Security assessment of data management systems for cyber physical system applications. Issue 2 (4th December 2019)

• Record Type: Journal Article
• Authors: Chaudhry, Natalia; Yousaf, Muhammad Murtaza; Khan, Muhammad Taimoor
• Other Names: Mashkoor Atif guestEditor.; Sametinger Johannes guestEditor.; Biro Miklós guestEditor.; Egyed Alexander guestEditor.
• Is Part Of: Journal of software. Volume 32:Issue 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-04
• Subjects: access control security -- CPS -- data integrity -- data security; Software engineering -- Periodicals; Computer software -- Development -- Periodicals; Software maintenance -- Periodicals; 005.1
• DOI: 10.1002/smr.2241
• Languages: English
• ISSNs: 2047-7473

Abstract

Abstract: Cyber physical system (CPS) applications are widely used to control critical infrastructure of various application domains, eg, medical health care, energy, and power, to name a few. Such applications usually take input data from sensors, estimate current state of the system, and then based on the estimation, make critical decisions to control the underlying infrastructure automatically. Therefore, security and integrity of the (system state) data are critically important to ensure safe operations of CPS. In this paper, we present a review of security of various data management systems used in CPS. Since CPS are composed of systems of (sub)systems that generate a huge amount of data (ie, periodical sensor input data), therefore, recently, NoSQL and NewSQL data management systems have emerged as popular data management systems to support efficient and scalable analysis of unstructured data. Unfortunately, these systems were not initially build for data security and thus are vulnerable to numerous security attacks. Considering flexible data model and efficient access methods in NoSQL and NewSQL, we discuss the security attacks on such data management systems and their corresponding solutions to mitigate them. In particular, we analyze the system and data security of popular NoSQL and NewSQL systems. To analyze that, we defined feature vectors for system and data security and compared the data systems against them. Finally, we propose security solutions for data management systems by identifying various security vulnerabilities in internal security algorithms of such systems.