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  • Information Flow Security Models for Cloud Computing
  • Abstract Cloud computing provides services to users through Internet. This open mode not only facilitates the access by users, but also brings potential security risks. In cloud computing, the risk of data leakage exists between users and virtual machines. Whether direct or indirect data leakage, it can be regarded as illegal information flow. Methods, such as access control models can control the information flow, but not the covert information flow. Therefore, it needs to use the noninterference models to detect the existence of illegal information flow in cloud computing architecture. Typical noninterference models are not suitable to certificate information flow in…
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  • A Differential Privacy Based (k-Ψ)-Anonymity Method for Trajectory Data Publishing
  • Abstract In recent years, mobile Internet technology and location based services have wide application. Application providers and users have accumulated huge amount of trajectory data. While publishing and analyzing user trajectory data have brought great convenience for people, the disclosure risks of user privacy caused by the trajectory data publishing are also becoming more and more prominent. Traditional k-anonymous trajectory data publishing technologies cannot effectively protect user privacy against attackers with strong background knowledge. For privacy preserving trajectory data publishing, we propose a differential privacy based (k-Ψ)-anonymity method to defend against re-identification and probabilistic inference attack. The proposed method is divided…
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  • An Efficient Mechanism for Product Data Extraction from E-Commerce Websites
  • Abstract A large amount of data is present on the web which can be used for useful purposes like a product recommendation, price comparison and demand forecasting for a particular product. Websites are designed for human understanding and not for machines. Therefore, to make data machine-readable, it requires techniques to grab data from web pages. Researchers have addressed the problem using two approaches, i.e., knowledge engineering and machine learning. State of the art knowledge engineering approaches use the structure of documents, visual cues, clustering of attributes of data records and text processing techniques to identify data records on a web page.…
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  • Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling
  • Abstract Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels within the threshold range are…
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  • Upper Bound Limit Analysis of Anisotropic Soils
  • Abstract In this paper, a novel discretization method in σ-τ space is developed to calculate the upper bound limit loads and failure modes of anisotropic Mohr-Coulomb materials. To achieve this objective, the Mohr-Coulomb yield criterion is linearized in σ-τ space, which allows for upper bound solution of soils whose cohesion and friction coefficient varying with direction. The finite element upper limit analysis formulation using the modified anisotropic yield criterion is then developed. Several examples are given to illustrate the capability and effectiveness of the proposed numerical procedure for computing rigorous upper bounds for anisotropic soils.
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  • IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference System for Diagnosis of COVID-19
  • Abstract The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer 1, and seven input variables…
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  • Bandwidth-Efficient Transmission Method for User View-Oriented Video Services
  • Abstract The trend in video viewing has been evolving beyond simply providing a multiview option. Recently, a function that allows selection and viewing of a clip from a multiview service that captures a specific range or object has been added. In particular, the freeview service is an extended concept of multi-view and provides a freer viewpoint. However, since numerous videos and additional data are required for its construction, all of the clips constituting the content cannot be simultaneously provided. Only certain clips are selected and provided to the user. If the video is not the preferred video, change request is made,…
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  • A Novel System for Recognizing Recording Devices from Recorded Speech Signals
  • Abstract The field of digital audio forensics aims to detect threats and fraud in audio signals. Contemporary audio forensic techniques use digital signal processing to detect the authenticity of recorded speech, recognize speakers, and recognize recording devices. User-generated audio recordings from mobile phones are very helpful in a number of forensic applications. This article proposed a novel method for recognizing recording devices based on recorded audio signals. First, a database of the features of various recording devices was constructed using 32 recording devices (20 mobile phones of different brands and 12 kinds of recording pens) in various environments. Second, the audio…
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  • Research on Intelligent Mobile Commerce Transaction Security Mechanisms Based on Mobile Agent
  • Abstract In networked mobile commerce network transactions, trust is the prerequisite and key to a smooth transaction. The measurement of trust between entities involves factors such as transaction amount, transaction time, personal income of consumer entities and their risk attitude towards trust, etc., so it is difficult to accurately calculate quantitatively. In order to find out the essential characteristics of this trust relationship, based on the research background of mobile commerce in the mobile network environment, a dynamic trust mechanism is proposed through the research of trust in the mobile network environment, trust influencing factors and trust mechanism. The calculation model…
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  • Stacked Attention Networks for Referring Expressions Comprehension
  • Abstract Referring expressions comprehension is the task of locating the image region described by a natural language expression, which refer to the properties of the region or the relationships with other regions. Most previous work handles this problem by selecting the most relevant regions from a set of candidate regions, when there are many candidate regions in the set these methods are inefficient. Inspired by recent success of image captioning by using deep learning methods, in this paper we proposed a framework to understand the referring expressions by multiple steps of reasoning. We present a model for referring expressions comprehension by…
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  •   Views:67       Downloads:55        Download PDF
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