大数据技术在现代计算机信息安全领域的应用研究

文章从3个方面提出大数据技术在现代计算机信息安全领域的应用构想,即:建立现代计算机信息安全数据服务中心;充分运用爬虫等技术进行计算机信息安全数据搜集;云计算技术助力数据信息的深度挖掘。通过上述3个方面构建起大数据技术在现代计算机信息安全领域的应用体系。以保障计算机信息安全为出发点与落脚点,对大数据技术在现代计算机信息安全领域中的应用进行了研究。

基于大数据的安防体系建设分析

大数据应用范围的不断扩大,不仅为社会发展提供了有力支持,而且还为数据网络带来了更多安全风险。为提升现代数据网络安全性,应构建完善的数据网络安防体系。基于此,文章对基于大数据的安防体系总体设计思路做了简单介绍,进而对安防体系框架及数据安全中台进行设计。

Secure Big Data Storage and Sharing Scheme for Cloud Tenants

The Cloud is increasingly being used to store and process big data for its tenants and classical security mechanisms using encryption are neither sufficiently efficient nor suited to the task of protecting big data in the Cloud.In this paper,we present an alternative approach which divides big data into sequenced parts and stores them among multiple Cloud storage service providers.Instead of protecting the big data itself,the proposed scheme protects the mapping of the various data elements to each provider using a trapdoor function.Analysis,comparison and simulation prove that the proposed scheme is efficient and secure for the big data of Cloud tenants.

A Retrievable Data Perturbation Method Used in Privacy-Preserving in Cloud Computing

With the increasing popularity of cloud computing,privacy has become one of the key problem in cloud security.When data is outsourced to the cloud,for data owners,they need to ensure the security of their privacy;for cloud service providers,they need some information of the data to provide high QoS services;and for authorized users,they need to access to the true value of data.The existing privacy-preserving methods can't meet all the needs of the three parties at the same time.To address this issue,we propose a retrievable data perturbation method and use it in the privacy-preserving in data outsourcing in cloud computing.Our scheme comes in four steps.Firstly,an improved random generator is proposed to generate an accurate "noise".Next,a perturbation algorithm is introduced to add noise to the original data.By doing this,the privacy information is hidden,but the mean and covariance of data which the service providers may need remain unchanged.Then,a retrieval algorithm is proposed to get the original data back from the perturbed data.Finally,we combine the retrievable perturbation with the access control process to ensure only the authorized users can retrieve the original data.The experiments show that our scheme perturbs date correctly,efficiently,and securely.

Toward Energy-Efficient and Trustworthy eHealth Monitoring System

The rapid technological convergence between Internet of Things （loT）, Wireless Body Area Networks （WBANs） and cloud computing has made e-healthcare emerge as a promising application domain, which has significant potential to improve the quality of medical care. In particular, patient-centric health monitoring plays a vital role in e-healthcare service, involving a set of important operations ranging from medical data collection and aggregation, data transmission and segregation, to data analytics. This survey paper firstly presents an architectural framework to describe the entire monitoring life cycle and highlight the essential service components. More detailed discussions are then devoted to {／em data collection} at patient side, which we argue that it serves as fundamental basis in achieving robust, efficient, and secure health monitoring. Subsequently, a profound discussion of the security threats targeting eHealth monitoring systems is presented, and the major limitations of the existing solutions are analyzed and extensively discussed. Finally, a set of design challenges is identified in order to achieve high quality and secure patient-centric monitoring schemes, along with some potential solutions.

Improving Security and Sharing in Online Social Efficiency for Encrypted Data Networks

Despite that existing data sharing systems in online social networks （OSNs） propose to encrypt data before sharing, the multiparty access control of encrypted data has become a challenging issue. In this paper, we propose a secure data sharing scheme in 0SNs based on ciphertext-policy attribute- based proxy re-encryption and secret sharing. In order to protect users＇ sensitive data, our scheme allows users to customize access policies of their data and then outsource encrypted data to the OSNs service provider. Our scheme presents a multiparty access control model, which enables the disseminator to update the access policy of ciphertext if their attributes satisfy the existing access policy. Further, we present a partial decryption construction in which the computation overhead of user is largely reduced by delegating most of the decryption operations to the OSNs service provider. We also provide checkability on the results returned from the OSNs service provider to guarantee the correctness of partial decrypted ciphertext. Moreover, our scheme presents an efficient attribute revocation method that achieves both forward and backward secrecy. The security and performance analysis results indicate that the proposed scheme is secure and efficient in OSNs.

The Cloud Storage Ciphertext Retrieval Scheme Based on ORAM

Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.