• Title/Summary/Keyword: Face privacy

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Privacy-Preserving Key-Updatable Public Key Encryption with Keyword Search Supporting Ciphertext Sharing Function

  • Wang, Fen;Lu, Yang;Wang, Zhongqi;Tian, Jinmei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.266-286
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    • 2022
  • Public key encryption with keyword search (PEKS) allows a user to make search on ciphertexts without disclosing the information of encrypted messages and keywords. In practice, cryptographic operations often occur on insecure devices or mobile devices. But, these devices face the risk of being lost or stolen. Therefore, the secret keys stored on these devices are likely to be exposed. To handle the key exposure problem in PEKS, the notion of key-updatable PEKS (KU-PEKS) was proposed recently. In KU-PEKS, the users' keys can be updated as the system runs. Nevertheless, the existing KU-PEKS framework has some weaknesses. Firstly, it can't update the keyword ciphertexts on the storage server without leaking keyword information. Secondly, it needs to send the search tokens to the storage server by secure channels. Thirdly, it does not consider the search token security. In this work, a new PEKS framework named key-updatable and ciphertext-sharable PEKS (KU-CS-PEKS) is devised. This novel framework effectively overcomes the weaknesses in KU-PEKS and has the ciphertext sharing function which is not supported by KU-PEKS. The security notions for KU-CS-PEKS are formally defined and then a concrete KU-CS-PEKS scheme is proposed. The security proofs demonstrate that the KU-CS-PEKS scheme guarantees both the keyword ciphertext privacy and the search token privacy. The experimental results and comparisons bear out that the proposed scheme is practicable.

IoT Security and Machine Learning

  • Almalki, Sarah;Alsuwat, Hatim;Alsuwat, Emad
    • International Journal of Computer Science & Network Security
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    • v.22 no.5
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    • pp.103-114
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    • 2022
  • The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.

Personal Information Protection Recommendation System using Deep Learning in POI (POI 에서 딥러닝을 이용한 개인정보 보호 추천 시스템)

  • Peng, Sony;Park, Doo-Soon;Kim, Daeyoung;Yang, Yixuan;Lee, HyeJung;Siet, Sophort
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.377-379
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    • 2022
  • POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

A Study on Human-Centered IT Utilization in Caring for Elderly People Who Live Alone (독거노인 돌봄에 있어 인간중심의 IT 활용방안에 관한 연구)

  • Choi, So-Yun
    • Journal of Digital Convergence
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    • v.20 no.2
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    • pp.455-462
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    • 2022
  • This study was conducted to find ways to utilize human-centered IT in caring for elderly people who live alone. Through focus group interviews with experts, this study investigated the problems with delivery system, and ethical issues. Problems such as lack of trust, supplier-centered care, and uniform service provision were derived as major problems in the delivery system. These findings indicate that IT should be used as an auxiliary means of face-to-face services and to be controllable and convenient. Issues such as "guaranteeing the right to self-determination," "protecting privacy," "sufficiently guaranteeing the right to know," and "encompassing blind spots" were raised as important ethical issues related to human-centered IT utilization. Based on the research results, this study presented the necessity of designing user-centered information technology and the necessity of developing ethical indicators for the use of human-centered technology.

Personal Information Protection in Digital Era -Reviewing Personal information protection Act- (디지털시대의 개인정보보호 - 새로운 개인정보보호법을 중심으로)

  • Yoo, Jong-Lak
    • Journal of Digital Convergence
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    • v.9 no.6
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    • pp.81-90
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    • 2011
  • Companies using internet as a kind of marketing means are increasing rapidly according to the expansion trend of e-commerce through internet and consumers also use internet as the common means of purchasing necessary articles. E-commerce using internet has advantages without limitation to temporal and spatial accessibility and general consumers and unspecified individuals also use internet to purchase their goods as well as general transactions such as advertisement, contract, payment and claim settlement. 'In the age of information, invasion of personal information resulted from the development of information and communication technology is one of the greatest problems all the countries in the world face. Therefore, Personal information protection Act is one of basic laws to protect personal information and rights and it is also an essential law in the age of information. In that sense, new Personal information protection Act is the advanced act containing various items to minimize the national damages from the leaking of private information and protect right to informational self-determination in the information society. It is expected that this legislation contributes to reduce the leaking of private information, enhance the level of privacy protection and develop privacy related industries. However, active participation of all members of our society and improvement of their recognition should be preceded for the rational and legal use of private information and the settlement of its protection culture. While the purpose of Personal information protection Act can protect privacy from collection, leaking, misuse and abuse of private information and enhance national interests and protect personal dignity and value, it also must perform the roles of balancing privacy protection with liberal information flow.

