This paper provides an overview of the Industrial Internet with the emphasis on the architecture, enabling technologies, applications, and existing challenges. The Industrial Internet is enabled by recent rising sensing, communication, cloud computing, and big data analytic technologies, and has been receiving much attention in the industrial section due to its potential for smarter and more efficient industrial productions. With the merge of intelligent devices, intelligent systems, and intelligent decisioning with the latest information technologies, the Industrial Internet will enhance the productivity, reduce cost and wastes through the entire industrial economy. This paper starts by investigating the brief history of the Industrial Internet. We then present the 5C architecture that is widely adopted to characterize the Industrial Internet systems. Then, we investigate the enabling technologies of each layer that cover from industrial networking, industrial intelligent sensing, cloud computing, big data, smart control, and security management. This provides the foundations for those who are interested in understanding the essence and key enablers of the Industrial Internet. Moreover, we discuss the application domains that are gradually transformed by the Industrial Internet technologies, including energy, health care, manufacturing, public section, and transportation. Finally, we present the current technological challenges in developing Industrial Internet systems to illustrate open research questions that need to be addressed to fully realize the potential of future Industrial Internet systems.

Industrial Internet: A Survey on the Enabling Technologies, Applications, and Challenges

With the widespread adoption of Internet of Things and cloud computing in different industry sectors, an increasing number of individuals or organizations are outsourcing their Industrial Internet of Things (IIoT) data in the cloud server to achieve cost saving and collaboration (e.g., data sharing). However, in this environment, preserving the privacy of data remains a key challenge and inhibiting factor to an even wider adoption of IIoT in the cloud environment. To mitigate these issues, in this paper, we design a new secure channel-free certificateless searchable public key encryption with multiple keywords scheme for IIoT deployment. We then demonstrate the security of the scheme in the random oracle model against two types of adversaries, where one adversary is given the power to choose a random public key instead of any user's public key and another adversary is allowed to learn the system master key. In the presence of these types of adversaries, we evaluate the performance of the proposed scheme and demonstrate that it achieves (computational) efficiency with low communication cost.

Certificateless Searchable Public Key Encryption Scheme for Industrial Internet of Things

Industrial Internet of Things (IIoT) integrates various types of intelligent terminals, mobile devices, and communication technologies to enable the upgrade of traditional industries to intelligent industries. IIoT relies on the powerful data processing capabilities of cloud computing to reduce the cost of various on-demand services as per the requirements of users. However, the privacy and confidentiality of the outsourced data should be protected in this environment because the data are typically “handled” by a third-party service provider. An encryption technique can guarantee the confidentiality of the data but it limits data retrieval due to its innate “all-or-nothing” decryption feature. To apply encryption to privacy-preserving data retrieval, many public key encryption techniques with keyword search systems have been proposed in the literature. However, most of the existing schemes are vulnerable to inside keyword guessing attack (IKGA), which is caused by a small keyword space. To address this problem, we propose a certificateless public key authenticated encryption with keyword search scheme, which is provably secure against IKGA. A performance analysis of the proposed scheme demonstrates that it is more secure and effective compared with other certificateless public key encryption with keyword search schemes.

Certificateless Public Key Authenticated Encryption With Keyword Search for Industrial Internet of Things

With the rapid development of cloud computing, more and more enterprises/individuals are starting to outsource local data to the cloud servers. However, under open networks and not fully trusted cloud environments, they face enormous security and privacy risks (e.g., data leakage or disclosure, data corruption or loss, and user privacy breach) when outsourcing their data to a public cloud or using their outsourced data. Recently, several studies were conducted to address these risks, and a series of solutions were proposed to enable data and privacy protection in untrusted cloud environments. To fully understand the advances and discover the research trends of this area, this survey summarizes and analyzes the state-of-the-art protection technologies. We first present security threats and requirements of an outsourcing data service to a cloud, and follow that with a high-level overview of the corresponding security technologies. We then dwell on existing protection solutions to achieve secure, dependable, and privacy-assured cloud data services including data search, data computation, data sharing, data storage, and data access. Finally, we propose open challenges and potential research directions in each category of solutions.

