Game Theory Based Correlated Privacy Preserving Analysis in Big Data

Privacy preservation is one of the greatest concerns in big data. As one of extensive applications in big data, privacy preserving data publication (PPDP) has been an important research field. One of the fundamental challenges in PPDP is the trade-off problem between privacy and utility of the single and independent data set. However, recent research has shown that the advanced privacy mechanism, i.e., differential privacy, is vulnerable when multiple data sets are correlated. In this case, the trade-off problem between privacy and utility is evolved into a game problem, in which payoff of each player is dependent on his and his neighbors’ privacy parameters. In this paper, we firstly present the definition of correlated differential privacy to evaluate the real privacy level of a single data set influenced by the other data sets. Then, we construct a game model of multiple players, in which each publishes data set sanitized by differential privacy. Next, we analyze the existence and uniqueness of the pure Nash Equilibrium. We refer to a notion, i.e., the price of anarchy, to evaluate efficiency of the pure Nash Equilibrium. Finally, we show the correctness of our game analysis via simulation experiments

Effects of transition metal substitutions on the incommensurability and spin fluctuations in BaFe2As2 by elastic and inelastic neutron scattering

The spin fluctuation spectra from nonsuperconducting Cu-substituted, and superconducting Co-substituted, BaFe2As2 are compared quantitatively by inelastic neutron scattering measurements and are found to be indis- tinguishable. Whereas diffraction studies show the appearance of incommensurate spin-density wave order in Co and Ni substituted samples, the magnetic phase diagram for Cu substitution does not display incommensu- rate order, demonstrating that simple electron counting based on rigid-band concepts is invalid. These results, supported by theoretical calculations, suggest that substitutional impurity effects in the Fe plane play a signifi- cant role in controlling magnetism and the appearance of superconductivity, with Cu distinguished by enhanced impurity scattering and split-band behavior.Comment: 5 pages, 5 figures, Major change in the manuscrip

Authenticity Preservation with Histogram-Based Reversible Data Hiding and Quadtree Concepts

With the widespread use of identification systems, establishing authenticity with sensors has become an important research issue. Among the schemes for making authenticity verification based on information security possible, reversible data hiding has attracted much attention during the past few years. With its characteristics of reversibility, the scheme is required to fulfill the goals from two aspects. On the one hand, at the encoder, the secret information needs to be embedded into the original image by some algorithms, such that the output image will resemble the input one as much as possible. On the other hand, at the decoder, both the secret information and the original image must be correctly extracted and recovered, and they should be identical to their embedding counterparts. Under the requirement of reversibility, for evaluating the performance of the data hiding algorithm, the output image quality, named imperceptibility, and the number of bits for embedding, called capacity, are the two key factors to access the effectiveness of the algorithm. Besides, the size of side information for making decoding possible should also be evaluated. Here we consider using the characteristics of original images for developing our method with better performance. In this paper, we propose an algorithm that has the ability to provide more capacity than conventional algorithms, with similar output image quality after embedding, and comparable side information produced. Simulation results demonstrate the applicability and better performance of our algorithm

Comparing the value of bioproducts from different stages of anaerobic membrane bioreactors

© 2016 Elsevier Ltd The anaerobic digestion process in anaerobic membrane bioreactors is an effective way for waste management, energy sustainability and pollution control in the environment. This digestion process basically involves the production of volatile fatty acids and biohydrogen as intermediate products and methane as a final product. This paper compares the value of bioproducts from different stages of anaerobic membrane bioreactors through a thorough assessment. The value was assessed in terms of technical feasibility, economic assessment, environmental impact and impact on society. Even though the current research objective is more inclined to optimize the production of methane, the intermediate products could also be considered as economically attractive and environment friendly options. Hence, this is the first review study to correlate the idea into an anaerobic membrane bioreactor which is expected to guide future research pathways regarding anaerobic process and its bioproducts

A Computational Model for Reputation and Ensemble-Based Learning Model for Prediction of Trustworthiness in Vehicular Ad Hoc Network

