The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform
Palvinder Singh Mann - One of the best experts on this subject based on the ideXlab platform.
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Approach to Mitigate DDoS Attacks and Improve Network Performance
2011Co-Authors: Palvinder Singh MannAbstract:The Distributed denial of service attacks (DDoS) have become more and more frequent and caused some fatal problems in the recent time. Internet users experience denialof-service (DoS) attacks every day. Our inboxes are swamped with spam containing subject lines that sometimes fool us; our search-engine queries return many irrelevant results; and online auctions are plagued by Corrupt Database records filled with intentionally misleading keywords and many more.Intense research have been done to detect and defend such attacks, however, many solutions are still in the phase of theoretical studies. Some of them may have certain practical value, but they have to reconstruct the existing network and the routing instruments with great cost. In this paper we are going to present an Analytical approach which will employ Reactive Defense Mechanism to mitigate the DDoS attack and further improve network performance in terms of less computation time. Further the simulation result proves it to be a better result oriented approach
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A Reactive Defense Mechanism based on an Analytical Approach to Mitigate DDoS Attacks and Improve Network Performance
International Journal of Computer Applications, 2011Co-Authors: Palvinder Singh Mann, Dinesh KumarAbstract:Distributed denial of service attacks (DDoS) have become more and more frequent and caused some fatal problems in the recent time. Internet users experience denial- of-service (DoS) attacks every day. Our inboxes are swamped with spam containing subject lines that sometimes fool us; our search-engine queries return many irrelevant results; and online auctions are plagued by Corrupt Database records filled with intentionally misleading keywords and many more .Intense research have been done to detect and defend such attacks, however, many solutions are still in the phase of theoretical studies. Some of them may have certain practical value, but they have to reconstruct the existing network and the routing instruments with great cost. In this paper we are going to present an Analytical approach which will employ Reactive Defense Mechanism to mitigate the DDoS attack and further improve network performance in terms of less computation time. Further the simulation result proves it to be a better result oriented approach. Keywordsdenial of service, Denial-of-service.
Dinesh Kumar - One of the best experts on this subject based on the ideXlab platform.
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A Reactive Defense Mechanism based on an Analytical Approach to Mitigate DDoS Attacks and Improve Network Performance
International Journal of Computer Applications, 2011Co-Authors: Palvinder Singh Mann, Dinesh KumarAbstract:Distributed denial of service attacks (DDoS) have become more and more frequent and caused some fatal problems in the recent time. Internet users experience denial- of-service (DoS) attacks every day. Our inboxes are swamped with spam containing subject lines that sometimes fool us; our search-engine queries return many irrelevant results; and online auctions are plagued by Corrupt Database records filled with intentionally misleading keywords and many more .Intense research have been done to detect and defend such attacks, however, many solutions are still in the phase of theoretical studies. Some of them may have certain practical value, but they have to reconstruct the existing network and the routing instruments with great cost. In this paper we are going to present an Analytical approach which will employ Reactive Defense Mechanism to mitigate the DDoS attack and further improve network performance in terms of less computation time. Further the simulation result proves it to be a better result oriented approach. Keywordsdenial of service, Denial-of-service.
Didier Maquin - One of the best experts on this subject based on the ideXlab platform.
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Fault detection and isolation with robust principal component analysis
2007Co-Authors: Yvon Tharrault, Gilles Mourot, José Ragot, Didier MaquinAbstract:Principal component analysis (PCA) is a powerful fault detection technique which has been widely used in process industries. However, a main drawback of PCA is that it is based on least squares estimation techniques and hence fails to account for outliers which are common in physical processes. This paper is concerned with the fault detection and isolation problem. The proposed method does not require a data matrix without outliers for a PCA model design. Indeed, the approach directly uses the eventually Corrupt Database to elaborate a robust PCA model allowing fault detection. Then reconstruction principle and fault signatures analysis are used for fault isolation.
Yvon Tharrault - One of the best experts on this subject based on the ideXlab platform.
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Fault detection and isolation with robust principal component analysis
2007Co-Authors: Yvon Tharrault, Gilles Mourot, José Ragot, Didier MaquinAbstract:Principal component analysis (PCA) is a powerful fault detection technique which has been widely used in process industries. However, a main drawback of PCA is that it is based on least squares estimation techniques and hence fails to account for outliers which are common in physical processes. This paper is concerned with the fault detection and isolation problem. The proposed method does not require a data matrix without outliers for a PCA model design. Indeed, the approach directly uses the eventually Corrupt Database to elaborate a robust PCA model allowing fault detection. Then reconstruction principle and fault signatures analysis are used for fault isolation.
Harold Van Heerde - One of the best experts on this subject based on the ideXlab platform.
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Life-Cycle Privacy Policies for the Ambient Intelligence ∗
2009Co-Authors: Harold Van HeerdeAbstract:A smart, anticipating and learning environment will have a great impact on privacy. Ambient Intelligence will be everywhere, is invisible, has powerful sensing capabilities and most of all has a memory [2]. This does introduce a privacy risk, because context histories are vulnerable for attacks (hacking the context Database, Corrupt Database administrators, human mistakes, et cetera), so storing of privacy sensitive data is not desirable in privacy perspective. However, high quality and quantity of data improves smartness for the Ambient Intelligence, while less and degraded data improves privacy. Therefore the problem to be solved is how to balance smartness and privacy. We propose to give the control over the life cycle of their data to users, who themselves can balance their needs and wishes in terms of smartness and privacy. Balancing the control and the information flow between owner and collector of data decreases the asymmetry of information and the chance of privacy violations [1]. We let users (the owners of the collected data) specify Life-Cycle Policies which will be bound to the acquired data. These data is stored in a privacy aware context Database which degrades the data progressively according to the policy. Data is modeled as triplets (time, person, context). Triplets can take values in context states, exhibiting a certain level of accuracy specified in a domain generalization graph of that attribute. The generalization graphs form together a cube, in which each dimensio
