arXiv subjects

Jingwei Liu

Publications and source records attributed to Jingwei Liu.

54 records · Page 3Linked to original sources

arXiv2018

An Efficient Anonymous Authentication Scheme for Internet of Vehicles

Internet of Vehicles (IoV) is an intelligent application of IoT in smart transportation, which can make intelligent decisions for passengers. It has drawn extensive attention to improve traffic safety and efficiency and create a more comfortable driving and riding environment. Vehicular cloud computing is a variant of mobile cloud computing, which can process local information quickly. The cooperation of the Internet and vehicular cloud can make the communication more efficient in IoV. In this paper, we mainly focus on the secure communication between vehicles and roadside units. We first propose a new certificateless short signature scheme (CLSS) and prove the unforgeability of it in random oracle model. Then, by combining CLSS and a regional management strategy we design an efficient anonymous mutual quick authentication scheme for IoV. Additionally, the quantitative performance analysis shows that the proposed scheme achieves higher efficiency in terms of interaction between vehicles and roadside units compared with other existing schemes.

cs.CR↗

arXiv2018

vFAC: Fine-Grained Access Control with Versatility for Cloud Storage

In recent years, cloud storage technology has been widely used in many fields such as education, business, medical and more because of its convenience and low cost. With the widespread applications of cloud storage technology, data access control methods become more and more important in cloud-based network. The ciphertext policy attribute-based encryption (CP-ABE) scheme is very suitable for access control of data in cloud storage. However, in many practical scenarios, all attributes of a user cannot be managed by one authority, so many multi-authority CP-ABE schemes have emerged. Moreover, cloud servers are usually semi-trusted, which may leak user information. Aiming at the above problems, we propose a fine-grained access control scheme with versatility for cloud storage based on multi-authority CP-ABE, named vFAC. The proposed vFAC has the features of large universe, no key escrow problem, online/offline mechanism, hidden policy, verifiability and user revocation. Finally, we demonstrate vFAC is static security under the random oracle model. Through the comparison of several existing schemes in terms of features, computational overhead and storage cost, we can draw a conclusion that vFAC is more comprehensive and scalable.

cs.CR↗

arXiv2018

A Traceable Concurrent Data Anonymous Transmission Scheme for Heterogeneous VANETs

Vehicular Ad Hoc Networks (VANETs) are attractive scenarios that can improve the traffic situation and provide convenient services for drivers and passengers via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. However, there are still many security challenges in the traffic information transmission, especially in the intense traffic case. For ensuring the privacy of users and traceability of vehicles, we propose a traceable concurrent data anonymous transmission scheme for heterogeneous VANETs. The scheme is based on certificateless aggregate signcryption, so it supports batch verification. Moreover, conditional anonymity is also achieved due to the involving of the pseudo-ID technique. Furthermore, it is a pairing-free scheme for the merit of multi-trapdoor hash functions. As a result, the total computation overhead is greatly reduced.

cs.CR↗

arXiv2018

Extension and Application of Deleting Items and Disturbing Mesh Theorem of Riemann Integral

The deleting items and disturbing mesh theorems of Riemann Integral are extended to multiple integral,line integral and surface integral respectively by constructing various of incomplete Riemann sum and non-Riemann sum sequences which converge to the same limit of classical Riemann sum. And, the deleting items and disturbing mesh formulae of Green's theorem, Stokes' theorem and divergence theorem (Gauss's or Ostrogradsky 's theorem) are also deduced. Then, the deleting items and disturbing mesh theorems of general Stokes' theorem on differential manifold are also derived.

math.PR↗

arXiv2018

An Accountable Anonymous Data Aggregation Scheme for Internet of Things

The Internet of Things (IoT) has become increasingly popular in people's daily lives. The pervasive IoT devices are encouraged to share data with each other in order to better serve the users. However, users are reluctant to share sensitive data due to privacy concerns. In this paper, we study the anonymous data aggregation for the IoT system, in which the IoT company servers, though not fully trustworthy, are used to assist the aggregation. We propose an efficient and accountable aggregation scheme that can preserve the data anonymity. We analyze the communication and computation overheads of the proposed scheme, and evaluate the total execution time and the per-user communication overhead with extensive simulations. The results show that our scheme is more efficient than the previous peer-shuffle protocol, especially for data aggregation from multiple providers.

cs.CR↗

arXiv2018

A Large-scale Concurrent Data Anonymous Batch Verification Scheme for Mobile Healthcare Crowd Sensing

