Work

Data Quality for Security Challenges: Case Studies of Phishing, Malware and Intrusion Detection Datasets

Year: 2019

Type: conference-paper

Abstract: Techniques from data science are increasingly being applied by researchers to security challenges. However, challenges unique to the security domain necessitate painstaking care for the models to be valid and robust. In this paper, we explain key dimensions of data quality relevant for security, illustrate them with several popular datasets for phishing, intrusion detection and malware, indicate operational methods for assuring data quality and seek to inspire the audience to generate high quality datasets for security challenges.

Source: ACM SIGSAC Conference on Computer and Communications Security (CCS)

DOI: 10.1145/3319535.3363267

Authors: Rakesh M. Verma, Victor Zeng, Houtan Faridi

Institution: University of Houston

Language: English

Topic: Data Quality and Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: National Science Foundation

Awards: TWC: Small: Unsupervised and Statistical Natural Language Processing Techniques for Automatic Phishing and Opinion Spam Detection, REU Site: Research Experience for Undergraduates in Data-Centric Computing, Preparing Computer Science Students for Global Challenges of the Twenty-first Century, Scholarships for Service: Increasing Talented Trus