The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
22017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)
The Internet of Things (IoT) is the current technological revolution which can upgrade the current Internet environment into a more pervasive and ubiquitous world. Due to the distributed nature and the limited hardware capabilities of IoT, a lightweight authentication scheme is necessary. A certain number of lightweight user authentication schemes suit to the IoT environment had been proposed in recent...
The emergence and development of the Internet resulted in the generation of huge amounts of data, which are often distributed among different sites. Many organizations and companies attempted to mine the data with cloud computing. However, given the rise of various privacy issues, sensitive data (e.g., medical records) need to be encrypted before outsourcing to the cloud. To process data mining, such...
Aiming to reduce the user's computational overhead and tackle the attribute revocation issue, an attribute-based encryption scheme supporting decryption outsourcing and attribute revocation is proposed in this paper. The proposed scheme outsources some decryption computational tasks to a cloud server such that the computational overhead on the user is simple and constant. We also propose an efficient...
Cloud storage service has been increasing in popularity as cloud computing plays an important role in the IT domain. Users can be relieved of the burden of storage and computation, by outsourcing the large data files to the cloud servers. However, from the cloud service providers' point of view, it is wise to utilize the data deduplication techniques to reduce the costs of running large storage system...
Homomorphic encryption technology can settle a dispute of data privacy security in cloud environment, but there are many problems in the process of access the data which is encrypted by a homomorphic algorithm in the cloud. In this paper, on the premise of attribute encryption, we propose a fully homomorphic encrypt scheme which based on attribute encryption with LSSS matrix. This scheme supports...
Detecting crack type and crack size is crucial for road maintenance and management. Mobile crowd sensing is a new way to collect the information of cracks on roads. We propose a system named CrackDetector to detect cracks and estimate their types and size with smart phone in this paper. The type of a crack (i.e., horizontal crack, vertical crack, net crack) is determined by a coordinate transmission...
The stream cipher Espresso was proposed by Elena Dubrova and Martin Hell in Cryptography and Communications in 2015, which employs the nonlinear feedback shift register (NLFSR) of Galois configuration as a main building block. This Galois configuration of NLFSR is transformed into its equivalent Fibonacci configuration, and then stream cipher Espresso is changed into the stream cipher Espresso variant...
With the yearly increase of the amount of Android users, malicious applications for mobile terminals are emerging in endlessly. Many researchers have started to explore how malicious apps are detected from the perspective of network traffic. We design and implement a control and management system of Android traffic collection, which contains the functions of downloading APKs, malware static detection,...
Aiming at the problem of internal attackers of database system, anomaly detection method of user behaviour is used to detect the internal attackers of database system. With using Discrete-time Markov Chains (DTMC), an anomaly detection system of user behavior is proposed, which can detect the internal threats of database system. First, we make an analysis on SQL queries, which are user behavior features...
This paper proposes a novel kernel-based image subspace learning method for face recognition, by encoding an face image as a tensor of second order (matrix). First, we propose a kernel based discriminant tensor criterion, called kernel bilinear fisher criterion (KBFC), which is designed to simultaneously pursue two projection vectors to maximize the interclass scatter and at the same time minimize...
The design of recommendation method is the core of personalized recommendation, and the implementation of recommendation depends on the matching relation between user preference and resource object. This paper proposes a hybrid personalized recommendation method based on context-based collaborative filtering and knowledge recommendation, which is based on personalized recommendation knowledge model,...
Nowadays, the most popular way of data storage is distributed storage and the most widespread cloud storage platform is HDFS. It successfully used by many notable companies since its excellent capability. Unfortunately, the original design of HDFS was to handle large files, when dealing with enormous quantity of small files, the situation is not very optimistic. To solve this problem, an optimized...
In the era of information explosion, the full-text search engine must index vast amounts of data as soon as possible to provide the best retrieval service. This paper firstly analyzes problems of the traditional stand-alone indexing, and how to solve them by distributed and parallel indexing. Then proposed a distributed indexing algorithm based on the Map/Reduce, which changed the structure of map...
Since sensor nodes have limited energy resources, prolonging network lifetime and improving capability are essential elements in energy-efficient Wireless Sensor Networks (WSNs). Most existing approaches consider the residual energy of a single node when electing a cluster head (CH), omitting other factors associated with the node, thus, this paper proposes a new scheme energy-based clustering model...
SLAM (Simultaneous Localization and Mapping) of robot is the key to achieve autonomous control of robot, and also a significant topic in the field of mobile robotics. Aiming at 3D modeling of indoor complex environment, this paper presents a fast three-dimensional simultaneous location and mapping (SLAM) method for mobile robots. On the basis of RGB-D SLAM algorithm, the open-source software combining...
In this paper, we introduce a new random walk on undirected networks, which transition probabilities depend on the degree distribution of neighbor nodes. We have derived an analytical expression for MFPT between two nodes, and obtained an explicit solution to the average MFPT in the network with at any node. Further we provided a low bound for GMFPT by Cauthy's inequality, and the lower bound is sharp...
The hydraulic simulation is an important work in the design and construction of gas pipeline network in the city. It is also a necessary means to improve pipeline network, optimize the operation and management of pipe network, and ensure the safety of gas supply. In this paper, based on the model of hydraulic calculation and the finite element nodal method, the research on the hydraulic simulation...
The network intrusion detection techniques are important to prevent our system and network from malicious behaviors. In order to improve accuracy of network intrusion detection, machine learning, feature selection and optimization methods have been used, and the result tell us that the combination of machine learning and feature selection can improve accuracy. In this study, we developed a new machine...
This paper focuses on the problems existing in intrusion detection using neural network, including redundant information, large amount of data, long-time training, easy to fall into the local optimal. An intrusion detection method using deep belief network (DBN) and probabilistic neural network (PNN) is proposed. First, the raw data are converted to low-dimensional data while retaining the essential...
This paper tries to gain a more comprehensive understanding of the logistics discipline, supply chain optimization theory, and the complex networks. We formulate the inference problem to the cascade transmission model as the diffusion network inference problem. The inference model is also given out. In the experiment, our algorithm's performance is accepted. The precision is decreasing when the recall...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.