Vehicular ad hoc networks (VANETs) are a special kind of wireless communication network that facilitates vehicle-to-vehicle(V2V) and vehicle-to-infrastructure(V2I) communication. This technology exhibits the potential to enhance the safety of roads, efficiency of traffic, and comfort of passengers. However, this can lead to potential safety hazards and security risks, especially in autonomous vehicles that rely heavily on communication with other vehicles and infrastructure. Trust, the precision of data, and the reliability of data transmitted through the communication channel are the major problems in VANET. Cryptography-based solutions have been successful in ensuring the security of data transmission. However, there is still a need for further research to address the issue of fraudulent messages being sent from a legitimate sender. As a result, in this study, we have proposed a methodology for computing vehicles reputation and subsequently predicting the trustworthiness of vehicles in networks. The blockchain records the most recent assessment of the vehicle’s credibility. This will allow for greater transparency and trust in the vehicle’s history, as well as reduce the risk of fraud or tampering with the information. The trustworthiness of a vehicle is confirmed not just by the credibility, but also by its network behavior as observed during data transfer. To classify the trust, an ensemble learning model is used. In depth tests are run on the dataset to assess the effectiveness of the proposed ensemble learning with feature selection technique. The findings show that the proposed ensemble learning technique achieves a 99.98% accuracy rate, which is notably superior to the accuracy rates of the baseline models

Metal–organic frameworks in seconds via selective microwave heating

Synthesis of metal–organic framework (MOF) materials via microwave heating often involves shorter reaction times and offers enhanced control of particle size compared to conventional heating. However, there is little understanding of the interactions between electromagnetic waves and MOFs, their reactants, and intermediates, all of which are required for successful scale-up to enable production of commercially viable quantities of material. By examining the effect of average absorbed power with a constant total absorbed energy to prepare MIL-53(Al) we have defined a selective heating mechanism that affords control over MOF particle size range and morphology by altering the microwave power. This is the first time a selective mechanism has been established for the preparation of MOFs via microwave heating. This approach has been applied to the very rapid preparation of MIL-53(Al)ta (62 mg in 4.3 seconds) which represents the fastest reported synthesis of a MOF on this scale to date

Organometallic nucleoside analogues: effect of hydroxyalkyl linker length on cancer cell line toxicity

A new series of chiral ferrocene derivatives containing both a hydroxyalkyl group and a thyminyl group on one cyclopentadienyl ring have been synthesised to probe structure–activity relationships in cancer cell line cytotoxicities. The stereoisomers of enantiomeric pairs of these so-called ferronucleosides have been studied and characterised by a combination of chiral analytical HPLC and single-crystal X-ray diffraction. Biological activity studies revealed that changing the length of the hydroxyalkyl group had marked effects on IC50 values, with compounds having shorter arms that more closely resemble endogenous nucleosides exhibiting lower cytotoxicities. The lipophilicities and electrochemical properties of this compound series have been studied to rationalise these trends and indicate future directions of study

Exogenous Melatonin Improves Cold Tolerance of Strawberry (Fragaria × ananassa Duch.) through Modulation of DREB/CBF-COR Pathway and Antioxidant Defense System

The strawberry (Fragaria × ananassa Duch.) is an important fruit crop cultivated worldwide for its unique taste and nutritional properties. One of the major risks associated with strawberry production is cold damage. Recently, melatonin has emerged as a multifunctional signaling molecule that influences plant growth and development and reduces adverse consequences of cold stress. The present study was conducted to investigate the defensive role of melatonin and its potential interrelation with abscisic acid (ABA) in strawberry plants under cold stress. The results demonstrate that melatonin application conferred improved cold tolerance on strawberry seedlings by reducing malondialdehyde and hydrogen peroxide contents under cold stress. Conversely, pretreatment of strawberry plants with 100 μM melatonin increased soluble sugar contents and different antioxidant enzyme activities (ascorbate peroxidase, catalase, and peroxidase) and non-enzymatic antioxidant (ascorbate and glutathione) activities under cold stress. Furthermore, exogenous melatonin treatment stimulated the expression of the DREB/CBF—COR pathways’ downstream genes. Interestingly, ABA treatment did not change the expression of the DREB/CBF—COR pathway. These findings imply that the DREB/CBF-COR pathway confers cold tolerance on strawberry seedlings through exogenous melatonin application. Taken together, our results reveal that melatonin (100 μM) pretreatment protects strawberry plants from the damages induced by cold stress through enhanced antioxidant defense potential and modulating the DREB/CBF—COR pathway. View Full-Tex

The Biomarker Toolkit - an evidence-based guideline to predict cancer biomarker success and guide development

BACKGROUND: An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation. METHODS: All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist. RESULTS: Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869-0.935, CRC: p>0.0001, 95.0% CI: 0.918-0.954). CONCLUSIONS: This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed