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随着移动设备和定位技术的发展,产生了大量的移动对象轨迹数据,相伴而来的是个人隐私泄露问题。现有的轨迹隐私保护研究均假设轨迹数据是准确无误的,但由于数据采集设备不精确、移动对象延迟更新等原因,轨迹数据不确定性普遍存在。提出了一种基于K-匿名的不确定轨迹数据隐私保护方法,对发布的数据进行隐私处理,该方法首次将线性轨迹转化为不确定区域的思想引进轨迹数据的隐私处理。首先,使用概率统计的方法将轨迹泛化成一个更为真实的轨迹区域,然后将相似度高的轨迹域聚合成等价类进行数据的隐匿和发布,最后在真实的数据集上进行实验。 相似文献
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In order to guarantee the users’ privacy in the process of making friends in the mobile social networks,a new scheme of proxy re-encryption privacy protection in the cross-domain environment was introduced.The scheme employed the cross-domain multi-authority to sharing secret keys,so as to realize the access and shave of the cross-domain users data.And the secret keys of users’ attributes were re-encrypted,based on the technology of the proxy re-encryption and attribute encryption,to achieve the friends matching under the conditions of extending the access policy.Meanwhile,in purpose of enhancing the privacy of users’ data,the technology which contained the separation of users’ privacy ciphertext and secret keys was adopted.Based on that,problems in the existing system such as user data’s inability to be shared cross-cloud,less matching during the process of making friends and users’ inability to make friends when offline had been addressed.Security and experimental analysis show that this scheme can achieve chosen plaintext attack (CPA) security,ensure the privacy of friend discovery,and that is more effective than existing solutions. 相似文献
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With the rapid development and extensive application of the Internet of things (IoT),big data and 5G network architecture,the massive data generated by the edge equipment of the network and the real-time service requirements are far beyond the capacity if the traditional cloud computing.To solve such dilemma,the edge computing which deploys the cloud services in the edge network has envisioned to be the dominant cloud service paradigm in the era of IoT.Meanwhile,the unique features of edge computing,such as content perception,real-time computing,parallel processing and etc.,has also introduced new security problems especially the data security and privacy issues.Firstly,the background and challenges of data security and privacy-preserving in edge computing were described,and then the research architecture of data security and privacy-preserving was presented.Secondly,the key technologies of data security,access control,identity authentication and privacy-preserving were summarized.Thirdly,the recent research advancements on the data security and privacy issues that may be applied to edge computing were described in detail.Finally,some potential research points of edge computing data security and privacy-preserving were given,and the direction of future research work was pointed out. 相似文献
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Aiming at the weak flexibility and lack of users’ transparency existing in the current Mix-zone schemes for Internet of vehicle (IoV),a dynamic was proposed for Mix-zone construction with traffic adaption,which could construct a Mix-zone for the vehicles dynamically according to the traffic conditions for changing pseudonym at anytime and anywhere.This kind of Mix-zone could achieve privacy-preserving based on the identity and location.In addition,a novel traffic-adaptive metric was presented for classifying the privacy leveled in Mix-zone,which applied the normalization quantitation to measure the degree of Mix-zone’s privacy demanding by the current region.It was verified that the joint entropy-based privacy measuring model and the Mix-zone construction scheme by utilizing the trajectory data of taxis in certain district in Shenzhen city.The experimental shows that the proposed combination entropy-based model could depict the proportional relationship between the traffic scene parameters and the privacy-preserving degrees.The scheme is better in performance over the related methods,and strikes a good balance between location privacy and service usability. 相似文献
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本文提出了一种能够计算两相交圆精确面积的安全协议.通过调用该协议,参与者能够安全的计算出两个相交圆的面积,并且保证各方的私有数据不会泄漏,分析证明该协议具有安全性和高效性. 相似文献
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Based on the small key size and high encryption efficiency on ideal lattices,a privacy-preserving attribute-based encryption scheme on ideal lattices was proposed,which could support flexible access policies and privacy protection for the users.In the scheme,a semi-hidden policy was introduced to protect the users’ privacy.Thus,the sensitive values of user’s attributes are hidden to prevent from revealing to any third parties.In addition,the extended Shamir secret-sharing schemes was used to construct the access tree structure which can support “and” “or” and “threshold” operations of attributes with a high flexibility.Besides,the scheme was proved to be secure against chosen plaintext attack under the standard mode.Compared to the existing related schemes,the scheme can yield significant performance benefits,especially the size of system public/secret keys,users’ secret key and ciphertext.It is more effective in the large scale distributed environment. 相似文献
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The Internet of Things-based smart healthcare provides numerous facilities to patients and medical professionals. Medical professionals can monitor the patient's real-time medical data and diagnose diseases through the medical health history stored in the cloud database. Any kind of attack on the cloud database will result in misdiagnosis of the patients by medical professionals. Therefore, it becomes a primary concern to secure private data. On the other hand, the conventional data aggregation method for smart healthcare acquires immense communication and computational cost. Edge-enabled smart healthcare can overcome these limitations. The paper proposes an edge-enabled efficient privacy-preserving data aggregation (EEPPDA) scheme to secure health data. In the EEPPDA scheme, captured medical data have been encrypted by the Paillier homomorphic cryptosystem. Homomorphic encryption is engaged in the assurance of secure communication. For data transmission from patients to the cloud server (CS), data aggregation is performed on the edge server (ES). Then aggregated ciphertext data are transmitted to the CS. The CS validates the data integrity and analyzes and processes the authenticated aggregated data. The authorized medical professional executes the decryption, then the aggregated ciphertext data are decrypted in plaintext. EEPPDA utilizes the batch verification process to reduce communication costs. Our proposed scheme maintains the privacy of the patient's identity and medical data, resists any internal and external attacks, and verifies the health data integrity in the CS. The proposed scheme has significantly minimized computational complexity and communication overhead concerning the existing approach through extensive simulation. 相似文献
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