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Ensuring the security of wireless sensor networks (WSNs) is vital for monitoring real-time systems. One of the major security flaws experienced by WSNs is denial of service (DoS) which can even lead to the breakdown of the complete system or to wrong decisions being made by the system that can cause adverse results. This research work focuses on two techniques for detecting a DoS attack at a medium...
Mobile Ad-hoc Networks (MANETs) are extremely vulnerable to a variety of misbehaviors because of their basic features, including lack of communication infrastructure, short transmission range, and dynamic network topology. To detect and mitigate those misbehaviors, many trust management schemes have been proposed for MANETs. Most rely on pre-defined weights to determine how each apparent misbehavior...
Trustworthy network is an inevitable trend in the development of high trusted computing and Internet. Behavior evaluation is an important research topic in trustworthy network. Till now, most effect focuses on the validity of host's and user's identity, such as integrity measurement and access control, which could not guarantee the trustworthiness of valid user's behavior. In this paper, we proposed...
The principle and methods of Support Vector Machine (SVM) are introduced in this dissertation, evaluation indicators system and early warning systems for oil security are established. On this basis, SVM algorithm and oil security evaluation system are combined to evaluate for oil security. The predicted result showing that it has higher accuracy, Therefore, the safety evaluation index system in the...
In this paper, we investigate imposture using synthetic speech. Although this problem was first examined over a decade ago, dramatic improvements in both speaker verification (SV) and speech synthesis have renewed interest in this problem. We use a HMM-based speech synthesizer which creates synthetic speech for a targeted speaker through adaptation of a background model. We use two SV systems: standard...
Behavior evaluation is an important research topic in trustworthy network. Up to now, most effect focuses on the validity of host's and user's identity, such as integrity measurement and access control, which could not guarantee the trustworthiness of valid user's behavior. In this paper, we proposed an unsupervised method for evaluating user's network behavior and trustworthiness grades in a local...
The important issue in multi-class classification on support vector machines is the decision rule, which determines whether an input pattern belongs to a predicted class. To enhance the accuracy of multi-class classification, this study proposes a multi-weighted majority voting algorithm of support vector machine (SVM), and applies it to overcome complex facial security application. The proposed algorithm...
Security detections for networked manufacturing can improve availability of security configuration and also lower life cycle cost. But the threat level should be classified scientifically before a safety decision could be given. In this paper, a new machine learning method suitable for small-sample pattern recognition, called least squares support vector machine, is studied, and the optimization method...
Support vector machine SVM is a branch of artificial intelligence. SVM has many advantages in solving small sample size, nonlinear and high dimensional pattern recognition problem. Kernel function is the key technology of SVM, the choice of Kernel function will affect the learning ability and generalization ability of SVM, and different kernel function will construct different SVMS. At present, there...
Along with the extensive application of the network, network security has received increasing attention recently.This paper researches on the network security risk evaluation and analyze the traditional risk evaluation methods, then proposes a new network security risk evaluation method based on Support Vector Machine (SVM) and Binary tree. Unlike the traditional risk evaluation methods, SVM is a...
Support vector machine is a novel machine learning method in recent years, the SVM with RBF is widely used in pattern recognition because of its good learning properties. If Support vector machine is applied into risk assessment, it will get better assessment results. But the performance of RBF-SVM is influenced greatly by the parameter of C and sigma. The principle of SVM and the essence of kernel...
The pattern recognition approach for security analysis (SA) of power systems has been presented as a promising tool for on-line applications. This paper applies a learning-based nonlinear classifier, which is a support vector machine (SVM) for SA. Three single SVM are trained to classify the state of the system: secure, alert and emergency. The final classification is obtained combining the output...
Steganography techniques can be used to convey hidden information. If done well, the information is difficult to discover and is unknown to an observer. The detection of steganography, known as steganalysis, is an important research pursuit. In previous work, we developed a method of steganalysis for images with messages embedded by an LSB plusmn1 scheme. Our method uses lossless image compression...
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