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  5. Enabling non-expert analysis of large volumes of intercepted network traffic
 
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Enabling non-expert analysis of large volumes of intercepted network traffic

Author(s)
Wiel, Erwin van de  
Scanlon, Mark  
Le-Khac, Nhien-An  
Uri
http://hdl.handle.net/10197/25079
Date Issued
2018-08-30
Date Available
2023-11-29T10:26:05Z
Abstract
Telecommunications wiretaps are commonly used by law enforcement in criminal investigations. While phone-based wiretapping has seen considerable success, the same cannot be said for Internet taps. Large portions of intercepted Internet traffic are often encrypted, making it difficult to obtain useful information. The advent of the Internet of Things further complicates network wiretapping. In fact, the current level of complexity of intercepted network traffic is almost at the point where data cannot be analyzed without the active involvement of experts. Additionally, investigations typically focus on analyzing traffic in chronological order and predominately examine the data content of the intercepted traffic. This approach is overly arduous when the amount of data to be analyzed is very large. This chapter describes a novel approach for analyzing large amounts of intercepted network traffic based on traffic metadata. The approach significantly reduces the analysis time and provides useful insights and information to non-technical investigators. The approach is evaluated using a large sample of network traffic data.
Type of Material
Conference Publication
Publisher
Springer
Series
IFIP Advances in Information and Communication Technology
532
Copyright (Published Version)
2018 IFIP International Federation for Information Processing
Subjects

Internet taps

Network forensics

Traffic metadata anal...

DOI
10.1007/978-3-319-99277-8_11
Web versions
http://www.ifip119.org/Conferences/
Language
English
Status of Item
Peer reviewed
Journal
Peterson, G. and Shenoi, S. (Eds.). Advances in Digital Forensics XIV
Conference Details
The Fourteenth Annual IFIP WG 11.9 International Conference on Digital Forensics (Digital Forensics 2018), New Delhi, India, 3-5 January 2018
ISBN
9783319992761
ISSN
1868-4238
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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NetworkIntell.pdf

Size

229.02 KB

Format

Adobe PDF

Checksum (MD5)

0886a0c567922bdfbbd0906f90c82c2f

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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