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Cognitive computing over big data brings more development opportunities for enterprises and organizations in industrial informatics, and can make better decisions for them when they face data security challenges. To satisfy the requirement of real-time data storage in industrial Internet of Things (IoT), the remote unconstrained storage cloud is usually used to store the generated big data. However, the characteristic of semitrust of the cloud service provider determines that the data owners will worry about whether the data stored in cloud computing has been corrupted. In this article, a secure storage auditing is proposed, which supports efficient key updates and can be well used in cognitive industrial IoT environment. Moreover, the proposed basic auditing can be extended to support batch auditing that is suitable for multiple end devices to audit their data blocks simultaneously in practice. In addition, a hybrid data dynamics method is proposed, which employs a hash table to store the data blocks and uses a linked list to locate the operated data block. Compared with previous methods, the data block location time in the proposed data dynamics can be reduced by 40%. The security analysis results demonstrate that the proposed scheme can be proved to be correct, and is secure under computational differ-hellman (CDH) and discrete logarithm (DL) assumptions.

The urgent requirement of the sustainable computing determines that many security assurance protocols are designed with low computational cost. The design of the sustainable cloud storage auditing protocol is an attractive research filed in the security community. As we all know, secret keys of the data storage auditing in the cloud system are very sensitive. To enhance the security of the cloud data storage auditing, some studies focused on the research of key updates. In this paper, we propose a secure sustainable storage auditing protocol that can support key updates for clients in cloud computing. In order to alleviate the high overhead of key updates at the local side, the partial key update tasks are outsourced to the TPA. Moreover, clients can verify the validity of the new updated keys by using the technology of the BLS signature. The security analysis shows that the proposed protocol can provide the security properties of the correctness, the verifiability and the accountability. Compared to previous studies, the proposed protocol is more efficient which is very suitable for the real-world sustainable cloud storage auditing.

Smart mobile devices are one of the core components of the wireless body area networks (WBANs). These devices shoulder the important task of collecting, integrating, and transmitting medical data. When a personal computer collects information from these devices, it needs to authenticate the identity of them. Some effective schemes have been put forward to the device authentication in WBANs. However, few researchers have studied the WBANs device authentication in emergency situations. In this paper, we present a novel system named emergency medical system without the assistance of doctors. Based on the system, we propose an identity-based fast authentication scheme for smart mobile devices in WBANs. The scheme can shorten the time of device authentication in an emergency to achieve fast authentication. The analysis of this paper proves the security and efficiency of the proposed scheme.

Privacy is a major concern in RFID systems, especially with widespread deployment of wireless enabled interconnected personal devices. In this paper, we consider privacy issues in RFID system where the authorized readers must be able to identify tags without an adversary being able to trace them, and provide a formal security model for privacy in RFID system. Under this model, we analyze the recently proposed RFID authentication protocol named anonymous RFID authentication protocol and show attacks on them that compromise the privacy.

Directional antennas have the potential to provide a fundamental breakthrough in ad hoc network capacity. Omni-directional nature of transmission restricts the network capacity, where distribution of energy in all directions other than the intended direction of the destination node not only generated unnecessary interference to other neighboring nodes but also decreases the potential range of transmission. Directional antenna systems are increasingly being recognized as a powerful way of increasing the capacity, connectivity, and covertness of MANETs. In this paper, we survey the state-of-the-art routing protocols and give a comparison result of them with respect to the important challenging issues. We study the advantages and disadvantages of the routing protocols using directional antenna and also highlight performance issues of each routing technique. At the end, an explicit comparison table is presented and discussed.

This paper presents an intersymbol interference (ISI) and system noise analysis of the P-SLAM (parallel-sub-lambda) optical data storage system. Data are stored in sub-wavelength features accessed by transmitting light through the structure and collecting optical power measurements in the near-field. The non-linear ISI caused by the interactions of light between these features is characterized using finite-difference time-domain (FDTD) simulations. A system noise analysis is also presented that quantifies the effects of imperfections in fabrication and material properties. Previously, the authors proposed a detection scheme that dealt with the non-linear ISI by physically reducing it with air gaps. In this paper a signal processing method, the Viterbi algorithm, is proposed to overcome ISI. A modification is proposed to the Viterbi algorithm that is designed to deal with both the non-linear ISI and system noise. System simulations are used to show the uncoded bit error rate of the system is similar to current technologies. Conservative predictions estimate a data density of 5 Gbits/cm 2 for the system which exceeds densities achievable by current optical technologies.

