Considered as a promising fine-grained access control mechanism for data sharing without a centralized trusted third-party, the access policy in a plaintext form may reveal sensitive information in ...the traditional CP-ABE method. To address this issue, a hidden policy needs to be applied to the CP-ABE scheme, as the identity of a user cannot be accurately confirmed when the decryption key is leaked, so the malicious user is traced and revoked as demanded. In this article, a CP-ABE scheme that realizes revocation, white-box traceability, and the application of hidden policy is proposed, and such ciphertext is composed of two parts. One is related to the access policy encrypted by the attribute value, and only the attribute name is evident in the access policy. Another is related to the revocation information and updated when revoking, where the revocation information is generated by the binary tree related to users. The leaf node value of a binary tree in the decryption key is used to trace the malicious user. From experimental results, it is shown that the proposed scheme is proven to be IND-CPA secure under the chosen plaintext attacks and selective access policy based on the decisional q-BDHE assumption in the standard model, efficient, and promising.
This paper first introduces a parametric binary tree labeling scheme (PBTL) to label image pixels in two different categories. Using PBTL, a data embedding method (PBTL-DE) is proposed to embed ...secret data to an image by exploiting spatial redundancy within small image blocks. We then apply PBTL-DE into the encrypted domain and propose a PBTL-based reversible data hiding method in encrypted images (PBTL-RDHEI). PBTL-RDHEI is a separable and reversible method that both the original image and secret data can be recovered and extracted losslessly and independently. Experiment results and analysis show that PBTL-RDHEI is able to achieve an average embedding rate as large as 1.752 bpp and 2.003 bpp when block size is set to <inline-formula><tex-math notation="LaTeX">2\times 2</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">3\times 3</tex-math></inline-formula>, respectively.
This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire ...original image but not in small image blocks to reserve room for hiding data. Then the original image is encrypted with an encryption key and the parametric binary tree is used to label encrypted pixels into two different categories. Finally, one of the two categories of encrypted pixels can embed secret information by bit replacement. According to the experimental results, compared with several state-of-the-art methods, the proposed IPBTL-RDHEI method achieves higher embedding rate and outperforms the competitors. Due to the reversibility of IPBTL-RDHEI, the original plaintext image and the secret information can be restored and extracted losslessly and separately.
Holonomic equations are recursive equations which allow computing efficiently numbers of combinatoric objects. Rémy showed that the holonomic equation associated with binary trees yields an efficient ...linear random generator of binary trees. I extend this paradigm to Motzkin trees and Schröder trees and show that despite slight differences my algorithm that generates random Schröder trees has linear expected complexity and my algorithm that generates Motzkin trees is in O(n) expected complexity, only if we can implement a specific oracle with a O(1) complexity. For Motzkin trees, I propose a solution which works well for realistic values (up to size ten millions) and yields an efficient algorithm.
Abstract
The data from an Iris flower database is studied. The Iris database is the most commonly used database for machine learning algorithms. The Iris database was developed by Ronald Aylmer ...Fisher in 1936. The Iris database has 150 records in three categories: Iris Sentosa, Iris Versicolor and Iris Virginic. The database has four attributes: sepal length, sepal width, petal length and petal width. For the machine learning algorithm, 150 Iris flower databases are used. Of the 150 Iris in the Iris database, 80% are used as the training set and the remaining 20% Iris as the test set. In machine learning, to perform classification and discrimination is a complicated and difficult thing. In this study, a grey relation grade is used to extract the main features of the Iris flower and a Binary Tree 1 is used to classify the Irises. The results show that for the same specific attributes, grey relation grade extracts the main attributes and can be used in combination with a binary for classification.