Ensuring Security and Privacy Preservation for Cloud Data Services

Public key encryption with keyword search, known as PEKS, is a useful technology in some Storage-as-a-Service clouds. This technology allows the cloud server to search on a keyword, which is receiv...

A Provably Secure Certificateless Public Key Encryption with Keyword Search

Public Key Encryption with Keyword Search (PEKS), an indispensable part of searchable encryption, is stock-in-trade for both protecting data and providing operability of encrypted data. So far most of PEKS schemes have been established on Identity-Based Cryptography (IBC) with key escrow problem inherently. Such problem severely restricts the promotion of IBC-based Public Key Infrastructure including PEKS component. Hence, Certifcateless Public Key Cryptography (CLPKC) is efficient to remove such problem. CLPKC is introduced into PEKS, and a general model of Certifcateless PEKS (CLPEKS) is formalized. In addition, a practical CLPEKS scheme is constructed with security and efficiency analyses. The proposal is secure channel free, and semantically secure against adaptive chosen keyword attack and keyword guessing attack. To illustrate the superiority, massive experiments are conducted on Enron Email dataset which is famous in information retrieval field. Compared with existed constructions, CLPEKS improves the efficiency in theory and removes the key escrow problem.

Certificateless public key encryption with keyword search

In massive multimedia era, the dimension curse and the I/O performance bottleneck have become two major challenges for disk-based Approximate Nearest Neighbor (ANN) search. Hashing is a popular solution to overcome the dimension curse, one promising hashing technique is Locality Sensitive Hashing (LSH). However, most existing LSH indexings incur significant I/O cost during the search due to their low NN candidate hits in each I/O access. We recommend a novel method SC-LSH (SortingCodes-LSH) which combines LSH with another hashing technique (i.e., the discriminative short codes) to lift the hit of NN candidates so as to further boost the ANN search performance. Firstly, we intensify an LSH index and sort all the compound hashing keys according to a linear order to make similar NN candidates distributed locally. Then we generate product quantization (PQ) codes to use them as candidates instead of the original data points. These space-efficient short codes can enable us acquire significantly candidates via much less I/O operations. Moreover, based on theoretical and empirical studies among series of space-filling curves, we finally choose the Gray curve as the linear order to produce better local distribution of candidate data. All these above significantly increase the NN hits during each I/O, which greatly reduce the amount of necessary I/O access. Meanwhile, with the good similarity preserving ability, PQ codes are precise enough to discriminate NNs and thus guarantee the accuracy. Empirical study demonstrates that, comparing with four state-of-the-arts, SC-LSH achieves the best accuracy with significantly smaller I/O cost and space consumption. In fact, depending on the datasets, the I/O cost (resp., space consumption) of our scheme is only 5%-20% (resp., 1%-20%) of the other methods.

An efficient LSH indexing on discriminative short codes for high-dimensional nearest neighbors

The existing researches of image fusion most focus on theory. The universal and real time fusion system is presented rarely. A general purpose scheme of real time image fusion system based on RTOS (real time operation system) is proposed, VME bus and distributed parallel computer architecture is given. The kernel component is RTOS of standard VME bus. Dual DSP perform registration and fusion parallel individually. CPLD is designed to control VMEbus and synchronization. The architecture of new scheme has characteristics of real time, strong computational capability, broad I/O bandwidth, and expansibility. The result of experiments indicate that this system works perfectly.

A New Scheme for Multisensor Image Fusion System

The Support vector machines can be posed as quadratic program problems in a variety of ways.This paper investigates a formulation using the two-norm for the misclassification error and appending a bias norm to objective function that leads to a positive definite quadratic program only with the nonnegative constraint under a duality construction. An unconstrained convex program problem, which minimizes a differentiable convex piecewise quadratic function, is proposed as the Lagrangian dual of the quadratic program. Then an exact semismooth Newton support vector machine (ESNSVM) is obtained to solve the program speedily. Some numerical experiments demonstrate that our algorithm is very efficient comparing with the similar algorithms such as LSVM.

Cui Jiangtao

Papers

Certificateless public key encryption with keyword search

An efficient LSH indexing on discriminative short codes for high-dimensional nearest neighbors

A New Scheme for Multisensor Image Fusion System

Exact semismooth newton SVM