Recently, with the rapid development of big data, Internet of Things (IoT) brings more and more intelligent and convenient services to people's daily lives. Mobile healthcare crowd sensing (MHCS), as a typical application of IoT, is becoming an effective approach to provide various medical and healthcare services to individual or organizations. However, MHCS still have to face to different security challenges in practice. For example, how to quickly and effectively authenticate masses of bio-information uploaded by IoT terminals without revealing the owners' sensitive information. Therefore, we propose a large-scale concurrent data anonymous batch verification scheme for MHCS based on an improved certificateless aggregate signature. The proposed scheme can authenticate all sensing bio-information at once in a privacy preserving way. The individual data generated by different users can be verified in batch, while the actual identity of participants is hidden. Moreover, assuming the intractability of CDHP, our scheme is proved to be secure. Finally, the performance evaluation shows that the proposed scheme is suitable for MHCS, due to its high efficiency.

cs.CR↗

arXiv2018

Approximative Theorem of Incomplete Riemann-Stieltjes Sum of Stochastic Integral

The approximative theorems of incomplete Riemann-Stieltjes sums of Ito stochastic integral, mean square integral and Stratonovich stochastic integral with respect to Brownian motion are investigated. Some sufficient conditions of incomplete Riemann-Stieltjes sums approaching stochastic integral are developed, which establish the alternative ways to converge stochastic integral. And, Two simulation examples of incomplete Riemann-Stieltjes sums about Ito stochastic integral and Stratonovich stochastic integral are given for demonstration.

math.PR↗

arXiv2017

Deleting Items and Disturbing Mesh Theorems for Riemann Definite Integral and Their Applications

Based on the definition of Riemann definite integral,deleting items and disturbing mesh theorems on Riemann sums are given. After deleting some items or disturbing the mesh of partition, the limit of Riemann sums still converges to Riemann definite integral under specific conditions. These theorems can deal with a class of complicate limitation of sum and product of series of a function, and demonstrate that the geometric intuition of Riemann definite integral is more profound than ordinary thinking of area of curved trapezoid.

math.PR↗

arXiv2016

Formula of Volume of Revolution with Integration by Parts and Extension

A calculation formula of volume of revolution with integration by parts of definite integral is derived based on monotone function, and extended to a general case that curved trapezoids is determined by continuous, piecewise strictly monotone and differential function. And, two examples are given, ones curvilinear trapezoids is determined by Kepler equation, and the other curvilinear trapezoids is a function transmuted from Kepler equation.

math.CA↗

arXiv2015

Pricing of European Basket Call Option under Exponential Ornstein-Uhlenbeck Process

Pricing of European basket call option with n-assets and a bond is discussed in this paper, where all prices of n-assets and the bond are driven by Exponential Ornstein-Uhlenbeck processes. The close-form of European basket option pricing formula is derived. Utilizing with 1-order differential approximate numerical solution of stochastic differential equation (Milstein method), a simulation example of European basket option pricing with 3 assets is also given.

q-fin.PR↗

arXiv2015

Parameter Estimation of Jelinski-Moranda Model Based on Weighted Nonlinear Least Squares and Heteroscedasticity

Parameter estimation method of Jelinski-Moranda (JM) model based on weighted nonlinear least squares (WNLS) is proposed. The formulae of resolving the parameter WNLS estimation (WNLSE) are derived, and the empirical weight function and heteroscedasticity problem are discussed. The effects of optimization parameter estimation selection based on maximum likelihood estimation (MLE) method, least squares estimation (LSE) method and weighted nonlinear least squares estimation (WNLSE) method are also investigated. Two strategies of heteroscedasticity decision and weighting methods embedded in JM model prediction process are also investigated. The experimental results on standard software reliability analysis database-Naval Tactical Data System (NTDS) and three datasets used by J.D. Musa demonstrate that WNLSE method can be superior to LSE and MLE under the relative error (RE) criterion.

cs.OH↗

arXiv2014

Inequality for Variance of Weighted Sum of Correlated Random Variables and WLLN

The upper bound inequality for variance of weighted sum of correlated random variables is derived according to Cauchy-Schwarz's inequality, while the weights are non-negative with sum of 1. We also give a novel proof with positive semidefinite matrix method. And the variance inequality of sum of correlated random variable with general weights is also obtained. Then, the variance inequalities are applied to the Chebyshev's inequality and sufficient condition of weak law of large numbers (WLLN) for sum of correlated random variables .

