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1
Introduction
2
What is data?
3
Getting data
4
Non-standard source data
5
Removing things from raw data
6
Storing data
7
Converting data to JSON (scripts)
8
A word about our schema: VERIS
9
Converting data to JSON (schema)
10
Validating Data
11
Exploring the data
12
Finding novel findings (hypotheses)
13
A word about non-incident data
14
Deciding what constitutes the dataset
15
Generating statistics (hypotheses)
16
Validation - Generating consistent, quality figures
17
Validating analysis (hypotheses)
18
Looking ahead
19
The complexity apocalypse
Description:
Explore the intricacies of data analysis in cybersecurity through this comprehensive BSidesLV conference talk. Delve into the process of handling and interpreting data from the Verizon Data Breach Investigations Report (DBIR). Learn about data collection, cleaning, storage, and conversion techniques, with a focus on the VERIS schema. Discover methods for exploring datasets, generating hypotheses, and validating findings. Gain insights into the challenges of non-standard data sources, non-incident data, and the complexities of dataset definition. Understand the importance of consistent and quality figure generation, as well as the validation of analysis results. Prepare for future challenges in data complexity as you enhance your skills in cybersecurity data analysis.

Dominating the DBIR Data

BSidesLV
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