{"_buckets": {"deposit": "fbcc0d69-9bfa-4a47-a13d-6b34a70db11c"}, "_deposit": {"created_by": 1, "id": "864", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "864"}, "status": "published"}, "_oai": {"id": "oai:ir.soken.ac.jp:00000864", "sets": ["19"]}, "author_link": ["0", "0", "0"], "item_1_biblio_info_21": {"attribute_name": "書誌情報（ソート用）", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2007-03-23", "bibliographicIssueDateType": "Issued"}, "bibliographic_titles": [{}]}]}, "item_1_creator_2": {"attribute_name": "著者名", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "HUDA, MD. Nurul"}], "nameIdentifiers": [{"nameIdentifier": "0", "nameIdentifierScheme": "WEKO"}]}]}, "item_1_creator_3": {"attribute_name": "フリガナ", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "モハマドフーダヌルル"}], "nameIdentifiers": [{"nameIdentifier": "0", "nameIdentifierScheme": "WEKO"}]}]}, "item_1_date_granted_11": {"attribute_name": "学位授与年月日", "attribute_value_mlt": [{"subitem_dategranted": "2007-03-23"}]}, "item_1_degree_grantor_5": {"attribute_name": "学位授与機関", "attribute_value_mlt": [{"subitem_degreegrantor": [{"subitem_degreegrantor_name": "総合研究大学院大学"}]}]}, "item_1_degree_name_6": {"attribute_name": "学位名", "attribute_value_mlt": [{"subitem_degreename": "博士（情報学）"}]}, "item_1_description_1": {"attribute_name": "ID", "attribute_value_mlt": [{"subitem_description": "2007039", "subitem_description_type": "Other"}]}, "item_1_description_12": {"attribute_name": "要旨", "attribute_value_mlt": [{"subitem_description": "A multi-party computation (MPC) allows η parties to compute an agreed-upon func- \u003cbr /\u003etion of their inputs and every party learns the correct function output. To solve a \u003cbr /\u003emulti-party computation problem (MPCP), the participants may need to share their \u003cbr /\u003eprivate data (inputs) between one another, resulting in data privacy loss. The key \u003cbr /\u003eresearch issue that has been addressed in this thesis is - how to solve multi-party \u003cbr /\u003ecomputation problems without disclosing anyone\u0027s private data to others. \u003cbr /\u003e\u003cbr /\u003e   Firstly, by studying and analyzing the traditional computational models, we have \u003cbr /\u003edevised a privacy loss model for multi-party computation problems and proposed a \u003cbr /\u003enovel metric, called the Min privacy metric, for quantitatively measuring the amount \u003cbr /\u003eof data privacy loss in solving the MPCPs. Then, we have presented a mobile agent- \u003cbr /\u003ebased scheduling algorithm that applies pseudonymization technique to reduce data \u003cbr /\u003eprivacy loss. Finally, we have proposed the security system design, including security \u003cbr /\u003epolicies and security architecture, of an agent server platform for enhancing data \u003cbr /\u003eprivacy protection while solving the MPCPs.\u003cbr /\u003e\u003cbr /\u003e   The privacy loss model has identified three factors affecting the amount of privacy \u003cbr /\u003eloss in solving the MPCPs: (1) the fraction ofprivate data which is shared with others, \u003cbr /\u003e(2) the probability of associating the shared private data with the data subject, and \u003cbr /\u003e(3) the probability of disclosing the shared private data to unauthorized parties.\u003cbr /\u003ePrivacy loss can be reduced by any mechanisms which reduces the values of any \u003cbr /\u003eof the three factors. The proposed Min privacy metric accounts for the number of \u003cbr /\u003eparticipants that lose their private data and the amount of private data disclosed to \u003cbr /\u003eunauthorized parties, regardless of how many parties they are revealed to. \u003cbr /\u003e\u003cbr /\u003e  Existing scheduling algorithms aim for a global objective function. As a result,\u003cbr /\u003ethey incur performance penalties in computational complexity and data privacy. This \u003cbr /\u003ethesis describes a mobile agent-based scheduling scheme called Efiicient and Privacy-\u003cbr /\u003eaware Meeting Scheduling (EPMS), which results in a tradeoff arnong complexity,\u003cbr /\u003eprivacy, and global utility for scheduling multiple events concurrently. We have intro- \u003cbr /\u003educed multiple criteria for evaluating privacy in the meeting scheduling problem. A \u003cbr /\u003ecommon computational space has been utilized in EPMS for reducing the complexity \u003cbr /\u003eand pseudonymization technique has been applied to reduce the privacy loss in the \u003cbr /\u003escheduling problem. The analytical results show that EPMS has a polynomial time \u003cbr /\u003ecomputational complexity. In addition, simulation results show that the obtained \u003cbr /\u003eglobal