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IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

Digital Communications and Networks 2024年第1期10卷 190-204页

作者： Farhan Ullah Shamsher Ullah Gautam Srivastava Jerry Chun-Wei Lin School of Software Northwestern Polytechnical UniversityXian710072ShaanxiChina Knowledge Unit of Systems and Technology University of Management and TechnologySialkot 51040Pakistan Department of Math and Computer Science Brandon UniversityBrandonMB R7A 6A9Canada Department of Computer Science and Math Lebanese American UniversityBeirut1102Lebanon Western Norway University of Applied Sciences BergenNorway Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina

A network intrusion detection system is critical for cyber security against llegitimate *** terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,*** terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal *** is challenging to identify a specific attack due to complex features and data imbalance *** address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced ***,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,***,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic ***,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority ***,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network ***,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep *** experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and *** explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

关键词： Network intrusion detection Transfer learning Features extraction Imbalance data Explainable AI Cybersecurity

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Case recommendation based on fuzzy clustering in personalization web services

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2013 3rd International Symposium on Chemical Engineering and Material Properties, ISCEMP 2013

作者： Chen, Xue Gang Zhang, Jia Lu Cheng, Jie Ren Department of Computer science Xiangnan University Chenzhou 423000 China Department of Math Xiangnan University Chenzhou 423000 China College of Applied Science and Technology Hainan University Hainan China

ISBN: (纸本)9783037858363

Aiming at the problems of no strong real-time performance and poor scalability using traditional filtering recommendation technology, and a novel case recommended based on fuzzy clustering is proposed in this paper. Using case-based reasoning technology to personalized recommendation system, and the old case is clustered using fuzzy clustering algorithm, and a classification model is built, and the target case-the case base is converted to the target case-case class to reduce the most case retrieval space of the target case's the nearest neighbors. The experimental results indicate that this method can effectively improve the real-time performance, and it is used in E-commerce recommendation systems, and the degree of recommendation results universe of discourse is improved. © (2013) Trans Tech Publications, Switzerland.

关键词： Fuzzy clustering

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A chat room assignment for teaching network security

A chat room assignment for teaching network security

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32nd SIGCSE Technical Symposium on computer science Education

作者： Mitchener, W. Garrett Vahdat, Amin Applied and Computational Math Princeton University Princeton NJ United States Department of Computer Science Duke University Durham NC United States

This paper describes a chat room application suitable for teaching basic network programming and security protocols. A client/server design illustrates the structure of current scalable network services while a multicast version demonstrates the need for efficient simultaneous distribution of network content to multiple receivers (e.g., as required by video broadcasts). The system also includes implementations of two security protocols, one similar to Kerberos and another based on public key encryption.

关键词： Engineering education

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Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques 1

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丛书名： Lecture Notes in computer science

1000年

作者： Irit Dinur Klaus Jansen Joseph Naor José Rolim

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Active learning with distributional estimates

Active learning with distributional estimates

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28th Conference on Uncertainty in Artificial Intelligence, UAI 2012

作者： Röder, Jens Nadler, Boaz Kunzmann, Kevin Hamprecht, Fred A. CR/AEM Robert Bosch GmbH Hildesheim Germany Department of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel University of Heidelberg Heidelberg Germany

ISBN: (纸本)9780974903989

Active Learning (AL) is increasingly important in a broad range of applications. Two main AL principles to obtain accurate classification with few labeled data are refinement of the current decision boundary and exploration of poorly sampled regions. In this paper we derive a novel AL scheme that balances these two principles in a natural way. In contrast to many AL strategies, which are based on an estimated class conditional probability p(y|x), a key component of our approach is to view this quantity as a random variable, hence explicitly considering the uncertainty in its estimated value. Our main contribution is a novel mathematical framework for uncertainty-based AL, and a corresponding AL scheme, where the uncertainty in p(y|x) is modeled by a second-order distribution. On the practical side, we show how to approximate such secondorder distributions for kernel density classification. Finally, we find that over a large number of UCI, USPS and Caltech- 4 datasets, our AL scheme achieves significantly better learning curves than popular AL methods such as uncertainty sampling and error reduction sampling, when all use the same kernel density classifier.

关键词： Uncertainty analysis

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Computation of the normal forms for general M-DOF systems using multiple time scales. Part II: Non-autonomous systems

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Communications in Nonlinear science and Numerical Simulation 2006年第1期11卷 45-81页

作者： Zhu, Songhui Yu, Pei Department of Applied Mathematics Faculty of Sciences The University of Western Ontario London Ont. N6A 5B7 Canada Department of Math./Computer Science Benedict College Columbia SC 29204 United States

A perturbation technique has been developed in Part I to consider the computation of the normal forms for general multiple-degree-of-freedom autonomous systems. In this paper, the perturbation approach is extended to study general non-autonomous systems and is focused on systems with external forcing. With the aid of multiple time scales, efficient recursive algorithms are developed for systematically computing the normal forms. General solutions are obtained for solving ordered perturbation equations. In particular, the following cases are considered in detail: the non-resonance, internal resonances (including general resonance, resonant case involving 1:1 primary resonance, and combination of resonant case with non-resonance), and external resonances (including general resonance, and combination of internal resonance and external resonance). User-friendly Maple programs have been coded which can be "automatically" executed on various computer systems. Examples are given to demonstrate the computational efficiency of the method and the convenience of using computer algebra systems. © 2004 Elsevier B.V. All rights reserved.

