語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Detecting LDAP Misuse in a Distribut...
~
Omolola, Godwin.
FindBook
Google Book
Amazon
博客來
Detecting LDAP Misuse in a Distributed Big Data Environment.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Detecting LDAP Misuse in a Distributed Big Data Environment./
作者:
Omolola, Godwin.
面頁冊數:
154 p.
附註:
Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
Contained By:
Dissertation Abstracts International76-06B(E).
標題:
Information Technology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3682128
ISBN:
9781321552652
Detecting LDAP Misuse in a Distributed Big Data Environment.
Omolola, Godwin.
Detecting LDAP Misuse in a Distributed Big Data Environment.
- 154 p.
Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
Thesis (D.C.S.)--Colorado Technical University, 2014.
This item must not be sold to any third party vendors.
Increasingly, organizations are looking to big data analytic tools for information security visibility because existing security programs are not sufficiently doing the job. Recurrent theme from literature also emphasized the importance of detection in security programs. This study examines big data in the context of providing intelligence-driven security, thereby improving network security visibility in an application cluster. The research premise is that it is possible to derive intelligence insight using big data analytic tools to detect attacks on Lightweight Directory Access Protocol (LDAP) when all data into and out of a computing environment is analyzed for hidden patterns and content. Knowledge gained from the analysis of system resource measurements like virtual memory utilization and amount of data written to disk when combined with other network events helps to spot malicious behavior attributed to LDAP misuse in real time. A simulated environment was designed to detect LDAP misuse responsible for most injection attacks in a distributed environment. The big data security analytical technique model captures LDAP misuse and provides ability to take corrective action and protect the system.
ISBN: 9781321552652Subjects--Topical Terms:
1030799
Information Technology.
Detecting LDAP Misuse in a Distributed Big Data Environment.
LDR
:02151nmm a2200289 4500
001
2057907
005
20150622091142.5
008
170521s2014 ||||||||||||||||| ||eng d
020
$a
9781321552652
035
$a
(MiAaPQ)AAI3682128
035
$a
AAI3682128
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Omolola, Godwin.
$3
3171800
245
1 0
$a
Detecting LDAP Misuse in a Distributed Big Data Environment.
300
$a
154 p.
500
$a
Source: Dissertation Abstracts International, Volume: 76-06(E), Section: B.
500
$a
Adviser: Imad Al Saeed.
502
$a
Thesis (D.C.S.)--Colorado Technical University, 2014.
506
$a
This item must not be sold to any third party vendors.
520
$a
Increasingly, organizations are looking to big data analytic tools for information security visibility because existing security programs are not sufficiently doing the job. Recurrent theme from literature also emphasized the importance of detection in security programs. This study examines big data in the context of providing intelligence-driven security, thereby improving network security visibility in an application cluster. The research premise is that it is possible to derive intelligence insight using big data analytic tools to detect attacks on Lightweight Directory Access Protocol (LDAP) when all data into and out of a computing environment is analyzed for hidden patterns and content. Knowledge gained from the analysis of system resource measurements like virtual memory utilization and amount of data written to disk when combined with other network events helps to spot malicious behavior attributed to LDAP misuse in real time. A simulated environment was designed to detect LDAP misuse responsible for most injection attacks in a distributed environment. The big data security analytical technique model captures LDAP misuse and provides ability to take corrective action and protect the system.
590
$a
School code: 1271.
650
4
$a
Information Technology.
$3
1030799
650
4
$a
Computer Science.
$3
626642
690
$a
0489
690
$a
0984
710
2
$a
Colorado Technical University.
$b
Information Technology.
$3
2105964
773
0
$t
Dissertation Abstracts International
$g
76-06B(E).
790
$a
1271
791
$a
D.C.S.
792
$a
2014
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3682128
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9290411
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入