In this paper, a reliable and energy efficient cooperative relaying (REECR) scheme was proposed for multi-hop communications in wireless sensor networks (WSNs). The scheme investigates node cooperation in conjunction with power control to conserve transmission energy and improve communication reliability in the presence of fading. By using a set of relay nodes that are located between transmitter and receiver to assist packet delivery, the scheme is capable of reaping both spatial diversity gains and path-loss savings. Local channel information is utilized in the relay selection process and the power control to reduce the energy consumption of data packet transmission. Moreover, a cooperative automatic repeat request (ARQ) is incorporated, whereby an intermediate node is chosen to help packet retransmission. Our simulations and analyses show that the proposed scheme improves energy efficiency, packet delivery ratio and extends nodes' battery lifetime.

Background: Sojourn time is the length of the preclinical screen-detectable phase, a period when a test can detect asymptomatic disease. Mean sojourn time (MST) is an important factor in determining appropriate screening intervals. Available estimates of MST for colorectal cancer (CRC) are imprecise and are associated with the older Hemoccult II test. This article presents MST estimates associated with the newer Hemoccult SENSA test and describes differences in MST by the location of cancer in the colorectum and age at the time of screening. Methods: MST was estimated from a cohort of 42,079 patients who underwent Hemoccult SENSA between January 1, 1997 and December 31, 2010. The precision of MST estimates was improved by incorporating information from a meta-analysis of the sensitivity of Hemoccult SENSA into the analytic model. Results: Estimated MST for cancers in the proximal and distal colorectum, with 95% credible intervals (CrI) in years, were: 3.86 (1.55–6.91) and 3.35 (2.11–4.93) among 45- to 54-year olds; 3.78 (2.18–5.77) and 2.24 (1.48–3.17) among 55- to 64-year olds; and 2.70 (1.41–4.31) and 2.10 (1.34–3.04) among 65- to 74-year olds. Conclusions: MST associated with Hemoccult SENSA was longer for CRC in the proximal versus distal colon. We found no evidence that MST increases with age and some evidence that it may decrease. Impact: These results add new information about the natural history of CRC and information about the performance of Hemoccult SENSA. Cancer Epidemiol Biomarkers Prev; 21(10); 1722–30. ©2012 AACR.

Sentiment classification aims at mining word-of-mouth, reviews of consumers, for a product or service by automatically classifying reviews as positive or negative. Few empirical studies have been conducted in comparing the different effects between machine learning and semantic orientation approaches on Chinese sentiment classification. This paper adopts three supervised learning approaches and a web-based semantic orientation approach, PMI-IR, to Chinese reviews. The results show that SVM outperforms naive bayes and N-gram model on various sizes of training examples, but does not obviously exceeds the semantic orientation approach when the number of training examples is smaller than 300.

Nowadays, online word-of-mouth has turned to be a very important resource for electronic businesses. How to analyze user generated reviews and to classify them into different sentiment classes is gradually becoming a question that people pay close attention to. In this field, special challenges are associated with the mining of traveler reviews. At present, there is some research on sentiment analysis for English traveler generated reviews, but very few studies pay attention to sentiment analysis for traveler reviews in Chinese. China is the largest country in terms of the number of Internet users. Internet technologies are gradually playing more and more important roles for many industries including tourism industry. The lack of sentiment analysis methods will block the use of word-of-mouth for tourism industry in China. To solve the problem, this study conducts an exploring research on sentiment analysis to Chinese traveler reviews by support vector machine (SVM) algorithm. The experiment data of Chinese reviews for hotels are downloaded from www.ctrip.com, the largest online travel agency in China. Empirical results indicate that, comparing to prior studies on English reviews, SVM algorithm can gain a very well performance of sentiment classification for traveler reviews in Chinese.