Publication:
Public-key cryptography: a hardware implementation and novel neural network-based approach

dc.contributor.advisorYang, Chyan
dc.contributor.authorNguyen, Phong
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentDepartment of Electrical and Computer Engineering
dc.contributor.secondreaderLoomis, Herschel H., Jr.
dc.dateSeptember 1992
dc.date.accessioned2012-11-29T16:19:08Z
dc.date.available2012-11-29T16:19:08Z
dc.date.issued1992-09
dc.description.abstractThe concealment of information passed over a non-secure communication link lies in the complex field of cryptography. Furthermore, when absolutely no secure channel exists for the exchange of a secret key with which data in encrypted and decrypted, the remedy lies in a branch of cryptology known as public-key cryptosystem (PKS). This thesis provides an in-depth study of the public-key cryptosystem. Essential background knowledge is covered leading up to a VLSI implementation of a fast modulo exponentiator based on the sum of residues (SOR) method. Fast modulo exponentiation is vital in the most popular PKS schemes. Furthermore, since all cryptosystems make use of some form of mapping functions, a neural network - an excellent nonlinear mapping techniques - provides a viable medium upon which a possible cryptosystem can be based. In examining this possibility, this thesis presents an adaptation of the back-propagation neural network to a "pseudo" public-key arrangement. Following examination of the network, a key management system is then devised. Finally, a complete top-down block diagram of an entire cryptosystem based on the neural network of this study is proposed.en_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.
dc.description.serviceLieutenant, United States Navyen_US
dc.description.urihttp://archive.org/details/publickeycryptog1094524018
dc.format.extent98 p.en_US
dc.identifier.urihttps://hdl.handle.net/10945/24018
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.subject.authorCryptographyen_US
dc.subject.authorPublic-keyen_US
dc.subject.authorSecret-keyen_US
dc.subject.authorDiscrete logarithmen_US
dc.subject.authorFast exponentiationen_US
dc.subject.authorDiffie-Hellmanen_US
dc.subject.authorRSAen_US
dc.subject.authorInverseen_US
dc.subject.authorGCDen_US
dc.subject.authorNeural networksen_US
dc.subject.authorBack-propagationen_US
dc.subject.authorSum of residuesen_US
dc.subject.authorModulo reducitonen_US
dc.titlePublic-key cryptography: a hardware implementation and novel neural network-based approachen_US
dc.typeThesisen_US
dspace.entity.typePublication
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.nameM.S. in Electrical Engineeringen_US
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