关键词： Degrees of freedom (mechanics)

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Approximating equilibria in sequential auctions with incomplete information and multi-unit demand

Approximating equilibria in sequential auctions with incompl...

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26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012

作者： Greenwald, Amy Li, Jiacui Sodomka, Eric Department of Computer Science Brown University Providence RI 02912 United States Department of Applied Math/Economics Brown University Providence RI 02912 United States

ISBN: (纸本)9781627480031

In many large economic markets, goods are sold through sequential auctions. Examples include eBay, online ad auctions, wireless spectrum auctions, and the Dutch flower auctions. In this paper, we combine methods from game theory and decision theory to search for approximate equilibria in sequential auction domains, in which bidders do not know their opponents' values for goods, bidders only partially observe the actions of their opponents', and bidders demand multiple goods. We restrict attention to two-phased strategies: first predict (i.e., learn);second, optimize. We use best-reply dynamics [4] for prediction (i.e., to predict other bidders' strategies), and then assuming fixed other-bidder strategies, we estimate and solve the ensuing Markov decision processes (MDP) [18] for optimization. We exploit auction properties to represent the MDP in a more compact state space, and we use Monte Carlo simulation to make estimating the MDP tractable. We show how equilibria found using our search procedure compare to known equilibria for simpler auction domains, and we approximate an equilibrium for a more complex auction domain where analytical solutions are unknown.

关键词： Markov processes

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Shortest Path to a Segment and Quickest Visibility Queries 31

Shortest Path to a Segment and Quickest Visibility Queries

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31st International Symposium on Computational Geometry, SoCG 2015

作者： Arkin, Esther M. Efrat, Alon Knauer, Christian Mitchell, Joseph S.B. Polishchuk, Valentin Rote, Günter Schlipf, Lena Talvitie, Topi Department of Applied Math and Statistics Stony Brook University United States Department of Computer Science University of Arizona United States Institute of Computer Science Universität Bayreuth Germany Communications and Transport Systems ITN Linköping University Sweden Institute of Computer Science Freie Universität Berlin Germany Department of Computer Science University of Helsinki Finland

ISBN: (纸本)9783939897835

We show how to preprocess a polygonal domain with a fixed starting point s in order to answer efficiently the following queries: Given a point q, how should one move from s in order to see q as soon as possible? This query resembles the well-known shortest-path-to-a-point query, except that the latter asks for the fastest way to reach q, instead of seeing it. Our solution methods include a data structure for a different generalization of shortest-path-to-a-point queries, which may be of independent interest: to report efficiently a shortest path from s to a query segment in the domain.

关键词： Visibility

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On the complexity of verifying concurrent transition systems 8th

On the complexity of verifying concurrent transition systems

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Proceedings of the 1997 8th International Conference on Concurrency Theory, CONCUR

作者： Harel, David Kupferman, Orna Vardi, Moshe Y. Department of Applied Math. and Computer Science The Weizmann Institute Rehovot 76100 Israel EECS Department UC Berkeley Berkeley 94720-1770 CA United States Rice University Department of Computer Science Houston 77251-1892 TX United States

ISBN: (纸本)3540631410

In implementation verification, we check that an implementation is correct with respect to a specification by checking whether the behaviors of a transition system that models the program's implementation correlate with the behaviors of a transition system that models its specification. In this paper, we investigate the effect of concurrency on the complexity of implementation verification. We consider trace-based and tree-based approaches to the verification of concurrent transition systems, with and without fairness. Our results show that in almost all cases the complexity of the problem is exponentially harder than that of the sequential case. Thus, as in the model-checking verification methodology, the state-explosion problem cannot be avoided.

关键词： Specifications

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Natural Image Denoising: Optimality and Inherent Bounds

Natural Image Denoising: Optimality and Inherent Bounds

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IEEE Conference on computer Vision and Pattern Recognition

作者： Anat Levin Boaz Nadler Department of Computer Science and Applied Math The Weizmann Institute of Science

ISBN: (纸本)9781457703942

The goal of natural image denoising is to estimate a clean version of a given noisy image, utilizing prior knowledge on the statistics of natural images. The problem has been studied intensively with considerable progress made in recent years. However, it seems that image denoising algorithms are starting to converge and recent algorithms improve over previous ones by only fractional dB values. It is thus important to understand how much more can we still improve natural image denoising algorithms and what are the inherent limits imposed by the actual statistics of the data. The challenge in evaluating such limits is that constructing proper models of natural image statistics is a long standing and yet unsolved problem. To overcome the absence of accurate image priors, this paper takes a non parametric approach and represents the distribution of natural images using a huge set of 10~(10) patches. We then derive a simple statistical measure which provides a lower bound on the optimal Bayesian minimum mean square error (MMSE). This imposes a limit on the best possible results of denoising algorithms which utilize a fixed support around a denoised pixel and a generic natural image prior. Our findings suggest that for small windows, state of the art denoising algorithms are approaching optimality and cannot be further improved beyond ～ 0.1dB values.

关键词： image denoising Noisy Image fixed pivot DATA(STATISTICS) images optimality Mean square error Converge Prior Learning Noise reduction

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