基于同态MAC的无线传感网安全数据融合方案

数据融合是缓解无线传感网资源瓶颈的重要方法之一,但在开放环境中易受数据机密性和完整性攻击。针对此问题,该文提出一种基于同态MAC的无线传感网安全数据融合方案SDA-HMAC。通过同态MAC技术进行融合数据的完整性检测,利用同态加密算法保证了融合数据的机密性,使用杂凑函数和时间参数t计算密钥的MAC保证了数据的新鲜性。实验仿真和理论分析表明,相比于其它方案,SDA-HMAC方案在传感网数据融合过程中能提供较好的数据机密性、完整性和新鲜性保护,具有较高的数据传输效率和融合精度,同时花费较少的计算量和通信量。     

基于改进RSA算法的隐私数据集同态加密方法

为提高对数据集的加密效果和保障数据集的安全性,在分析传统非对称密钥(RSA)算法运行原理及其参数选择、素数判定条件的基础上,提出了改进RSA算法。为进一步提升加密速度,引入数据加密(DES)算法。首先利用DES算法实现明文数据集的加密,并针对密钥进行RSA加密;在此基础上,在明文和密文空间中,利用加法同态过程对密文进行计算,并通过对结果的解密操作得到相应的明文计算结果。实验结果表明,与基于传统RSA算法或DES算法的加密方法相比,该方法的加密效率和抵御攻击成功率更高,加密过程耗时5~6 s,抵御攻击成功率保持在95%上下,说明该方法能够有效保护隐私数据集的安全。     

基于同态加密的DBSCAN聚类隐私保护方案

为了降低数据外包聚类运算过程中存在的隐私泄露风险,提出了一个基于同态加密的DBSCAN聚类隐私保护方案.为了加密实际场景中的浮点型数据,给出了针对不同数据精度的3种数据预处理方式,并提出了一种基于数据特点且综合考虑数据精度和计算开销等方面的数据预处理方式的选择策略.由于同态加密不支持密文比较运算,设计了一个用户端与云服...     

基于同态加密的智能电表数据聚合方案

针对多个智能电表实时采集数据聚合上传过程中所存在的用户隐私泄露和计算效率不高的问题,提出了一个基于同态加密的智能电表数据聚合方案。该聚合方案使得多个智能电表数据能够聚合传输至电力系统,而电力系统却无法得到单个智能电表的用电数据。仿真结果表明,该方案在智能电表侧和聚合器侧均可有效降低计算成本和通信成本。     

基于全同态加密的安全多方计算协议

针对云计算环境下数据的隐私保护问题,在研究全同态加密技术的基础上设计了一个安全多方计算协议.该协议约定网络类型为同步网络,信道模式为可信的安全信道,敌手为半诚实的参与者,同时有一个服务器作为计算中心.参与者通过全同态加密算法预先对输入进行加密并将明文发送给服务器进行安全多方计算,服务器和其他参与者全程得不到该参与者的输...     

一种基于同态Hash的数据持有性证明方法

在云存储服务中,为了让用户可以验证存储服务提供者正确地持有(保存)用户的数据,该文提出一种基于同态hash (homomorphic hashing)的数据持有性证明方法。因为同态hash算法的同态性,两数据块之和的hash值与它们hash值的乘积相等,初始化时存放所有数据块及其hash值,验证时存储服务器返回若干数据块的和及其hash值的乘积,用户计算这些数据块之和的hash值,然后验证是否与其hash值的乘积相等,从而达到持有性证明的目的。在数据生存周期内,用户可以无限次地验证数据是否被正确持有。该方法在提供数据持有性证明的同时,还可以对数据进行完整性保护。用户只需要保存密钥K,约520 byte,验证过程中需要传递的信息少,约18 bit,并且持有性验证时只需要进行一次同态hash运算。文中提供该方法的安全性分析,性能测试表明该方法是可行的。     

