several configurations of 1D-CNN and 2D-CNN, using the honeypot commands and legitimate commands collected from 32 users on 27 servers. The evaluation results indicate that 1D-CNN(shallow) and 2D-CNN(large) models provide a good performance regarding detection rate and false positive rate. Even when the trends of honeypot commands changed, the detection rate were almost 100% and the false positive rate were 0.0% regarding the two models.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134437708","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":"Keynote","authors":"Denis Caromel","doi":"10.1109/KST57286.2023.10086847","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086847","url":null,"abstract":"This talk gives an overview of progress and challenges in learnable image encryption with a secret key for deep neural networks (DNNs). Learnable encryption with a secret key enables us not only to protect visual information on plain images but also to embed unique features controlled with a key into images and models. Various applications of such encryption have been developed by using these properties. In this talk, we first focus privacy-preserving image classification tasks with learnable encryption, and then such encryption is demonstrated to give a new insight to adversarially robust defenses and model protection. Finally, we discuss future prospects for reliable deep leaning. Biography Hitoshi Kiya is a Professor of the Department of Computer Science at Tokyo Metropolitan University, Japan. He received the B.E. and M.E. degrees from the Nagaoka University of Technology, Japan, in 1980 and 1982, respectively, and the Dr.Eng. degree from Tokyo Metropolitan University in 1987. In 1982, he joined Tokyo Metropolitan University, where he became a Full Professor in 2000. From 1995 to 1996, he attended the University of Sydney, Australia, as a Visiting Fellow. He is a Life Fellow of IEEE, and a Fellow of IEICE, ITE and AAIA. He served as the President of APSIPA, and the Regional Director-at-Large for Region 10 of the IEEE Signal Processing Society. He was also the President of the IEICE Engineering Sciences Society. He has organized a lot of international conferences in such roles as the TPC Chair of IEEE ICASSP 2012 and as the General Co-Chair of IEEE ISCAS 2019. He has received numerous awards, including 12 best paper awards. 20 23 1 5t h In te rn at io na l C on fe re nc e on K no w le dg e an d Sm ar t T ec hn ol og y (K ST ) | 9 78 -1 -6 65 477 12 -3 /2 3/ $3 1. 00 © 20 23 IE EE | D O I: 10 .1 10 9/ K ST 57 28 6. 20 23 .1 00 86 84 7 2023 15th International Conference on Knowledge and Smart Technology (KST) __________________________________________________________________________________ XVI Computational Intelligence in Biomedical Engineering Assoc. Prof. Sansanee Auephanwiriyakul, Ph.D. Computer Engineering Department, Faculty of Engineering Biomedical Engineering Institute, Chiang Mai University, Thailand Abstract Computational Intelligence (CI) relies on and combines several algorithms in fuzzy systems, neural networks, evolutionary computation, swarm intelligence, fractals, chaos theory, artificial immune systems, wavelets, etc., to produce an algorithm that is intelligent somehow. CI has been utilized in many applications for several years. One of the areas that CI has an impact on is the area of biomedical engineering, e.g., medical image processing, medical signal processing and biometrics. One of the CI tools used in those mentioned application is classification or sometimes called decision making. The major area in the classification is to develop a classifier, including, feature generation and selection. The fuzzy set theory is one","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134634595","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":"KST 2023 Cover Page","authors":"","doi":"10.1109/kst57286.2023.10086890","DOIUrl":"https://doi.org/10.1109/kst57286.2023.10086890","url":null,"abstract":"","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115475647","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":"An Efficient Medical Records Access Control with Auditable Outsourced Encryption and Decryption","authors":"S. Fugkeaw, Len Wirz, Lyhour Hak","doi":"10.1109/KST57286.2023.10086904","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086904","url":null,"abstract":"Existing access control schemes for IoT-Cloud-based settings generally focus on investigating the fine-grained access featured with the lightweight decryption. However, these requirements are not adequate for sensitive and high volumes of data such as IoT healthcare data that is outsourced in the cloud. In this paper, we proposed a secure, fine-grained, and batch-auditable access control scheme, that supports both lightweight encryption and decryption for outsourced IoT-based electronic medical records (EMRs). Technically, our proposed scheme fully offloads a ciphertext-policy attribute-based (CP-ABE) encryption and decryption to the fog nodes to minimize the communication and computation cost for both data owners and data users. We employed blockchain to store the record’s indices and access transactions and developed smart contracts to automate user authentication and verification. In addition, we developed a ciphertext auditing algorithm to efficiently handle batch auditing. For the evaluation, we conducted comparative experiments to show that our scheme is more efficient than related works.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114414604","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":"Skin Video-based Blood Pressure Approximation Using CHROM with LSTM-NN","authors":"Chayanin Lumyong, Nutcha Yodrabum, K. Winaikosol, Taravichet Titijaroonroj","doi":"10.1109/KST57286.2023.10086816","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086816","url":null,"abstract":"The measurement of blood pressure (BP) is an essential step in clinical practice. It is used to determine the patient’s BP, which reflects the condition of the patient. Recently, there is a solution for extracting, non-invasively and with no contact, a blood pressure indicator from electrical signal like Photoplethysmography (PPG), called remote-Photoplethysmography (rPPG). This rPPG signal can be used to estimate from a video clip several vital physiological indicators for humans, especially, systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP). This paper proposed a computer method for blood pressure approximation from an input video. A chrominance method, or CHROM, was used to extract rPPG signal from a given video before forwarding it to estimate SBP and DBP values by LSTM-NN. Afterwards, MAP value was determined from SBP and DBP values by a weighting score technique. Experimental results showed that CHROM achieved the lowest mean absolute error (MAE) at 14.04, 8.37, and 9.78 for the SBP, DBP, and MAP, respectively, when compared among NN, RNN, and GRU.