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Network formed between users in a social media can be used to encourage information spreading among them. This research applied Social Network Analysis which further can be used to social media marketing to improve the marketing process effectively. Based on previous research, information spreading speed among the social media is affected by the users' activity connection which can be represented...
Underwater ship targets classification in a passive mode has valuable applications in many fields. In this paper, a novel time-frequency (TF) feature extraction and fusion strategy based on the ship radiated signal's whole quadratic TF representation matrix is presented. Firstly, with the help of the modified B-distribution, the one-dimensional received signal was transformed into a two-dimensional...
The aim of this paper was to separate the EEG recordings into cerebral and noncerebral waves and compare a statistical properties of chosen components using the coefficient of excess kurtosis. Noncerebral waves, particularly the ocular artifacts, should be properly identified, because some of them imitate the cerebral potentials. The eye opening and closure, blinks or eye flutter are similar to the...
The underground economy is a key component in cyber carding crime ecosystems because it provides a black marketplace for cyber criminals to exchange malicious tools and services that facilitate all stages of cyber carding crime. Consequently, black market sellers are of particular interest to cybersecurity researchers and practitioners. Malware/carding sellers are critical to cyber carding crime since...
An algorithm is presented to automate the identification of breaking waves in images collected with a camera on a drifting buoy. Each image is given a score from four separate analysis techniques: brightness detection, pixel histogram, entropy (texture) analysis, and glare identification. By combining these in a composite score, potential breaking wave images are detected and the number of images...
In this paper, a variant of (t, n) threshold secret sharing scheme is realized using a lattice model. Due to the potential quantum attacks in the future, we need to construct a secure channels for transmitting secret shares. Such channels could be modeled by a lattice based public key cryptosystem whose security is based on the worst case hardness of lattice problems. Therefore, we propose a lattice...
Survivability is a key attribute to measure large-scale network security and has become a hot research issue. Large-scale network is a complex system, which has the typical survivability characteristics of complex system. The current network survivability studies usually aim for a specific aspect of network. In this paper, we attempt to study the survivability of large-scale network based on the characteristics...
Anomaly detection has been a hot topic in recent years due to its capability of detecting zero day attacks. In this paper, we propose a new metric called Entropy-Ratio. We validate that the Entropy-Ratio is stationary. Making use of this observation, we combine the Least Mean Square algorithm and the Forward Linear Predictor to propose a new on-line detector called LMS-FLP detector. Using the two...
As one of the emerging technologies with most potential for developing, Network Coding (NC) has gained significant momentum. Due to encode-and-forward model, NC has natural privacy in communication, but it also induces that attackers become more imperceptible and impact on NC caused by them becomes more far-reaching. This requires that the security schemes should consider the characteristics of different...
Content based image retrieval (CBIR) system allows users to retrieve similar images from a large image database based upon a query image. Furthermore, the challenges faced by content-based image retrieval system are the semantic gap and perception subjectivity. In this paper, a combined feature fuzzy approach based CBIR system for the retrieval of bio-medical images is proposed in order to provide...
This study was aimed at comparing two alternative information-theoretic approaches for the combined analysis of heart rate variability (HRV) and respiration variability (RV). The approaches decompose the predictive information about HRV in two terms, quantifying respectively the information stored into HRV and that transferred to HRV from RV. Storage and transfer were assessed by the popular self...
Attacks against web servers and web-based applications remain a serious global network security threat. Attackers are able to compromise web services, collect confidential information from web data bases, interrupt or completely paralyze web servers. In this study, we consider the analysis of HTTP logs for the detection of network intrusions. First, a training set of HTTP requests which does not contain...
Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In this algorithm, the parameter selection is very important on the algorithm performance. Huang proposed a modified...
Determining the original file type of data fragments helps data recovery, spam detection, virus scanning, and network monitoring operations. In many cases, only unordered fragments of the original file are available for investigation. Therefore, we can only base on the content of a fragment to identify its file type. However, data fragments come with different sizes, as they may be the residual data...
Structural complexity measures and embedding have both been extensively and separately employed for the problems of graph clustering and classification. In this paper we aim to explore whether entropy component analysis can be used as a means of combining these two fundamental approaches. Specifically we develop a novel method that embeds undirected graphs into a feature space based on the graph entropy...
Weapon system selection is a critical task for commanders because weapon systems have become the primary deciding factor to determine the results of battles. Weapon system evaluation and selection problem is usually regarded as a multiple attribute decision-making(MADM) problem under fuzzy environment. Therefore, a hybrid fuzzy MADM methodology is proposed to deal with weapon system selection in this...
Network forensics is addressed to deal with cybercrime. The main purpose of a network forensics system is reconstructing evidences of network attacks. In order to reconstruct evidence, the network attack is firstly identified. Therefore, network attack detection solutions play an important role in network forensics. There are two main types of network attacks: network level and application level....
Large scale image classification requires efficient scalable learning methods with linear complexity in the number of samples. Although Stochastic Gradient Descent is an efficient alternative to classical Support Vector Machine, this method suffers from slow convergence. In this paper, our contribution is two folds. First we consider the minimization of specific calibrated losses, for which we show...
In this paper, we aim to characterize hyper graphs in terms of structural complexities. To measure the complexity of a hyper graph in a straightforward way, we transform a hyper graph into a line graph which accurately reflects the multiple relationships exhibited by the hyper graph. To locate the dominant substructure within a line graph, we identify a centroid vertex by computing the minimum variance...
The aim of this study was to examine the magnetoencephalography (MEG) background activity in Alzheimer's disease (AD) using three embedding entropies: approximate entropy (ApEn), sample entropy (SampEn), and fuzzy entropy (FuzzyEn). These three methods measure the time series regularity. Five minutes of recording were acquired with a 148-channel whole-head magnetometer from 36 AD patients and 24 elderly...
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