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What is Deep Packet Inspection

Handbook of Research on Computational Forensics, Digital Crime, and Investigation: Methods and Solutions
A form of packet filtering that examines not only the header part of packets but also the data content of packets.
Published in Chapter:
Deception Detection on the Internet
Xiaoling Chen (Stevens Institute of Technology, USA), Rohan D.W. Perera (Stevens Institute of Technology, USA), Ziqian (Cecilia) Dong (Stevens Institute of Technology, USA), Rajarathnam Chandramouli (Stevens Institute of Technology, USA), and Koduvayur P. Subbalakshmi (Stevens Institute of Technology, USA)
DOI: 10.4018/978-1-60566-836-9.ch014
Abstract
This chapter provides an overview of techniques and tools to detect deception on the Internet. A classification of state-of-the-art hypothesis testing and data mining based deception detection methods are presented. A psycho-linguistics based statistical model for deception detection is also described in detail. Passive and active methods for detecting deception at the application and network layer are discussed. Analysis of the pros and cons of the existing methods is presented. Finally, the inter-play between psychology, linguistics, statistical modeling, network layer information and Internet forensics is discussed along with open research challenges.
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Scheduling Large-Scale DNA Sequencing Applications
Deep Packet Inspection (DPI) is a form of computer network packet filtering that examines the data and/or header part of a packet as it passes an inspection point, searching for protocol non-compliance, viruses, spam, intrusions or predefined criteria to decide if the packet can pass or if it needs to be routed to a different destination, or for the purpose of collecting statistical information. This is in contrast to shallow packet inspection which just checks the header portion of a packet.
Full Text Chapter Download: US $37.50 Add to Cart
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