Trusted CI Webinar: Data Quality & Security Evaluation Framework Development with Leon Reznik & Igor Khokhlov

Reznik, Leon; Khokhlov, Igor

Permalink

https://hdl.handle.net/2142/99558 Copy

Description

Title

Trusted CI Webinar: Data Quality & Security Evaluation Framework Development with Leon Reznik & Igor Khokhlov

Author(s)

• Reznik, Leon
• Khokhlov, Igor

Issue Date

2018-03-26

Keyword(s)

• Webinar
• NSF
• Cybersecurity
• Trusted CI

Abstract

In this talk, we are presenting our work on building a data quality and security (DQS) framework, which integrates cybersecurity with other diverse metrics, such as accuracy, reliability, timeliness, and safety into a single methodological and technological framework. This innovation has a high potential to enable a significant improvement in a wide spectrum of science and technology applications as it will create new opportunities for optimizing data structures, data processing and fusion procedures based on a new quality and security information application. While the developed evaluation techniques may cover a wide range of data sources, the current framework’s implementation concentrates on using an ordinary user’s owned mobile devices and Android-based smartphones in particular. After discussing a motivation and general concepts of data quality evaluation, we will present preliminary results. As the framework integrates various metrics from accuracy to security and privacy, we will show examples of cyberinfrastructure elements from those areas developed so far. The security evaluation aspect of the framework is introduced with the Android applications that evaluate a smartphone security, gives a comprehensive score, and advises how the smartphone security can be improved. Two applications that are already available on Google Play will be presented and discussed. In addition, we will show some examples of the framework’s user interface designed for data quality metrics assignment and demonstrate its visualization capabilities. The data privacy evaluation is presented with the investigation of the colluded application vulnerability in Android OS devices. We will discuss and analyze the results achieved in this domain. We believe that DQS evaluation framework will stimulate further improvement of the quality of the whole cyberinfrastructure and, in particular, cybersecurity. We will discuss possible further developments and seek the feedback and advice on the further DQS evaluation research directions. In particular, we are looking for a collaboration in the development of our framework applications in various science and technology domains. Leon Reznik is a Professor of Computer Science (primary affiliation) and Computing Security (secondary affiliation) at the Rochester Institute of Technology. His current research concentrates on data quality and security evaluation and assurance; cognitive sensor networks and systems; intelligent intrusion detection and big data analytics. Igor Khokhlov is a Ph.D. candidate at the Rochester Institute of Technology. He conducts research on data quality and value evaluation for sensor-originated data. Igor’s fields of interest include Android OS, cyber-security, and AI.

Type of Resource

• text
• image

Language

en

Permalink

http://hdl.handle.net/2142/99558

Sponsor(s)/Grant Number(s)

• NSF ACI-1547301
• NSF Grant #1547272; NSF Grant #1547301

Copyright and License Information

Copyright © 2019 The Trustees of Indiana University. This work is licensed under a Creative Commons Attribution-­NonCommercial 3.0 Unported (CC BY­NC 3.0) license.

Owning Collections