Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Enhanced Request Threshold Collaborative Mitigation For HTTP Flood | Jones Ogidiagba (u. a.) | Taschenbuch | 72 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786202064415 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2019, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -HTTP flood attacks have proven to be a long time challenge to internet web service. Various approaches have been devised to detect and mitigate against flood attack, however, it is not always possible for a router on the adversary (i.e the victim path) to detect an attack in progress. Also most of the approaches only detects the presence of an attack. This research presented Enhanced Request threshold based collaborative detection and mitigation model to detect and mitigate against flood attacks in progress irrespective of the path and the position of the adversary. Hence, this system will help to reduce HTTP flood attacks to a level that will ensure uninterrupted services to legitimate users. The res- ults gotten from the approach shows that an improvement of utilization performance of 64.33% against the scenario without Request threshold based scheme is recorded. This implies that Request threshold based detection and mitigation model provides 14.33% increment in cpu performance of web server under flood attack against other ap- proaches such as the rate based detection and mitigation scheme. The research provides an algorithm for mitigating against flood. 72 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Print on Demand.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: moluna, Greven, Germany
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ogidiagba JonesM.tech Cyber security at Federal University of Technology, Minna. NigeriaB.SC computer Science Delta State University, Abraka. NigeriaI am Network and Cyber security Administrator.HTTP flood attacks have proven to .
Language: English
Published by LAP LAMBERT Academic Publishing Jun 2019, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -HTTP flood attacks have proven to be a long time challenge to internet web service. Various approaches have been devised to detect and mitigate against http flood attack, however, it is not always possible for a router on the adversary (i.e the victim path) to detect an attack in progress. Also most of the approaches only detects the presence of an attack. This research presented Enhanced Request threshold based collaborative detection and mitigation model to detect and mitigate against http flood attacks in progress irrespective of the path and the position of the adversary. Hence, this system will help to reduce HTTP flood attacks to a level that will ensure uninterrupted services to legitimate users. The res- ults gotten from the approach shows that an improvement of utilization performance of 64.33% against the scenario without Request threshold based scheme is recorded. This implies that Request threshold based detection and mitigation model provides 14.33% increment in cpu performance of web server under http flood attack against other ap- proaches such as the rate based detection and mitigation scheme. The research provides an algorithm for mitigating against http flood.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6202064412 ISBN 13: 9786202064415
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - HTTP flood attacks have proven to be a long time challenge to internet web service. Various approaches have been devised to detect and mitigate against flood attack, however, it is not always possible for a router on the adversary (i.e the victim path) to detect an attack in progress. Also most of the approaches only detects the presence of an attack. This research presented Enhanced Request threshold based collaborative detection and mitigation model to detect and mitigate against flood attacks in progress irrespective of the path and the position of the adversary. Hence, this system will help to reduce HTTP flood attacks to a level that will ensure uninterrupted services to legitimate users. The res- ults gotten from the approach shows that an improvement of utilization performance of 64.33% against the scenario without Request threshold based scheme is recorded. This implies that Request threshold based detection and mitigation model provides 14.33% increment in cpu performance of web server under flood attack against other ap- proaches such as the rate based detection and mitigation scheme. The research provides an algorithm for mitigating against flood.