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نتیجه جستجو - anonymization

تعداد مقالات یافته شده: 15
ردیف عنوان نوع
1 Proposal of anonymization dictionary using disclosed statements by business operators
پیشنهاد فرهنگ لغت ناشناس با استفاده از اظهارات افشا شده توسط اپراتورهای تجاری-2022
Increasing the number of business operators using anonymously processed information is a critical privacy topic in Japan. To promote the use of the information, an ‘‘anonymization dictionary’’ is proposed and implemented. The dictionary is the system that shares usecases regarding the manner by which business operators produce and provide anonymously processed information. To develop this system, two technical difficulties are resolved: the lack of (i) a method to acquire the use-cases and (ii) a data structure to store the use-cases. In terms of (i), disclosed statements that specify the production and provisioning processes for anonymously processed information is focused. To recognize the statements described in the business operators’ webpages as the use-cases, a web crawler that acquires the statements is developed. The crawler acquires 331 use-cases (statements) in a short duration. In terms of (ii), to define a concrete data structure to store anonymously processed information use-cases, the structure of the use-cases acquired is analyzed. The use-cases are stored into the structure and then in the DB of the dictionary application. This enables a search function to be provided for identifying the necessary use-cases and organizing use-cases in a readable form to the business operators.
keywords: اطلاعات پردازش شده به صورت ناشناس | ناشناس سازی | اظهارات افشا شده | خزنده | حفظ حریم خصوصی | Anonymously processed information | Anonymization | Disclosed statements | Crawler | Privacy preservation
مقاله انگلیسی
2 Privacy Preservation for Social Networks Sequential Publishing
حفظ حریم خصوصی برای انتشارات متوالی شبکه های اجتماعی-2020
The proliferation of social networks allowed creating a big quantity of data about users and their relationships. Such data contain much private information. Therefore, anonymization is required before publishing the data for data mining purposes (scientific research, marketing, decision support, etc). Most of the anonymization works in social networks focus on publishing one instance while not considering the need for anonymizing sequential releases. However, many cases show that sequential releases may infer private information even though individual instances are anonymized. This paper studies the privacy issues of sequential releases and proposes a privacy preserving solution for this case. The proposed solution ensures three privacy requirements (users’ privacy, groups’ privacy and edges’ privacy), and it considers the case where many users and groups may share the same profiles. Some experiments over some complex queries show that the utility of the released data is better preserved than other solutions, with regard to the privacy of users, groups and edges.
Keywords: Privacy preserving | Social networks | Anonymization | Sequential releases
مقاله انگلیسی
3 درآوردن شبکه های اجتماعی دارای مقیاس آزاد از حالت بی نامی با استفاده از روش قسمت بندی طیفی
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 5 - تعداد صفحات فایل doc فارسی: 15
داده های شبکه های اجتماعی به صورت گسترده ای با بخشهای ثالث به اشتراک گذاشته می شوند، ارسال می شوند و منتشر می شوند که منجر به ایجاد خطر افشای اطلاعات محرمانه می شود. اگرچه تامین کننده شبکه همیشه قبل از انتشار آن نگران داده ها می باشد اما حمله کننده ها می توانند هنوزهم داده های بی نام را برطبق اطلاعات کمکی جمع آوری شده بازیابی کنند. ما در این مقاله مشکل از حالت بی نام درآوردن را به مشکل هماهنگ سازی گره در گراف تبدیل می کنیم و روش درآوردن از حالت بی نامی می تواند تعداد گره هایی که باید در هر بار هماهنگ سازی شوند را کاهش می دهد. به علاوه، ما از روش قسمت بندی طیفی برای تقسیم بندی گراف اجتماعی به زیرگراف های گسسته استفاده می کنیم و این روش می تواند به صورت موثری برای شبکه های اجتماعی دارای مقیاس بزرگ به کار برده شود و به صورت موازی با استفاده از چندین پردازشگر اجرا شود. درطی تحلیل تاثیر توزیع قانون توانی روی درآوردن از حالت بی نامی، ما از روی قواعد ترکیبی اطلاعات ساختاری و فردی کاربران را بررسی می کنیم که این کار اطلاعات مشخصه کاربر را عملی تر می سازد.
