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In this book, the cryptanalysis problem of unknown cipher system is presented as a Black-Box, nonlinear, system identification problem, which assumes no priori knowledge about the cipher system except its input and output. Black-Box model is constructed using Artificial Neural Networks to attack the target cipher system, with the addition of building an equivalent Neuro-Model for the target cipher system. In cryptanalysis terminology, it is a known-plaintext attack. The constructed Neuro-Identifier has been used in two different approaches; the objective of the first approach is to determine the enciphering key, which is a total break and represent the ultimate performance of any cryptanalysis method. The cryptanalysis objectives are achieved in this approach. The aim of the second approach is to build an equivalent Neuro-Model for the target cipher system, which presents a new direction in cryptology. The constructed Neuro-Model can be regarded as an equivalent model for the real target system, which is a valuable product in many cases where the real system is not available.
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Über die Autorin bzw. den Autor
Qualifications: Ph. D. (Computer Science & Inf. Systems). Al-Nahrain UniversitySpecialization: Information & Network SecurityTeaching Area(s): Cryptography & Network Security, Artificial Intelligence, Management Information Systems, Software Engineering. Research Area(s): Cryptography, Network Security, Information Security.
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Black-Box Attack Using Neuro-Identifier
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, the cryptanalysis problem of unknown cipher system is presented as a Black-Box, nonlinear, system identification problem, which assumes no priori knowledge about the cipher system except its input and output. Black-Box model is constructed using Artificial Neural Networks to attack the target cipher system, with the addition of building an equivalent Neuro-Model for the target cipher system. In cryptanalysis terminology, it is a known-plaintext attack. The constructed Neuro-Identifier has been used in two different approaches; the objective of the first approach is to determine the enciphering key, which is a total break and represent the ultimate performance of any cryptanalysis method. The cryptanalysis objectives are achieved in this approach. The aim of the second approach is to build an equivalent Neuro-Model for the target cipher system, which presents a new direction in cryptology. The constructed Neuro-Model can be regarded as an equivalent model for the real target system, which is a valuable product in many cases where the real system is not available. 120 pp. Englisch. Bestandsnummer des Verkäufers 9783330975613
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Black-Box Attack Using Neuro-Identifier
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, the cryptanalysis problem of unknown cipher system is presented as a Black-Box, nonlinear, system identification problem, which assumes no priori knowledge about the cipher system except its input and output. Black-Box model is constructed using Artificial Neural Networks to attack the target cipher system, with the addition of building an equivalent Neuro-Model for the target cipher system. In cryptanalysis terminology, it is a known-plaintext attack. The constructed Neuro-Identifier has been used in two different approaches; the objective of the first approach is to determine the enciphering key, which is a total break and represent the ultimate performance of any cryptanalysis method. The cryptanalysis objectives are achieved in this approach. The aim of the second approach is to build an equivalent Neuro-Model for the target cipher system, which presents a new direction in cryptology. The constructed Neuro-Model can be regarded as an equivalent model for the real target system, which is a valuable product in many cases where the real system is not available. Bestandsnummer des Verkäufers 9783330975613
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Al ubaidy Mahmood KhalelQualifications: Ph. D. (Computer Science & Inf. Systems). Al-Nahrain UniversitySpecialization: Information & Network SecurityTeaching Area(s): Cryptography & Network Security, Artificial Intelligence, Manageme. Bestandsnummer des Verkäufers 157880802
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Black-Box Attack Using Neuro-Identifier
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Paperback. Zustand: Brand New. 120 pages. 8.66x5.91x0.28 inches. In Stock. Bestandsnummer des Verkäufers 333097561X
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, the cryptanalysis problem of unknown cipher system is presented as a Black-Box, nonlinear, system identification problem, which assumes no priori knowledge about the cipher system except its input and output. Black-Box model is constructed using Artificial Neural Networks to attack the target cipher system, with the addition of building an equivalent Neuro-Model for the target cipher system. In cryptanalysis terminology, it is a known-plaintext attack. The constructed Neuro-Identifier has been used in two different approaches; the objective of the first approach is to determine the enciphering key, which is a total break and represent the ultimate performance of any cryptanalysis method. The cryptanalysis objectives are achieved in this approach. The aim of the second approach is to build an equivalent Neuro-Model for the target cipher system, which presents a new direction in cryptology. The constructed Neuro-Model can be regarded as an equivalent model for the real target system, which is a valuable product in many cases where the real system is not available.Books on Demand GmbH, Überseering 33, 22297 Hamburg 120 pp. Englisch. Bestandsnummer des Verkäufers 9783330975613
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Taschenbuch. Zustand: Neu. Black-Box Attack Using Neuro-Identifier | Mahmood Khalel Al ubaidy | Taschenbuch | 120 S. | Englisch | 2017 | Noor Publishing | EAN 9783330975613 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 109545818
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