國立虎尾科技大學 |

Distributed Data Streaming Algorithms for Network Anomaly Detection.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Distributed Data Streaming Algorithms for Network Anomaly Detection./
作者:	Chen, Wenji.
面頁冊數:	1 online resource (107 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-11(E), Section: B.
Contained By:	Dissertation Abstracts International78-11B(E).
標題:	Computer engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9781369878547

Distributed Data Streaming Algorithms for Network Anomaly Detection.
Chen, Wenji.

Distributed Data Streaming Algorithms for Network Anomaly Detection. - 1 online resource (107 pages)

Source: Dissertation Abstracts International, Volume: 78-11(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Network attacks and anomalies such as DDoS attacks, service outages, email spamming are happening everyday, causing various problems for users such as financial loss, inconvenience due to service unavailability, personal information leakage and so on. Different methods have been studied and developed to tackle these network attacks, and among them data streaming algorithms are quite powerful, useful and flexible schemes that have many applications in network attack detection and identification. Data streaming algorithms usually use limited space to store aggregated information and report certain properties of the traffic in short and constant time.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369878547Subjects--Topical Terms:

569006
Computer engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Distributed Data Streaming Algorithms for Network Anomaly Detection.
LDR:03019ntm a2200361Ki 4500 001 910709
005 20180517112608.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9781369878547
035 $a (MiAaPQ)AAI10245404
035 $a (MiAaPQ)iastate:16194
035 $a AAI10245404
040 $a MiAaPQ $b eng $c MiAaPQ
099 $a TUL $f hyy $c available through World Wide Web
100 1 $a Chen, Wenji. $3 1182143
245 1 0 $a Distributed Data Streaming Algorithms for Network Anomaly Detection.
264 0 $c 2017
300 $a 1 online resource (107 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: Dissertation Abstracts International, Volume: 78-11(E), Section: B.
500 $a Adviser: Yong Guan.
502 $a Thesis (Ph.D.) $c Iowa State University $d 2017.
504 $a Includes bibliographical references
520 $a Network attacks and anomalies such as DDoS attacks, service outages, email spamming are happening everyday, causing various problems for users such as financial loss, inconvenience due to service unavailability, personal information leakage and so on. Different methods have been studied and developed to tackle these network attacks, and among them data streaming algorithms are quite powerful, useful and flexible schemes that have many applications in network attack detection and identification. Data streaming algorithms usually use limited space to store aggregated information and report certain properties of the traffic in short and constant time.
520 $a There are several challenges for designing data streaming algorithms. Firstly, network traffic is usually distributed and monitored at different locations, and it is often desirable to aggregate the distributed monitoring information together to detect attacks which might be low-profile at a single location; thus data streaming algorithms have to support data merging without loss of information. Secondly, network traffic is usually in high-speed and large-volume; data streaming algorithms have to process data fast and smart to save space and time. Thirdly, sometimes only detection is not useful enough and identification of targets make more sense, in which case data streaming algorithms have to be concise and reversible.
520 $a In this dissertation, we study three different types of data streaming algorithms: hot item identification, distinct element counting and superspreader identification. We propose new algorithms to solve these problems and evaluate them with both theoretical analysis and experiments to show their effectiveness and improvements upon previous methods.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer engineering. $3 569006
655 7 $a Electronic books. $2 local $3 554714
690 $a 0464
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Iowa State University. $b Electrical and Computer Engineering. $3 1179387
773 0 $t Dissertation Abstracts International $g 78-11B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10245404 $z click for full text (PQDT)