無可信第三方的數(shù)據(jù)匿名化收集協(xié)議

周治平; 李智聰

doi:10.11999/JEIT180595

無可信第三方的數(shù)據(jù)匿名化收集協(xié)議

doi: 10.11999/JEIT180595

周治平^{1, 2, ,},
李智聰¹

1.
江南大學(xué)物聯(lián)網(wǎng)工程學(xué)院? ?無錫? ?214122
2.
江南大學(xué)物聯(lián)網(wǎng)技術(shù)應(yīng)用教育部工程研究中心? ?無錫? ?214122

詳細(xì)信息

作者簡(jiǎn)介:
周治平：男，1962 年生，博士，教授，研究方向?yàn)闄z測(cè)技術(shù)與自動(dòng)化裝置、信息安全等

李智聰：男，1992 年生，碩士生，研究方向?yàn)槲锫?lián)網(wǎng)安全認(rèn)證

通訊作者:
周治平　zzp@jiangnan.edu.cn

中圖分類號(hào): TP309.2
計(jì)量
- 文章訪問數(shù): 1936
- HTML全文瀏覽量: 932
- PDF下載量: 60
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2018-06-19
- 修回日期: 2019-03-04
- 網(wǎng)絡(luò)出版日期: 2019-03-25
- 刊出日期: 2019-06-01

Data Anonymous Collection Protocol without Trusted Third Party

Zhiping ZHOU^{1, 2
, ,},
Zhicong LI¹

1.
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
2.
Engineering Research Center of Internet of Things Technology Applications ofMinistry of Education, Jiangnan University, Wuxi 214122, China

摘要

摘要: 針對(duì)半誠(chéng)信的數(shù)據(jù)收集者對(duì)包含敏感屬性(SA)數(shù)據(jù)收集和使用過程中可能造成隱私泄露問題，該文在傳統(tǒng)模型中增加實(shí)時(shí)的數(shù)據(jù)領(lǐng)導(dǎo)者，并基于改進(jìn)模型提出一個(gè)隱私保護(hù)的數(shù)據(jù)收集協(xié)議，確保無可信第三方假設(shè)前提下，數(shù)據(jù)收集者最大化數(shù)據(jù)效用只能建立在K匿名處理過的數(shù)據(jù)基礎(chǔ)上。數(shù)據(jù)擁有者分布協(xié)作的方式參與協(xié)議流程，實(shí)現(xiàn)了準(zhǔn)標(biāo)識(shí)(QI)匿名化后SA的傳輸，降低了數(shù)據(jù)收集者通過QI關(guān)聯(lián)準(zhǔn)確SA值的概率，減弱內(nèi)部標(biāo)識(shí)揭露造成隱私泄露風(fēng)險(xiǎn)；通過樹形編碼結(jié)構(gòu)將SA的編碼值分為隨機(jī)錨點(diǎn)和補(bǔ)償距離兩份份額，由K匿名形成的等價(jià)類成員選舉獲取兩個(gè)數(shù)據(jù)領(lǐng)導(dǎo)者，分別對(duì)兩份份額進(jìn)行聚集和轉(zhuǎn)發(fā)，解除唯一性的網(wǎng)絡(luò)標(biāo)識(shí)和SA值的關(guān)聯(lián)，有效防止外部標(biāo)識(shí)揭露造成的隱私泄露；建立符合該協(xié)議特性的形式化規(guī)則并對(duì)協(xié)議進(jìn)行安全分析，證明了協(xié)議滿足隱私保護(hù)需求。
- 數(shù)據(jù)隱私 /
- 隱私保護(hù) /
- K匿名 /
- 敏感屬性 /
- 匿名化
Abstract: Semi-honest data collectors may cause privacy leaks during the collection and use of Sensitive Attribute (SA) data. In view of the problem, real-time data leaders are added in the traditional model and a privacy-protected data collection protocol based on the improved model is proposed. Without the assumption of trusted third party, the protocol ensures that data collectors maximization data utility can only be established on the basis of K-anonymized data. Data owners participates in the protocol flow in a distributed and collaborative manner to achieve the transmission of SA after the Quasi-Identifier (QI) is anonymized. This reduces the probability that the data collector uses the QI to associate SA values and weakens the risk of privacy leakage caused by internal identity disclosure. It divides the coded value of the SA into two shares of a random anchor point and a compensation distance through the tree coding structure and the members of the equivalent class formed by K-anonymity elect two data leaders to aggregate and forward the two shares respectively, which releases the association between unique network identification and SA values and prevents leakage of privacy caused by external identification effectively. Formal rules are established that meet the characteristics of the protocol and analyze the protocol to prove that the protocol meets privacy protection requirements.
- Data privacy /
- Privacy protection /
- K-anonymity /
- Sensitive Attribute (SA) /
- Anonymization