مقاله ترجمه شده
4 The users’ perspective on the privacy-utility trade-offs in health recommender systems
دیدگاه کاربران در مورد مبادلات مربوط به حریم خصوصی در سیستم های توصیه کننده سلامت-2019
Privacy is a major good for users of personalized services such as recommender systems. When applied to the field of health informatics, privacy concerns of users may be amplified, but the possible utility of such services is also high. Despite availability of technologies such as k-anonymity, differential privacy, privacy-aware rec- ommendation, and personalized privacy trade-offs, little research has been conducted on the users’ willingness to share health data for usage in such systems. In two conjoint-decision studies (sample size ???? = 521 ), we in- vestigate importance and utility of privacy-preserving techniques related to sharing of personal health data for k-anonymity and differential privacy. Users were asked to pick a preferred sharing scenario depending on the recipient of the data, the benefit of sharing data, the type of data, and the parameterized privacy. Users disagreed with sharing data for commercial purposes regarding mental illnesses and with high de-anonymization risks but showed little concern when data is used for scientific purposes and is related to physical illnesses. Suggestions for health recommender system development are derived from the findings.
Keywords: Recommender systems | Health recommender system | Privacy | Privacy trade-off | Health informatics | Conjoint study
مقاله انگلیسی
5 A new technique ensuring privacy in big data: K-anonymity without prior value of the threshold k
یک تکنیک جدید مطمعن حریم خصوصی در داده های بزرگ: K-anonymity بدون مقدار قبلی آستانه k-2018
Big data has become omnipresent and crucial for many application domains. Big data makes reference to the explosive quantity of data generated in today’s society that might contain personally identifiable information (PII). That’s why the challenge from the point of view of data privacy is one of the major hurdles for the application of big data. In that situation, several techniques were exposed in order to ensure privacy in big data including generalization, randomization and cryptographic techniques as well. It is well known that there exist two main types of attributes in the literature, quasi identifier and sensitive attributes. In this paper, we are going to focus on quasi identifier attributes. Over the years, k-anonymity has been treated with great interest as an anonymization technique ensuring privacy in big data when we are dealing with quasi identifier attributes. Despite the fact that many algorithms of k-anonymity have been proposed, most of them admit that the threshold k of k-anonymity has to be known before anonymizing the data set. Here, a novel way in applying k-anonymity for quasi identifier attributes is presented. It’s a new algorithm called “k-anonymity without prior value of the threshold k”. Our proposed algorithm was experimentally evaluated using a test table of quasi identifier attributes. Furthermore, we highlight all the steps of our proposed algorithm with detailed comments.
Keywords: k-anonymity; quasi identifier attributes; big data; anonymization; privacy
مقاله انگلیسی
6 Implementing a Data Management Infrastructure for Big HealthCare Data
پیاده سازی یک زیرساخت مدیریت داده برای داده های سلامت بزرگ-2018
The advancements in healthcare have brought to the fore the need for flexible access to health-related information and created an ever-growing demand for efficient data management infrastructures. To this direction, in this paper, we present an effective and efficient data management infrastructure implemented for the iManageCancer EU project. The architecture focuses on enabling data access to multiple, heterogeneous and diverse data source that are initially available in a data lake. Parts of these data are integrated and semantically uplifted using a modular ontology. This integration can be either at run-time or through an ETL process ensuring efficient access to the integrated information. A unique feature of out platform is that it allows the uninterrupted, continuous evolution of ontologies/terminologies. Finally, summarization tools enable the quick understanding of the available information, whereas APIs and anonymization services ensure the secure access to the requested information
مقاله انگلیسی
7 نظارت جمعی و گزینه های سیاست فن آوری: بهبود امنیت ارتباطات خصوصی
سال انتشار: 2017 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 26
افشاگری های اسنودن در سال 2013 شعله بحث شدید در مشروعیت و وسعت عملیات جاسوسی که ناظر بر اینترنت و ارتباطات از راه دور در سراسر جهان بود را شعله ور کرد. حمله مداوم به حوزه خصوصی افراد در سراسر جهان توسط دولت ها و شرکت ها موضوعی است که بطور کافی با استفاده از اقدامات فنی و سازمانی فعلی صورت گرفته است. این مقاله استدلال می کند که به منظور حفظ اینترنت حیاتی و فعال، زیرساخت های اساسی آن باید بطور قابل توجهی تقویت شود. ما تعدادی گزینه های فنی و سیاسی، که به بهبود امنیت در اینترنت کمک می کند،پیشنهاد می کنیم. بر بحث پیرامون رمزگذاری و ناشناخته ، و همچنین در سیاست های مقابله با آسیب پذیری های نرم افزار و سخت افزار و ضعف معماری اینترنت تمرکز دارد.
