Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage

Guo, Yeting; Liu, Fang; Cai, Zixing; Xiao, Nong; Zhao, Ziming

doi:10.3390/s18041189

Cited by 26 publications

(25 citation statements)

References 30 publications

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“…(i) According to [21], in order to transmit data quickly, the system first selects dominator nodes as a CDS. The selected nodes must satisfy the following conditions:…”

Section: Overview Of the Proposed Schemementioning

confidence: 99%

“…Selecting Nodes to Form CDS. The method of constructing the CDS is the same as with [21]. Reference [21] construct minimum connected dominating set in wireless sensor network using two-hop information.…”

Section: Overview Of the Proposed Schemementioning

confidence: 99%

“…The construction of the PDS is constructed based on 1-hop and 2-hop neighbors' information from each node and its remaining energy [21]. In the initial stage, in this algorithm, the color of nodes starts as white, and as the dominators and virtual dominators are selected, the nodes' color changes.…”

Section: Overview Of the Proposed Schemementioning

confidence: 99%

“…In the initial stage, in this algorithm, the color of nodes starts as white, and as the dominators and virtual dominators are selected, the nodes' color changes. In each round, a node can be selected as dominator if node v has a degree higher than its 1-hop and 2-hop neighbor nodes [21]. The degree of a node is the number of nodes in the range of transmission radius.…”

Section: Overview Of the Proposed Schemementioning

confidence: 99%

“…Wireless sensor networks (WSNs) are important components for IoT, in which each node senses information from surrounding environment and where each node in the network helps in routing by forwarding data to other nodes [21][22][23][24][25][26][27]. To reduce the complexity of processing big data in the network, big data codes need to be reprogrammed.…”

Section: Introductionmentioning

confidence: 99%

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Construction Low Complexity and Low Delay CDS for Big Data Code Dissemination

et al. 2018

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The diffusion of codes is an important processing technology for big data networks. In previous scheme, data analysis was conducted for small samples of big data and complex problems that cannot be processed by big data technology. Due to the limited capacity of intelligence device, a better method is to select a set of nodes (intelligence device) to form a connected dominating set (CDS) to save energy, and constructing CDS is proved to be a complete NP problem. However, it is a challenge to reduce the communication delay and complexity for urgent data transmission in big data. In this paper, an appropriate duty cycle control (ADCC) scheme is proposed to reduce communication delay and complexity while improving energy efficient in CDS-based WSNs. In ADCC scheme, the method for constructing CDS is proposed at lower complexity. Nodes in CDS are selected according to the degree of nodes. Then, duty cycle of dominator nodes in CDS is higher than that of dominated nodes, so the communication delay in the proposed scheme is far less than that of previous scheme. The duty cycle of dominated nodes is small to save energy. This is because the number of dominator nodes in CDS is far less than the number of dominated nodes whose duty cycle is small; thus, the total energy consumption of the network is less than that of the previous scheme. As a result, the performance of energy consumption and communication delay and complex have been improved. Its complexity O ∑ v i=0 m − i + 2m − 2v − s is reduced a lot for big data. The theoretical analysis shows that compared to the previous scheme, the transmission delay can be reduced 25-92% and the energy efficiency is improved by about 80% while retaining network lifetime.

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“…(i) According to [21], in order to transmit data quickly, the system first selects dominator nodes as a CDS. The selected nodes must satisfy the following conditions:…”

Section: Overview Of the Proposed Schemementioning

confidence: 99%

Section: Overview Of the Proposed Schemementioning

confidence: 99%

Section: Overview Of the Proposed Schemementioning

confidence: 99%

Section: Overview Of the Proposed Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Construction Low Complexity and Low Delay CDS for Big Data Code Dissemination

et al. 2018

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Survey on secure search over encrypted data on the cloud

Pham

Woodworth

Salehi

2019

Concurrency and Computation

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Cloud computing has become a potential resource for businesses and individuals to outsource their data to remote but highly accessible servers. However, the potential of cloud services has not been fully realized due to users concerns about data privacy and security. User-side encryption techniques can be employed to mitigate the security concerns, but once the data is encrypted, no processing (eg, searching) can be performed on the outsourced data. Searchable Encryption (SE) techniques have been widely studied to enable searching on the data while they are encrypted. These techniques enable various types of search on the encrypted data and offer different levels of security. While these techniques enable different search types and vary in details, they share similarities in their components and architectures. In this paper, we provide a comprehensive survey on different secure search techniques, a high-level architecture for these systems, and an analysis of their performance and security level. KEYWORDScloud security, encrypted search, search over encrypted data, survey INTRODUCTIONAs cloud computing becomes prevalent, more cloud-based solutions are being developed and widely used in different applications. Companies that have adopted cloud storage solutions are reported to gain a competitive edge against those that have not. 1Cloud computing is favored due to its many advantages, including convenience and accessibility, consistent back ups to reducing the burden of local storage, and saving capital expenditure on in-house hardware and software maintenance. 2 However, public cloud storage services may be utilized by multi-tenant customers who store large amounts of potentially sensitive data on the cloud. Using cloud storage implies losing full control over data and delegating it to the cloud administrators, exposing the data to potential external and internal attacks, 3,4 which can be devastating for organizations that rely on confidentiality of their data (eg, financial corporations).These problems have made businesses concerned about outsourcing their data to the cloud and utilizing its potential. 5,6 For instance, a medical center that owns patients' health records cannot outsource its data to a cloud that is vulnerable to attacks, due to legal regulations. 7 In another instance, a law enforcement agency that keeps sensitive criminal records will hesitate to use cloud storage because of similar concerns.this approach remains impractical. Therefore, searchable encryption systems (eg, see other works 12-15 ) have been introduced to cope with this problem. These systems ideally allow the encrypted data to be searched without revealing the data and search query. Hence, they relieve concerns about data confidentiality in the cloud. Efforts to create searchable encryption systems date back to 2000 with work by Song et al. 11 Since then, numerous research works have been undertaken to enable different types of searchable encryption. Although these systems differ in their search approaches, security level, and perf...

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Lightweight edge‐based kNN privacy‐preserving classification scheme in cloud computing circumstance

Tan

Liu

et al. 2020

Concurrency and Computation

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Summary Because mobile terminals have limited computing and storage resources, individuals tend to outsource their data generated from mobile devices to clouds to do data operations. However, utilization of the abundant computation and storage resources of clouds may pose a threat to user's private data. In this paper, we focus on the issue of encrypted k‐nearest neighbor (kNN) classification on the cloud. In the past few years, many solutions were proposed to protect the user's privacy and data security. Unfortunately, most privacy‐preserving data mining schemes are not lightweight, which are not practical in real‐world applications. To solve this issue, we proposed a lightweight edge‐based kNN (EBkNN) classification scheme over encrypted cloud database utilizing edge computing technology. Our proposed scheme can provide several security guarantees: (i) user's data security, (ii) user's query privacy, and (iii) data access patterns. We analyzed the security of our scheme utilizing the semi‐honest security model and evaluated the performance using a synthetic dataset. The experiment results indicate that our scheme is more lightweight than the state‐of‐the‐art scheme.

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Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage

Cited by 26 publications

References 30 publications

Construction Low Complexity and Low Delay CDS for Big Data Code Dissemination

Construction Low Complexity and Low Delay CDS for Big Data Code Dissemination

Survey on secure search over encrypted data on the cloud

Lightweight edge‐based kNN privacy‐preserving classification scheme in cloud computing circumstance

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