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134282995","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":"Information Extraction from Indonesian Crime News with Named Entity Recognition","authors":"Roy Rachman Sedik, A. Romadhony","doi":"10.1109/KST57286.2023.10086789","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086789","url":null,"abstract":"Information Extraction on crime domain is the process of extracting information related to crime event. A prior study of crime information extraction on Indonesian text has been carried out by utilizing features from Part-of-Speech tagging and Dependency Parsing. However, there are some misclassifications, especially in location and date/time extraction. The misclassification is mainly due to the system was not able to identify several named entities. In this study, we propose a system capable of extracting criminal information on Indonesian online news by utilizing named entity recognition, with the focus to extract crime location and time. We use Support Vector Machine (SVM) to classify crime type. We evaluate the proposed system performance by comparing with the gold label. The test results show that crime type classification has an overall performance of 92%, the Crime Location Extraction has F1 score of 90.8%, and for Crime Date Extraction the F1 score is 94,1%. Based on analysis, improvement should be conducted especially on Crime Location extraction. Identification of various date time format is also important to be explored further.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115452445","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 Dynamic and Efficient Crypto-Steganography System for Securing Multiple Files in Cloud","authors":"S. Fugkeaw, Narinthorn Chinvorarat, Nutchanon Charnwutiwong, Korn Chaisuwan, Worapas Pruktipinyopap","doi":"10.1109/KST57286.2023.10086908","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086908","url":null,"abstract":"Traditional steganography is generally based on the way of hiding payloads into a cover image. In this way, the quality of the visibility is subject to the size of cover image and the payload size. Existing works provided the attempts to manage multiple payloads to multiple cover images simultaneously. However, the secure and fine-grained access control for stego images has not been addressed. In this paper, we propose a system scheme called CryptSteg to support a secure and fine-grained data hidden in the image files shared on cloud. Essentially, we integrate the ciphertext policy-attribute based encryption (CP-ABE) and the symmetric encryption to secure the payload and the secret key in the cryptographic steganography setting. In addition, we proposed an algorithm to embed the ciphertext payload into multiple cover images. For the evaluation, we conducted the experiment to demonstrate the efficiency of our proposed scheme.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115460896","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":"Design and Implementation of Fast and Secure SSO Authentication for Multi-Application Services Deployed in Cloud","authors":"S. Fugkeaw, Intanont Langsanam, Hasatorn Saviphan","doi":"10.1109/KST57286.2023.10086933","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086933","url":null,"abstract":"This paper presents the design and implementation of a cloud-based Single Sign-On (SSO) authentication system called D-IAM that supports fast and secure SSO authentication for multi-application hosted on cloud computing. The system consists of three main modules including Identity and single sign-on (SSO) Authentication module, OAuth system, and authorization system. At a core of our proposed scheme, we introduced the secure user identification and SSO authentication method leveraging the secure identification and authentication and OAuth 2.0. We implemented the multi-thread programming to enhance the SSO token generation performance for supporting a high number of user access requests. For the system evaluation, we presented the implementation of our prototype system and conducted the experiments to substantiate the correctness of the functionality and performance of D-IAM system.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126889003","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":"OWADIS: Rapid Discovery of OWASP10 Vulnerability based on Hybrid IDS","authors":"Len Wirz, Asipan Ketphet, Nattapol Chiewnawintawat, Rinrada Tanthanathewin, S. Fugkeaw","doi":"10.1109/KST57286.2023.10086878","DOIUrl":"https://doi.org/10.1109/KST57286.2023.10086878","url":null,"abstract":"Rapid advancements in internet applications introduce new vulnerabilities and threats that malicious actors are keen to exploit. These activities are becoming more versatile and challenging to address. In addition to implementing firewalls to control the inbound and outbound network traffic, an intrusion detection system (IDS) is commonly employed to monitor the network for malicious activities and policy violations. However, most IDSs are generally designed to monitor network traffic. They are incapable to detect the vulnerabilities embedded in the legitimate packets, especially the vulnerabilities targeting web applications. In this paper, we propose a cloud-based IDS with an emphasis on the detection of OWASP Top 10 Injection vulnerabilities, combined with additional common vulnerabilities such as brute-forcing and session hijacking. Furthermore, DDoS attacks, which are commonly seen, can also be detected with our proposed adaptable HTTP flooding detection engine. We also provide the evaluation to show that our proposed scheme provides fewer false positives than SNORT and gives efficient system throughput based on the leverage of Kafka and Spark streaming.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124383450","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}