数据隐私保护的社会化推荐协议

基于邻域的社会化推荐需要同时依赖用户的历史行为数据和完善的社交网络拓扑图,但通常这些数据分别属于不同平台,如推荐系统服务提供商和社交网络服务提供商。出于维护自身数据价值及保护用户隐私的考虑,他们并不愿意将数据信息提供给其他方。针对这一现象,提出了2种数据隐私保护的社会化推荐协议,可以在保护推荐系统服务提供商和社交网络服务提供商的数据隐私的同时,为用户提供精准的推荐服务。其中,基于不经意传输的社会化推荐,计算代价较小,适用于对推荐效率要求较高的应用;基于同态加密的社会化推荐,安全程度更高,适用于对数据隐私要求较高的应用。在4组真实数据集上的实验表明,提出的2种方案切实可行,用户可以根据自身需求选择合适的方案。     

A secure channel code‐based scheme for privacy preserving data aggregation in wireless sensor networks

Data aggregation is an efficient method to reduce the energy consumption in wireless sensor networks (WSNs). However, data aggregation schemes pose challenges in ensuring data privacy in WSN because traditional encryption schemes cannot support data aggregation. Homomorphic encryption schemes are promising techniques to provide end to end data privacy in WSN. Data reliability is another main issue in WSN due to the errors introduced by communication channels. In this paper, a symmetric additive homomorphic encryption scheme based on Rao‐Nam scheme is proposed to provide data confidentiality during aggregation in WSN. This scheme also possess the capability to correct errors present in the aggregated data. The required security levels can be achieved in the proposed scheme through channel decoding problem by embedding security in encoding matrix and error vector. The error vectors are carefully designed so that the randomness properties are preserved while homomorphically combining the data from different sensor nodes. Extensive cryptanalysis shows that the proposed scheme is secure against all attacks reported against private‐key encryption schemes based on error correcting codes. The performance of the encryption scheme is compared with the related schemes, and the results show that the proposed encryption scheme outperforms the existing schemes.     

Layered data aggregation with efficient privacy preservation for fog‐assisted IIoT

The emergence of fog computing facilitates industrial Internet of Things (IIoT) to be more real‐time and efficient; in order to achieve secure and efficient data collection and applications in fog‐assisted IIoT, it usually sacrifices great computation and bandwidth resources. From the low computation and communication overheads perspective, this paper proposes a layered data aggregation scheme with efficient privacy preservation (LDA‐EPP) for fog‐assisted IIoT by integrating the Chinese remainder theorem (CRT), modified Paillier encryption, and hash chain technology. In LDA‐EPP scheme, the entire network is divided into several subareas; the fog node and cloud are responsible for local and global aggregations, respectively. Specially, the cloud is able to obtain not only the global aggregation result but also the fine‐grained aggregation results of subareas, which enables that can provide fine‐grained data services. Meanwhile, the LDA‐EPP realizes data confidentiality by the modified Paillier encryption, ensures that both outside attackers and internal semi‐trusted nodes (such as, fog node and cloud) are unable to know the privacy data of individual device, and guarantees data integrity by utilizing simply hash chain to resist tempering and polluting attacks. Moreover, the fault tolerance is also supported in our scheme; ie, even though some IIoT devices or channel links are failure, the cloud still can decrypt incomplete aggregation ciphertexts and derive expected aggregation results. Finally, the performance evaluation indicates that our proposed LDA‐EPP has less computation and communication costs.     

低能耗的隐私数据安全融合方法

为解决物联网安全数据融合过程中,数据隐私保护与节点计算能力及能量受限之间的矛盾,在对现有方法优缺点分析的基础上,提出一种低能耗的隐私数据安全融合方法(LCSDA, low energy-consuming secure data aggregation),该方法根据最短路径原则选择邻居节点,并且采用Prim最小生成树算法建立簇内数据融合路径。仿真结果表明,该方法可以有效降低节点能耗和簇头节点被捕获的概率,同时保证节点数据的隐私性。     

Secure data aggregation in wireless sensor networks using homomorphic encryption

In a Wireless Sensor Network (WSN), aggregation exploits the correlation between spatially and temporally proximate sensor data to reduce the total data volume to be transmitted to the sink. Mobile agents (MAs) fit into this paradigm, and data can be aggregated and collected by an MA from different sensor nodes using context specific codes. The MA-based data collection suffers due to large size of a typical WSN and is prone to security problems. In this article, homomorphic encryption in a clustered WSN has been proposed for secure and efficient data collection using MAs. The nodes keep encrypted data that are given to an MA for data aggregation tasks. The MA performs all the data aggregation operations upon encrypted data as it migrates between nodes in a tree-like structure in which the nodes are leafs and the cluster head is the root of the tree. It returns and deposits the encrypted aggregated data to the cluster head after traversing through all the intra cluster nodes over a shortest path route. The homomorphic encryption and aggregation processing in encrypted domain makes the data collection process secure. Simulation results confirm the effectiveness of the proposed secure data aggregation mechanism. In addition to security, MA-based mechanism leads to lesser delay and bandwidth requirements.     

