東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Key Generation and Secure Coding in Communications and Private Learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Key Generation and Secure Coding in Communications and Private Learning./
Author:	Aldaghri, Nasser.
Description:	1 online resource (146 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 84-01, Section: B.
Contained By:	Dissertations Abstracts International84-01B.
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29274916click for full text (PQDT)
ISBN:	9798438777977

Key Generation and Secure Coding in Communications and Private Learning.
Aldaghri, Nasser.

Key Generation and Secure Coding in Communications and Private Learning. - 1 online resource (146 pages)

Source: Dissertations Abstracts International, Volume: 84-01, Section: B.

Thesis (Ph.D.)--University of Michigan, 2022.

Includes bibliographical references

The increasingly distributed nature of many current and future technologies has introduced many challenges for devices designed for such settings. Devices operating in such environments, such as Internet-of-Things (IoT), medical devices, connected vehicles, etc., typically have limited computational power and rely on batteries to operate. Therefore, efficiency is a paramount requirement for any algorithm designed to be implemented on these devices. Furthermore, these devices typically generate and collect huge amounts of extremely sensitive and personal data, such as health-related data, behavior-related data, etc. As a result, there is a need for security and privacy protections to guard against various attacks. Additionally, since these devices are typically resource-constrained, any algorithm or protocol needs to be efficient to enable its implementation on such devices. Efficient security and privacy solutions are essential to cope with, as well as enable, high deployment rate of such devices for various sensitive applications. In this dissertation, efficient solutions for protecting the security and privacy of data generated by such devices are explored. Low-complexity protocols for generating secret keys in static environments, along with a formulation of threshold-secure coding with a shared key and corresponding coding schemes are presented. Additionally, algorithms for coded machine unlearning for regression problems are presented, as well as a new setup and algorithm for federated learning with opt-out differential privacy are presented and evaluated.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798438777977Subjects--Topical Terms:

649834
Electrical engineering.
Subjects--Index Terms:

SecurityIndex Terms--Genre/Form:

542853
Electronic books.

Key Generation and Secure Coding in Communications and Private Learning.
LDR:03075nmm a2200445K 4500 001 2360660
005 20231015184447.5
006 m o d
007 cr mn ---uuuuu
008 241011s2022 xx obm 000 0 eng d
020 $a 9798438777977
035 $a (MiAaPQ)AAI29274916
035 $a (MiAaPQ)umichrackham004060
035 $a AAI29274916
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Aldaghri, Nasser. $3 3701284
245 1 0 $a Key Generation and Secure Coding in Communications and Private Learning.
264 0 $c 2022
300 $a 1 online resource (146 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-01, Section: B.
500 $a Advisor: Mahdavifar, Hessam.
502 $a Thesis (Ph.D.)--University of Michigan, 2022.
504 $a Includes bibliographical references
520 $a The increasingly distributed nature of many current and future technologies has introduced many challenges for devices designed for such settings. Devices operating in such environments, such as Internet-of-Things (IoT), medical devices, connected vehicles, etc., typically have limited computational power and rely on batteries to operate. Therefore, efficiency is a paramount requirement for any algorithm designed to be implemented on these devices. Furthermore, these devices typically generate and collect huge amounts of extremely sensitive and personal data, such as health-related data, behavior-related data, etc. As a result, there is a need for security and privacy protections to guard against various attacks. Additionally, since these devices are typically resource-constrained, any algorithm or protocol needs to be efficient to enable its implementation on such devices. Efficient security and privacy solutions are essential to cope with, as well as enable, high deployment rate of such devices for various sensitive applications. In this dissertation, efficient solutions for protecting the security and privacy of data generated by such devices are explored. Low-complexity protocols for generating secret keys in static environments, along with a formulation of threshold-secure coding with a shared key and corresponding coding schemes are presented. Additionally, algorithms for coded machine unlearning for regression problems are presented, as well as a new setup and algorithm for federated learning with opt-out differential privacy are presented and evaluated.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 649834
650 4 $a Computer engineering. $3 621879
650 4 $a Computer science. $3 523869
650 4 $a Multimedia communications. $3 590562
653 $a Security
653 $a Privacy
653 $a Internet-of-Things
653 $a Key generation
653 $a Threshold security
653 $a Federated learning
653 $a Secure coding
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0544
690 $a 0984
690 $a 0464
690 $a 0558
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a University of Michigan. $b Electrical and Computer Engineering. $3 3284714
773 0 $t Dissertations Abstracts International $g 84-01B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29274916 $z click for full text (PQDT)