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Survey of Data Leakage Detection and Prevention Solutions 2012 [Mīkstie vāki]

  • Formāts: Paperback / softback, 92 pages, height x width: 235x155 mm, weight: 454 g, 9 Illustrations, black and white; VIII, 92 p. 9 illus., 1 Paperback / softback
  • Sērija : SpringerBriefs in Computer Science
  • Izdošanas datums: 16-Mar-2012
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1461420520
  • ISBN-13: 9781461420521
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  • Formāts: Paperback / softback, 92 pages, height x width: 235x155 mm, weight: 454 g, 9 Illustrations, black and white; VIII, 92 p. 9 illus., 1 Paperback / softback
  • Sērija : SpringerBriefs in Computer Science
  • Izdošanas datums: 16-Mar-2012
  • Izdevniecība: Springer-Verlag New York Inc.
  • ISBN-10: 1461420520
  • ISBN-13: 9781461420521
Citas grāmatas par šo tēmu:
SpringerBriefs present concise summaries of cutting-edge research and practical applications across a wide spectrum of fields. Featuring compact volumes of 50 to 100 pages (approximately 20,000- 40,000 words), the series covers a range of content from professional to academic. Briefs allow authors to present their ideas and readers to absorb them with minimal time investment. As part of Springers eBook collection, SpringBriefs are published to millions of users worldwide.

Information/Data Leakage poses a serious threat to companies and organizations, as the number of leakage incidents and the cost they inflict continues to increase. Whether caused by malicious intent, or an inadvertent mistake, data loss can diminish a companys brand, reduce shareholder value, and damage the companys goodwill and reputation. This book aims to provide a structural and comprehensive overview of the practical solutions and current research in the DLP domain. This is the first comprehensive book that is dedicated entirely to the field of data leakage and covers all important challenges and techniques to mitigate them. Its informative, factual pages will provide researchers, students and practitioners in the industry with a comprehensive, yet concise and convenient reference source to this fascinating field.

We have grouped existing solutions into different categories based on a described taxonomy. The presented taxonomy characterizes DLP solutions according to various aspects such as: leakage source, data state, leakage channel, deployment scheme, preventive/detective approaches, and the action upon leakage. In the commercial part we review solutions of the leading DLP market players based on professional research reports and material obtained from the websites of the vendors. In the academic part we cluster the academic work according to the nature of the leakage and protection into various categories. Finally, we describe main data leakage scenarios and present for eachscenario the most relevant and applicable solution or approach that will mitigate and reduce the likelihood and/or impact of the leakage scenario.

Recenzijas

From the reviews:

Springer Briefs is a series of short books to help information and communications technology (ICT) professionals learn about new or unfamiliar technologies. This work is from that series, providing an introduction to the detection of corporate data loss and leaks. the book amounts to a good, concise brief for quickly coming to grips with the basics of protecting corporate data from leakage and loss. There is a good table of contents and a thorough list of references. (David B. Henderson, ACM Computing Reviews, September, 2012)

1 Introduction to Information Security
1(4)
2 Data Leakage
5(6)
3 A Taxonomy of Data Leakage Prevention Solutions
11(6)
3.1 What to protect? (data-state)
11(1)
3.2 Where to protect? (deployment scheme)
12(1)
3.3 How to protect? (leakage handling approach)
13(4)
4 Data Leakage Detection/Prevention Solutions
17(22)
4.1 A review of commercial DLP solutions
11(10)
4.1.1 Market overview
17(1)
4.1.2 Technological offerings of market leaders
17(2)
4.1.3 Conclusions, remarks, and problems with the state of the art in industrial DLP
19(2)
4.2 Academic research in the DLP domain
21(18)
4.2.1 Misuse detection in information retrieval (IR) systems
24(2)
4.2.2 Misuse detection in databases
26(2)
4.2.3 Email leakage protection
28(2)
4.2.4 Network/web-based protection
30(1)
4.2.5 Encryption and access control
31(2)
4.2.6 Hidden data in files
33(1)
4.2.7 Honeypots for detecting malicious insiders
34(5)
5 Data Leakage/Misuse Scenarios
39(8)
5.1 Classification of data leakage/misuse scenarios
39(2)
5.1.1 Where did the leakage occur?
39(1)
5.1.2 Who caused the leakage?
39(1)
5.1.3 What was leaked?
40(1)
5.1.4 How was access to the data gained?
40(1)
5.1.5 How did the data leak?
41(1)
5.2 Description of main data leakage/misuse scenarios
41(5)
5.3 Discussion
46(1)
6 Privacy, Data Anonymization, and Secure Data Publishing
47(22)
6.1 Introduction to data anonymization
47(1)
6.2 Elementary anonymization operations
48(4)
6.2.1 Generalization
48(3)
6.2.2 Suppression
51(1)
6.2.3 Permutation
51(1)
6.2.4 Perturbation
51(1)
6.3 Privacy models
52(6)
6.3.1 Basic concepts
52(1)
6.3.2 k-Anonymity
52(2)
6.3.3 L-Diversity
54(1)
6.3.4 X-Uncertainty
55(1)
6.3.5 (X,Y)-Privacy
56(1)
6.3.6 (X,Y)-Anonymity
56(1)
6.3.7 (X,Y)-Linkability
57(1)
6.4 Metrics
58(2)
6.4.1 Information metrics
58(1)
6.4.2 Search metrics
59(1)
6.5 Standard anonymization algorithms
60(2)
6.6 Multiple-release publishing
62(7)
6.6.1 Single vs. multiple-release publishing
63(1)
6.6.2 Publishing releases in parallel
63(1)
6.6.3 Publishing releases in sequence
64(1)
6.6.4 Anonymizing sequential releases
64(5)
7 Case studies
69(14)
7.1 Misuse detection in database systems
69(7)
7.1.1 Applying unsupervised context-based analysis
70(4)
7.1.2 Calculating a misusability score for tabular data
74(2)
7.2 Using honeytokens
76(3)
7.3 Email leakage
79(4)
8 Future Trends in Data Leakage
83(4)
References 87