HTML全文

圖 1 樹形編碼結(jié)構(gòu)圖

下載: 全尺寸圖片幻燈片

圖 2 參與實(shí)體的模型結(jié)構(gòu)

下載: 全尺寸圖片幻燈片

圖 3 協(xié)議有向圖

下載: 全尺寸圖片幻燈片

圖 4 屬性域尺寸和編碼長(zhǎng)度的關(guān)系

下載: 全尺寸圖片幻燈片

圖 5 屬性域尺寸和敵手獲勝概率

下載: 全尺寸圖片幻燈片

表 1 階段1協(xié)議步驟

(1) for ${U_i} \in \text{U}$, $1 \le i \le N$ do
${U_i}$發(fā)送${Q_i}$給${\rm{DC}}$.
(2) ${\rm{DC}}$通過K匿名將$Q$泛化為$G$
for ${G_j} \in \text{G}$, $1 \le j \le M$ do
(3) for ${G_j}$中元組對(duì)應(yīng)的${U_k}$, $1 \le k \le K$ do
${\rm{DC}}$向${U_k}$發(fā)送${G_j}$
if 每個(gè)${U_k}$驗(yàn)證${G_j}$是有效，進(jìn)入階段2
else 終止協(xié)議

下載: 導(dǎo)出CSV

表 2 階段2協(xié)議步驟

(1) for $ {G_j} \in \text{G}$, $ 1 \le j \le M$ do
隨機(jī)選取領(lǐng)導(dǎo)者$ L_1^j$和$ L_2^j$
for $ {G_j}$中元組對(duì)應(yīng)的$ {{U}_{k}}$, $ 1 \le k \le K$ do
發(fā)送$ ({G_j},{R_k})$和$ ({G_j},{D_k})$分別給$ L_1^j$和$ L_2^j$
(2) $ L_1^j$和$ L_2^j$分別聚集$ ({G_j},{R_k})$和$ ({G_j},{D_k})$列表的給$ {\rm{DC}}$
(3) for $ 1 \le i \le N$ do
$ {\rm{DC}}$計(jì)算$ {W_i}{\rm{ = }}{R_i} \oplus {D_i}$
(4) 搜索$ {W_i}$映射的$ {S_i}$得到數(shù)據(jù)列表$ (\text{G},\text{S})$

下載: 導(dǎo)出CSV

參考文獻(xiàn)(18)

曹珍富, 董曉蕾, 周俊, 等. 大數(shù)據(jù)安全與隱私保護(hù)研究進(jìn)展[J]. 計(jì)算機(jī)研究與發(fā)展, 2016, 53(10): 2137–2151. doi: 10.7544/issn1000-1239.2016.20160684

CAO Zhenfu, DONG Xiaolei, ZHOU Jun, et al. Research advances on big data security and privacy preserving[J]. Journal of Computer Research and Development, 2016, 53(10): 2137–2151. doi: 10.7544/issn1000-1239.2016.20160684

包國(guó)華, 王生玉, 李運(yùn)發(fā). 云計(jì)算中基于隱私感知的數(shù)據(jù)安全保護(hù)方法研究[J]. 信息網(wǎng)絡(luò)安全, 2017(1): 84–89. doi: 10.3969/j.issn.1671-1122.2017.01.013

BAO Guohua, WANG Shengyu, and LI Yunfa. Research on data security protection method based on privacy awareness in cloud computing[J]. Netinfo Security, 2017(1): 84–89. doi: 10.3969/j.issn.1671-1122.2017.01.013

IMRUL K and ADRIANA I. Privacy and security in online social networks: A survey[J]. Online Social Networks and Media, 2017, 4(3): 1–21. doi: 10.1109/ICME.2011.6012166

SWEENEY L. k-Anonymity: A model for protecting privacy[J]. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2002, 10(5): 557–570. doi: 10.1142/S0218488502001648

MACHANAVAJJHALA A, GEHRKE J, KIFER D, et al. l-Diversity: Privacy beyond k-anonymity[C]. Proceedings of the 22nd International Conference on Data Engineering, Atlanta, USA, 2006: 24.