Lightweight integrity verification scheme for cloud based group data

In order to protect the security of the data stored in the cloud by group users,a data integrity verification scheme was designed which can protect the privacy of the group users.The scheme can efficiently detect the shared data in the cloud and support the dynamic updating of the data,and use the characteristic of the ring signature to hide the iden-tity of the signer corresponding to the data block.That is,the third-party verifier can not spy on the users identity and other private information when validating.The aggregated approach is used to generate data labels,which reduces the storage cost of labels and supports the dynamic operation of group data,so that the users in the group can easily modify the cloud group data.     

安全的WSN数据融合隐私保护方案设计

针对无线传感器网络数据融合过程中的数据隐私和完整性保护问题,提出一种安全的数据融合隐私保护方案(SPPDA),把节点的私密因子与原始数据构成复数,采用同态加密方法对复数进行加密,实现在密文不解密的情况下进行数据融合,同时采用基于复数的完整性验证方法,确保数据的可靠性。理论分析和仿真结果表明,SPPDA方案的计算代价和通信开销较少,数据融合的精确度高。     

Separable reversible data hiding in encrypted image based on pixel value ordering and additive homomorphism

This work proposes a separable reversible data hiding scheme in encrypted images based on pixel value ordering (PVO). After the original image is encrypted using homomorphism encryption by the content owner, the data hider embeds the secret data in encrypted domain. The PVO strategy realizes hiding data in each block. Additive homomorphism guarantees the performance of PVO in encrypted domain is close to that in plain domain. Besides, the homomorphism encryption does not cause data expansion, and the payload can be further improved. With the watermarked encrypted image, if the receiver has only the data hiding key, he can extract the additional data. If the receiver has only the encryption key, he can obtain a decrypted image similar to the original one. If the receiver has both the data hiding key and the encryption key, he can extract the additional data without any error and recover the original image losslessly.     

A faulty node detection scheme for wireless sensor networks that use data aggregation for transport

This paper presents a faulty node detection approach for wireless sensor networks that aggregate measurement data on their way toward the sink (base station). The approach is based on the idea of commanding sensor nodes on the aggregation paths to temporarily stop including their readings in the received aggregated readings from their upstream neighbors. The scheme is dependent on the ability of the sink to detect faulty nodes through changes in the received aggregated readings at the sink using a Markov Chain Controller (MCC). The algorithm that is run in the sink uses the MCC to assign a state to each sensor node based on transitions that are triggered by receiving aggregated path readings, and accordingly deduces the nodes that may be faulty. The experimental results show at least 98% detection rate at the cost of reasonable detection delays and generated wireless network traffic. Copyright © 2016 John Wiley & Sons, Ltd.     

Reversible digital watermarking-based protocol for data integrity in wireless sensor network

For the contradiction between high energy consumption of WSN privacy protection algorithm and constrained resources of sensor network,a recoverable data fusion protocol that ensures data integrity and confidentiality based on reversible digital watermarking and homomorphic encryption technology was proposed.On the one hand,the data from the sensor was embedded by the difference expansion method by using the reversible digital watermarking technique,and original data could be recovered by using a reversible watermark to ensure the integrity check of the fusion data when the fusion data were destroyed.On the other hand,elliptic curve homomorphic encryption encrypted data to prevent sensor data from being perceived during data transmission.Security results show that the proposed protocol performs well against cluster head node compromise as well as tampering from an attack.Performance analysis shows that the protocol has significant advantages over other algorithms in terms of computation,communication overhead and propagation delay.The experimental results show that the protocol has a low resource overhead and improves network performance.