LASARUS: Lightweight attack surface reduction for legacy industrial control systems

5Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Many operational Industrial Control Systems (ICSs) were designed and deployed years ago with little or no consideration of security issues arising from an interconnected world. It is well-known that attackers can read and write sensor and actuator data from Programmable Logic Controllers (PLCs) as legacy ICS offer little means of protection. Replacing such legacy ICS is expensive, requires extensive planning and a major programme of updates often spanning several years. Yet augmenting deployed ICS with established security mechanisms is rarely possible. Legacy PLCs cannot support computationally expensive (i.e., cryptographic) operations while maintaining real-time control. Intrusion Detection Systems (IDSs) have been employed to improve security of legacy ICS. However, attackers can avoid detection by learning acceptable system behaviour from observed data. In this paper, we present LASARUS, a lightweight approach that can be implemented on legacy PLCs to reduce their attack surface, making it harder for an attacker to learn system behaviour and craft useful attacks. Our approach involves applying obfuscation to PLC data whenever it is stored or accessed which leads to a continuous change of the target surface. Obfuscation keys can be refreshed depending on the threat situation, striking a balance between system performance and protection level. Using real-world and simulated ICS data sets, we demonstrate that LASARUS is able to prevent a set of well-known attacks like random or replay injection, by reducing their passing rate significantly—up to a 100 times.

Cite

CITATION STYLE

APA

Le, A., Roedig, U., & Rashid, A. (2017). LASARUS: Lightweight attack surface reduction for legacy industrial control systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10379 LNCS, pp. 36–52). Springer Verlag. https://doi.org/10.1007/978-3-319-62105-0_3

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