LI Ninghui, LI Tiancheng, and VENKATASUBRAMANIAN S. t-Closeness: Privacy beyond k-anonymity and l-diversity[C]. Proceedings of the 23rd International Conference on Data Engineering, Istanbul, Turkey, 2007: 106–115.

DWORK C, KENTHAPADI K, MCSHERRY F, et al. Our data, ourselves: Privacy via distributed noise generation[C]. Proceedings of the 24th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Petersburg, Russia, 2006: 486–503.

DWORK C, NAOR M, PITASSI T, et al. Differential privacy under continual observation[C]. Proceedings of the 42nd ACM symposium on Theory of Computing, Cambridge, Massachusetts, USA, 2010: 715–724.

CLARKE A and STEELE R. A smartphone-based system for population-scale anonymized public health data collection and Intervention[C]. Proceedings of the 47th Hawaii International Conference on System Sciences, Waikoloa, USA, 2014: 2908–2917.

ZHONG Sheng, YANG Zhiqiang, and CHEN Tingting. k-anonymous data collection[J]. Information Sciences, 2009, 179(17): 2948–2963. doi: 10.1016/j.ins.2009.05.004

XUE Mingqiang, PAPADIMITRIOU P, RA?SSI C, et al. Distributed privacy preserving data collection[C]. Proceedings of the 16th International Conference on Database Systems for Advanced Applications, Hongkong, China, 2011: 93–107.

LI Hongtao, GUO Feng, ZHANG Wenyin, et al. (a, k)-Anonymous scheme for privacy-preserving data collection in IoT-based healthcare services systems[J]. Journal of Medical Systems, 2018, 42(3): 56. doi: 10.1007/s10916-018-0896-7

劉琴, 劉旭輝, 胡柏霜, 等. 個(gè)人健康記錄云管理系統(tǒng)中支持用戶撤銷的細(xì)粒度訪問控制[J]. 電子與信息學(xué)報(bào), 2017, 39(5): 1206–1212. doi: 10.11999/JEIT160621

LIU Qin, LIU Xuhui, HU Baishuang, et al. Fine-grained access control with user revocation in cloud-based personal health record system[J]. Journal of Electronics &Information Technology, 2017, 39(5): 1206–1212. doi: 10.11999/JEIT160621

LUO Entao, BHUIYAN M Z A, WANG Guojun, et al. Privacy protector: Privacy-protected patient data collection in IoT-based healthcare systems[J]. IEEE Communications Magazine, 2018, 56(2): 163–168. doi: 10.1109/MCOM.2018.1700364

龔奇源, 楊明, 羅軍舟. 面向關(guān)系-事務(wù)數(shù)據(jù)的數(shù)據(jù)匿名方法[J]. 軟件學(xué)報(bào), 2016, 27(11): 2828–2842. doi: 10.13328/j.cnki.jos.005099

GONG Qiyuan, YANG Ming, and LUO Junzhou. Data anonymization approach for microdata with relational and transaction attributes[J]. Journal of Software, 2016, 27(11): 2828–2842. doi: 10.13328/j.cnki.jos.005099

KIM S and CHUNG Y D. An anonymization protocol for continuous and dynamic privacy-preserving data collection[J]. Future Generation Computer Systems, 2019, 93: 1065–1073. doi: 10.1016/j.future.2017.09.009

VILLADANGOS J, CORDOBA A, FARINA F, et al. Efficient leader election in complete networks[C]. Proceedings of the 13th Euromicro Conference on Parallel, Distributed and Network-Based Processing, Lugano, Switzerland, 2005: 136–143.

羅恩韜, 王國(guó)軍. 移動(dòng)社交網(wǎng)絡(luò)中一種朋友發(fā)現(xiàn)的隱私安全保護(hù)策略[J]. 電子與信息學(xué)報(bào), 2016, 38(9): 2165–2172. doi: 10.11999/JEIT151479

LUO Entao and WANG Guojun. A novel friends matching privacy preserving strategy in mobile social networks[J]. Journal of Electronics &Information Technology, 2016, 38(9): 2165–2172. doi: 10.11999/JEIT151479

相關(guān)文章

施引文獻(xiàn)

資源附件(0)

訪問統(tǒng)計(jì)