Inference of birthplaces of users with public information in FaceBook (페이스북 공개 정보를 이용한 사용자 출생지 추론)

  • Choi, Daeseon;Lee, Younho
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.2
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    • pp.431-434
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    • 2014
  • This paper shows the users' birthplace information can be inferred with only the public information in FaceBook SNS. Through experiments with various machine learning algorithms and various parameters, we have found that SVM algorithm with the location of the highschool, the current address, and the graduate year of highschool performs best for the inference, as this can infer 78% of users' birthplaces correctly. Since the birthplace information is used for various security purpose such as questions for getting the forgotten password and a part of korean residence registration number, this is a non-trival security breach and users need be cautious about it.

Ethical Conducts in Qualitative Research Methodology :Participant Observation and Interview Process

  • KANG, Eungoo;HWANG, Hee-Joong
    • Journal of Research and Publication Ethics
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    • v.2 no.2
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    • pp.5-10
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    • 2021
  • Purpose: Ethical behaviors become more salient when researchers utilize face-to-face interviews and observation with vulnerable groups or communities, which may be unable to express their emotions during the sessions. The present research aims to investigate ethical behaviors while conducting research have resonance due to the deep nature of observation and interview data collection methods. Research design, data and methodology: The present research obtained non-numeric (Textual) data based on prior literature review to investigate Ethical Conducts in Qualitative Research. Non-numeric data differs from numeric data in how the data is collected, analyzed and presented. It is important to formulate written questions and adopt them what the method claims for the researcher to understand the studied phenomenon. Results: Our findings show that while conducting qualitative research, researchers must adhere to the following ethical conducts; upholding informed consent, confidentiality and privacy, adhering to beneficence's principle, practicing honesty and integrity. Each ethical conduct is discoursed in detail to realize more information on how it impacts the researcher and research participants. Conclusions: The current authors concludes that five ethical conducts are important for realizing extensive and rich information during qualitative research and may be exploited in implementing research policies for researchers utilizing observation and interviews methods of data collection.

Secure Biometric Hashing by Random Fusion of Global and Local Features

  • Ou, Yang;Rhee, Kyung-Hyune
    • Journal of Korea Multimedia Society
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    • v.13 no.6
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    • pp.875-883
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    • 2010
  • In this paper, we present a secure biometric hashing scheme for face recognition by random fusion of global and local features. The Fourier-Mellin transform and Radon transform are adopted respectively to form specialized representation of global and local features, due to their invariance to geometric operations. The final biometric hash is securely generated by random weighting sum of both feature sets. A fourfold key is involved in our algorithm to ensure the security and privacy of biometric templates. The proposed biometric hash can be revocable and replaced by using a new key. Moreover, the attacker cannot obtain any information about the original biometric template without knowing the secret key. The experimental results confirm that our scheme has a satisfactory accuracy performance in terms of EER.

Estimation and Watermarking of Motion Parameters in Model Based Image Coding

  • Park, Min-Chul
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.1264-1267
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    • 2002
  • In order to achieve an advanced human-computer interface system, it is necessary to analyze and synthesize facial motions just as they are in an interactive way, and to protect them from unwanted use and/or illegal use for their privacy, various uses in applications and the costs of obtaining motion parameters. To estimate facial motion, a method of using skin color distribution, luminance, and geometrical information of a face is employed. Digital watermarks are embedded into facial motion parameters and then these parameters are scrambled so that it cannot be understood. Experimental results show high accuracy and efficiency of the proposed estimation method and the usefulness of the proposed watermarking method.

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Detection and Blocking of a Face Area Using a Tracking Facility in Color Images (컬러 영상에서 추적 기능을 활용한 얼굴 영역 검출 및 차단)

  • Jang, Seok-Woo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.10
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    • pp.454-460
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    • 2020
  • In recent years, the rapid increases in video distribution and viewing over the Internet have increased the risk of personal information exposure. In this paper, a method is proposed to robustly identify areas in images where a person's privacy is compromised and simultaneously blocking the object area by blurring it while rapidly tracking it using a prediction algorithm. With this method, the target object area is accurately identified using artificial neural network-based learning. The detected object area is then tracked using a location prediction algorithm and is continuously blocked by blurring it. Experimental results show that the proposed method effectively blocks private areas in images by blurring them, while at the same time tracking the target objects about 2.5% more accurately than another existing method. The proposed blocking method is expected to be useful in many applications, such as protection of personal information, video security, object tracking, etc.