Security of Data Science and Data Science for Security

2Citations
Citations of this article
23Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this chapter, we present a brief overview of important topics regarding the connection of data science and security. In the first part, we focus on the security of data science and discuss a selection of security aspects that data scientists should consider to make their services and products more secure. In the second part about security for data science, we switch sides and present some applications where data science plays a critical role in pushing the state-of-the-art in securing information systems. This includes a detailed look at the potential and challenges of applying machine learning to the problem of detecting obfuscated JavaScripts.

Cite

CITATION STYLE

APA

Tellenbach, B., Rennhard, M., & Schweizer, R. (2019). Security of Data Science and Data Science for Security. In Applied Data Science: Lessons Learned for the Data-Driven Business (pp. 265–288). Springer International Publishing. https://doi.org/10.1007/978-3-030-11821-1_15

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free