Ranked keyword search over encrypted data has been extensively studied in cloud computing as it enables data users to find the most relevant results quickly. However, existing ranked multi-keyword ...search solutions cannot achieve efficient ciphertext search and dynamic updates with forward security simultaneously. To solve the above problems, we first present a basic Machine Learning-based Ranked Keyword Search (ML-RKS) scheme in the static setting by using the k-means clustering algorithm and a balanced binary tree. ML-RKS reduces the search complexity without sacrificing the search accuracy, but is still vulnerable to forward security threats when applied in the dynamic setting. Then, we propose an Enhanced ML-RKS (called ML-RKS<inline-formula><tex-math notation="LaTeX">^{+}</tex-math> <mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="miao-ieq1-3140098.gif"/> </inline-formula>) scheme by introducing a permutation matrix. ML-RKS<inline-formula><tex-math notation="LaTeX">^{+}</tex-math> <mml:math><mml:msup><mml:mrow/><mml:mo>+</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="miao-ieq2-3140098.gif"/> </inline-formula> prevents cloud servers from making search queries over newly added files via previous tokens, thereby achieving forward security. The security analysis proves that our schemes protect the privacy of indexes, query tokens and keywords. Empirical experiments using the real-world dataset demonstrate that our schemes are efficient and feasible in practical applications.
Though low earth orbit (LEO) satellite networks have superiorities in short delay, wide coverage and flexible networking, the end-to-end (E2E) transmission has been confronted with severe challenges ...due to frequent changes of network topology. In this paper, a time-varying graph and binary tree search based routing algorithm for LEO satellite networks is proposed to reduce the E2E transmission delay and improve the network quality of service. Firstly, a coordinate graph (CG) model is adopted to characterize the topology structure and resource distribution of LEO satellite networks. Then, an E2E minimum-hop area is determined based on CG model, so that a minimum-hop binary tree (MHBT) is constructed. Finally, the pruning traversal of MHBT is performed to obtain all minimum-hop paths, based on which the E2E path with the shortest delay is determined. Simulation results show that the proposed routing algorithm not only reduces the path delay, but also improves the file delivery ratio.
Aiming at the complex computation and time-consuming problem during unordered image stitching, we present a method based on the binary tree and the estimated overlapping areas to stitch images ...without order in this paper. For image registration, the overlapping areas between input images are estimated, so that the extraction and matching of feature points are only performed in these areas. For image stitching, we build a model of the binary tree to stitch each two matched images without sorting. Compared to traditional methods, our method significantly reduces the computational time of matching irrelevant image pairs and improves the efficiency of image registration and stitching. Moreover, the stitching model of the binary tree proposed in this paper further reduces the distortion of the panorama. Experimental results show that the number of extracted feature points in the estimated overlapping area is approximately 0.3~0.6 times of that in the entire image by using the same method, which greatly reduces the computational time of feature extraction and matching. Compared to the exhaustive image matching method, our approach only takes about 1/3 of the time to find all matching images.
In the latest Joint Video Exploration Team development, the quadtree plus binary tree (QTBT) block partitioning structure has been proposed for future video coding. Compared to the traditional ...quadtree structure of High Efficiency Video coding (HEVC) standard, QTBT provides more flexible patterns for splitting the blocks, which results in dramatically increased combinations of block partitions and high computational complexity. In view of this, a confidence interval based early termination (CIET) scheme is proposed for QTBT to identify the unnecessary partition modes in the sense of rate-distortion (RD) optimization. In particular, a RD model is established to predict the RD cost of each partition pattern without the full encoding process. Subsequently, the mode decision problem is casted into a probabilistic framework to select the final partition based on the confidence interval decision strategy. Experimental results show that the proposed CIET algorithm can speed up QTBT block partitioning structure by reducing 54.7% encoding time with only 1.12% increase in terms of bit rate. Moreover, the proposed scheme performs consistently well for the high resolution sequences, of which the video coding efficiency is crucial in real applications.
In this article, a new method of option pricing in the form of fuzzy number is established based on fuzzy number binary tree model. Firstly,by using the operation rules of fuzzy number addition and ...number multiplication in cut set form, the fuzzy number binary tree model is equivalently transformed into two families of classical binary tree models which change with the level value, and some properties of the two binary tree model families are obtained, which are related to solve the problem of fuzzy option pricing. Then, based on the results obtained by us, the concepts of fuzzy set option price and fuzzy number option price are defined, and a sufficient condition is obtained for fuzzy set option price to be fuzzy number option price in the fuzzy number binary tree model. And then, for the convenience of practical application, the concepts of fold line fuzzy set and fuzzy number option price are introduced, a sufficient condition for fold line fuzzy set option price to be fold line fuzzy number option price is obtained, and a specific solution method of the fold line set and the fold line fuzzy number option pricing are set up. At last, two specific examples are given to show how to solve the fold line set and the fold line fuzzy number option price.
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