math.PR↗

arXiv2013

Penalty Constraints and Kernelization of M-Estimation Based Fuzzy C-Means

A framework of M-estimation based fuzzy C-means clustering (MFCM) algorithm is proposed with iterative reweighted least squares (IRLS) algorithm, and penalty constraint and kernelization extensions of MFCM algorithms are also developed. Introducing penalty information to the object functions of MFCM algorithms, the spatially constrained fuzzy C-means (SFCM) is extended to penalty constraints MFCM algorithms(abbr. pMFCM).Substituting the Euclidean distance with kernel method, the MFCM and pMFCM algorithms are extended to kernelized MFCM (abbr. KMFCM) and kernelized pMFCM (abbr.pKMFCM) algorithms. The performances of MFCM, pMFCM, KMFCM and pKMFCM algorithms are evaluated in three tasks: pattern recognition on 10 standard data sets from UCI Machine Learning databases, noise image segmentation performances on a synthetic image, a magnetic resonance brain image (MRI), and image segmentation of a standard images from Berkeley Segmentation Dataset and Benchmark. The experimental results demonstrate the effectiveness of our proposed algorithms in pattern recognition and image segmentation.

cs.CV↗

arXiv2012

Protein Function Prediction Based on Kernel Logistic Regression with 2-order Graphic Neighbor Information

To enhance the accuracy of protein-protein interaction function prediction, a 2-order graphic neighbor information feature extraction method based on undirected simple graph is proposed in this paper, which extends the 1-order graphic neighbor featureextraction method. And the chi-square test statistical method is also involved in feature combination. To demonstrate the effectiveness of our 2-order graphic neighbor feature, four logistic regression models (logistic regression (abbrev. LR), diffusion kernel logistic regression (abbrev. DKLR), polynomial kernel logistic regression (abbrev. PKLR), and radial basis function (RBF) based kernel logistic regression (abbrev. RBF KLR)) are investigated on the two feature sets. The experimental results of protein function prediction of Yeast Proteome Database (YPD) using the the protein-protein interaction data of Munich Information Center for Protein Sequences (MIPS) show that 2-order graphic neighbor information of proteins can significantly improve the average overall percentage of protein function prediction especially with RBF KLR. And, with a new 5-top chi-square feature combination method, RBF KLR can achieve 99.05% average overall percentage on 2-order neighbor feature combination set.

q-bio.QM↗

arXiv2012

Extension of Three-Variable Counterfactual Casual Graphic Model: from Two-Value to Three-Value Random Variable

The extension of counterfactual causal graphic model with three variables of vertex set in directed acyclic graph (DAG) is discussed in this paper by extending two- value distribution to three-value distribution of the variables involved in DAG. Using the conditional independence as ancillary information, 6 kinds of extension counterfactual causal graphic models with some variables are extended from two-value distribution to three-value distribution and the sufficient conditions of identifiability are derived.

stat.ME↗

arXiv2012

Implied volatility formula of European Power Option Pricing

We derive the implied volatility estimation formula in European power call options pricing, where the payoff functions are in the form of $V=(S^α_T-K)^{+}$ and $V=(S^α_T-K^α)^{+}$ ($α>0$)respectively. Using quadratic Taylor approximations, We develop the computing formula of implied volatility in European power call option and extend the traditional implied volatility formula of Charles J.Corrado, et al (1996) to general power option pricing. And the Monte-Carlo simulations are also given.

q-fin.PR↗

arXiv2011

Function Based Nonlinear Least Squares and Application to Jelinski--Moranda Software Reliability Model

A function based nonlinear least squares estimation (FNLSE) method is proposed and investigated in parameter estimation of Jelinski-Moranda software reliability model. FNLSE extends the potential fitting functions of traditional least squares estimation (LSE), and takes the logarithm transformed nonlinear least squares estimation (LogLSE) as a special case. A novel power transformation function based nonlinear least squares estimation (powLSE) is proposed and applied to the parameter estimation of Jelinski-Moranda model. Solved with Newton-Raphson method, Both LogLSE and powLSE of Jelinski-Moranda models are applied to the mean time between failures (MTBF) predications on six standard software failure time data sets. The experimental results demonstrate the effectiveness of powLSE with optimal power index compared to the classical least--squares estimation (LSE), maximum likelihood estimation (MLE) and LogLSE in terms of recursively relative error (RE) index and Braun statistic index.

stat.ME↗

arXiv2011

Confounding of three binary-variables counterfactual model

Confounding of three binary-variables counterfactual model is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses, the sufficient conditions to determine whether the covariate variable is an irrelevant factor or a confounder in each counterfactual model are obtained.

stat.AP↗