Update from the DATA CORE: Services Utilization Form (SUF) Aids Network Data Collection Efforts

2003 ◽  
Author(s):  
Keyword(s):  
Data Collection ◽  
Network Data ◽  
Services Utilization

scholarly journals The Challenges of Effectively Anonymizing Network Data

2013 ◽  
pp. 15-22
Author(s):  
Ch. Himabindu
Keyword(s):  
Network Security ◽  
Information Security ◽  
Data Collection ◽  
Network Data ◽  
Sensitive Information ◽  
Security Testing ◽  
The Past ◽  
Technical Leadership ◽  
Security Research ◽  
Privacy Issues

The availability of realistic network data plays a significant role in fostering collaboration and ensuring U.S. technical leadership in network security research. Unfortunately, a host of technical, legal, policy, and privacy issues limit the ability of operators to produce datasets for information security testing. In an effort to help overcome these limitations, several data collection efforts (e.g., CRAWDAD[14], PREDICT [34]) have been established in the past few years. The key principle used in all of these efforts to assure low-risk, high-value data is that of trace anonymization—the process of sanitizing data before release so that potentially sensitive information cannot be extracted.

scholarly journals A survey on network data collection

2018 ◽  
Vol 116 ◽  
pp. 9-23 ◽  
Author(s):  
Donghao Zhou ◽  
Zheng Yan ◽  
Yulong Fu ◽  
Zhen Yao
Keyword(s):  
Data Collection ◽  
Network Data

Social Network Construction in the Information Age

2011 ◽  
pp. 131-155 ◽  
Author(s):  
Michael Farrugia ◽  
Neil Hurley ◽  
Diane Payne ◽  
Aaron Quigley
Keyword(s):  
Social Network ◽  
Data Collection ◽  
Information Age ◽  
Network Data ◽  
Electronic Data ◽  
Network Construction ◽  
Electronic Data Collection ◽  
Social Network Data

In this chapter, the authors will discuss the differences between manual data collection and electronic data collection to understand the advantages and the challenges brought by electronic social network data. They will discuss in detail the processes that are used to transform electronic data to social network data and the procedures that can be used to validate the resultant social network.

scholarly journals Wireless Sensor Networks Scheduling Algorithm Based on the Probability of Monitoring

2012 ◽  
Vol 4 ◽  
pp. 32-37
Author(s):  
Jin Song Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Scheduling Algorithm ◽  
Wireless Sensor ◽  
Network Data ◽  
Sleep Scheduling ◽  
Node Scheduling ◽  
Collection Data ◽  
Perceived Probability

This paper introduces the basics of wireless sensor networks, focusing on the concept of sensor network data collection, data collection mechanisms, data collection in-network data aggregation, data collection and data collection applications Research. This paper presents the data collection in WSN node scheduling concept, analyzed the two data collection in WSN scheduling mechanism, which is based on data collection interval node scheduling mechanism and turn the data based on perceived probability of node sleep scheduling mechanism.

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