utility for scheduling multiple meetings with EPMS is close to the optimal \u003cbr /\u003elevel and the resulting privacy loss is less than for those in extsting algorithms. \u003cbr /\u003e   Cryptography-based aJgorithms for MPCPs are either too complex to be used \u003cbr /\u003epractically or applicable only to the specific applications for which they have been \u003cbr /\u003edeveloped. In addition, traditional (non-cryptography-based) algorithms do not pro- \u003cbr /\u003evide good privacy protection for MPCPs. We have proposed a novel privacy pro- \u003cbr /\u003etection mechanism in which MPCPs are solved by mobile agents using traditional \u003cbr /\u003ealgorithms at an agent server platform, called isolated Closed-door One-way Plat- \u003cbr /\u003eform (iCOP). The participating mobile agents are trapped into iCOP where they \u003cbr /\u003eare allowed to share their private information to solve the problem using traditional \u003cbr /\u003ealgorithms. However, they are protected from disclosing the shared private infor- \u003cbr /\u003emation to the outside world. The enforcement of the security policies protects the \u003cbr /\u003eparticipating agents from sending anything other than the computational result to \u003cbr /\u003ethe users. The security and privacy analysis illustrates that the proposed mechanism \u003cbr /\u003eprovides very good privacy protection if the participants solve the problem with dis- \u003cbr /\u003etributed algorithms and can provide complete privacy protection if the participants \u003cbr /\u003eexchange inputs within the iCOP and each of them solve the problem with centralized \u003cbr /\u003ealgorithms. Finally, experimental evaluation shows that the proposed agent platform \u003cbr /\u003esecurity system significantly enhances privacy protection while solving many MPCPs \u003cbr /\u003ewith traditional algorithms.\u003cbr /\u003e ", "subitem_description_type": "Other"}]}, "item_1_description_18": {"attribute_name": "フォーマット", "attribute_value_mlt": [{"subitem_description": "application/pdf", "subitem_description_type": "Other"}]}, "item_1_description_7": {"attribute_name": "学位記番号", "attribute_value_mlt": [{"subitem_description": "総研大甲第1054号", "subitem_description_type": "Other"}]}, "item_1_select_14": {"attribute_name": "所蔵", "attribute_value_mlt": [{"subitem_select_item": "有"}]}, "item_1_select_8": {"attribute_name": "研究科", "attribute_value_mlt": [{"subitem_select_item": "複合科学研究科"}]}, "item_1_select_9": {"attribute_name": "専攻", "attribute_value_mlt": [{"subitem_select_item": "17 情報学専攻"}]}, "item_1_text_10": {"attribute_name": "学位授与年度", "attribute_value_mlt": [{"subitem_text_value": "2006"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "HUDA, MD. Nurul", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "0", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2016-02-17"}], "displaytype": "simple", "download_preview_message": "", "file_order": 0, "filename": "甲1054_要旨.pdf", "filesize": [{"value": "322.2 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_11", "mimetype": "application/pdf", "size": 322200.0, "url": {"label": "要旨・審査要旨", "url": "https://ir.soken.ac.jp/record/864/files/甲1054_要旨.pdf"}, "version_id": "d6033db3-b71e-44e8-a2a2-88b62c17bac0"}, {"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2016-02-17"}], "displaytype": "simple", "download_preview_message": "", "file_order": 1, "filename": "甲1054_本文.pdf", "filesize": [{"value": "14.1 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_11", "mimetype": "application/pdf", "size": 14100000.0, "url": {"label": "本文", "url": "https://ir.soken.ac.jp/record/864/files/甲1054_本文.pdf"}, "version_id": "de08fa80-539a-41cf-9bb2-c14cca6a3402"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "thesis", "resourceuri": "http://purl.org/coar/resource_type/c_46ec"}]}, "item_title": "A Mobile Agent-based Privacy Protection Mechanism in Solving Multi-party Computation Problems", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "A Mobile Agent-based Privacy Protection Mechanism in Solving Multi-party Computation Problems"}, {"subitem_title": "A Mobile Agent-based Privacy Protection Mechanism in Solving Multi-party Computation Problems", "subitem_title_language": "en"}]}, "item_type_id": "1", "owner": "1", "path": ["19"], "permalink_uri": "https://ir.soken.ac.jp/records/864", "pubdate": {"attribute_name": "公開日", "attribute_value": "2010-02-22"}, "publish_date": "2010-02-22", "publish_status": "0", "recid": "864", "relation": {}, "relation_version_is_last": true, "title": ["A Mobile Agent-based Privacy Protection Mechanism in Solving Multi-party Computation Problems"], "weko_shared_id": -1}