کلید واژه ها: نظارت | سیاست | رمزگذاری | حریم خصوصی
مقاله ترجمه شده
8 Efficient location privacy algorithm for Internet of Things (IoT) services and applications
الگوریتم حریم خصوصی کارامد برای خدمات اینترنت اشیاء و برنامه های کاربردی -2017
Location-based Services (LBS) have become a very important area for research with the rapid development of Internet of Things (IoT) technology and the ubiquitous use of smartphones and social networks in our daily lives. Although users can enjoy a lot of flexibility and conveniences from the LBS with IoT, they may also lose their privacy. Untrusted or malicious LBS servers with all users’ information can track users in various ways or release personal data to third parties. In this work, we first analyze the current dummy-location selection (DLS) algorithm—an efficient location privacy preservation approach and design an attack algorithm for DLS (ADLS) for test emerging IoT security. For efficiently preserving users location privacy, we propose a novel dummy location privacy-preserving (DLP) algorithm by considering both computational costs and various privacy requirements of different users. Extensive simulation experiments have been carried out to evaluate the efficiency of the proposed schemes. Evaluation results show that the ADLS algorithm has a high probability of identifying the users real location out from chosen dummy locations in the DLS algorithm. Our proposed DLP algorithm has clear advantages over the DLS algorithm in term of lower probability of revealing the users real location and improved computational cost and efficiency (i.e., time, speed, accuracy, and complexity) while preserve the same privacy level as DLS algorithm.
Keywords: Privacy preserving | Location privacy | Location based services | k-anonymization
مقاله انگلیسی
9 A privacy self-assessment framework for online social networks
یک چارچوب خود ارزیابی خصوصی برای شبکه های اجتماعی آنلاین-2017
During our digital social life, we share terabytes of information that can potentially reveal private facts and personality traits to unexpected strangers. Despite the research efforts aiming at providing efficient solutions for the anonymization of huge databases (including networked data), in online social networks the most powerful privacy protection “weapons” are the users themselves. However, most users are not aware of the risks derived by the indiscriminate disclosure of their personal data. Moreover, even when social networking platforms allow their participants to control the privacy level of every published item, adopting a correct privacy policy is often an annoying and frustrating task and many users prefer to adopt simple but extreme strategies such as “visible-to-all” (exposing themselves to the highest risk), or “hidden-to-all” (wasting the positive social and economic potential of social networking websites). In this paper we propose a theoretical framework to i) measure the privacy risk of the users and alert them whenever their privacy is compromised and ii) help the users customize semi-automatically their privacy settings by limiting the number of manual operations. By investigating the relationship between the privacy measure and privacy preferences of real Facebook users, we show the effectiveness of our framework.
Keywords: Privacy measures | Online social networks | Active learning
مقاله انگلیسی
10 Anonymizing popularity in online social networks with full utility
محبوبیت ناشناس در شبکه های اجتماعی آنلاین با ابزار کامل-2017
With the rapid growth of social network applications, more and more people are participating in social networks. Privacy protection in online social networks becomes an important issue. The illegal disclosure or improper use of users’ private information will lead to unaccepted or unexpected consequences in people’s lives. In this paper, we concern on authentic popularity disclosure in online social networks. To protect users’ privacy, the social networks need to be anonymized. However, existing anonymization algorithms on social networks may lead to nontrivial utility loss. The reason is that the anonymization process has changed the social network’s structure. The social network’s utility, such as retrieving data files, reading data files, and sharing data files among different users, has decreased. Therefore, it is a challenge to develop an effective anonymization algorithm to protect the privacy of user’s authentic popularity in online social networks without decreasing their utility. In this paper, we first design a hierarchical authorization and capability delegation (HACD) model. Based on this model, we propose a novel utility-based popularity anonymization (UPA) scheme, which integrates proxy re-encryption with keyword search techniques, to tackle this issue. We demonstrate that the proposed scheme can not only protect the users’ authentic popularity privacy, but also keep the full utility of the social network. Extensive experiments on large real-world online social networks confirm the efficacy and efficiency of our scheme.
Keywords: Anonymization algorithm | Authentic popularity privacy | Social network utility
مقاله انگلیسی
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