Lightweight and Seamless Memory Randomization for Mission-Critical Services in a Cloud Platform

Joobeom Yun, Ki-Woong Park, Dongyoung Koo and Youngjoo Shin
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Joobeom Yun: Department of Computer and Information Security, Sejong University, Seoul 05006, Korea
Ki-Woong Park: Department of Computer and Information Security, Sejong University, Seoul 05006, Korea
Dongyoung Koo: Department of Electronics and Information Engineering, Hansung University, Seoul 02876, Korea
Youngjoo Shin: Department of Computer and Information Engineering, Kwangwoon University, Seoul 01897, Korea

Energies, 2020, vol. 13, issue 6, 1-15

Abstract: Nowadays, various computing services are often hosted on cloud platforms for their availability and cost effectiveness. However, such services are frequently exposed to vulnerabilities. Therefore, many countermeasures have been invented to defend against software hacking. At the same time, more complicated attacking techniques have been created. Among them, code-reuse attacks are still an effective means of abusing software vulnerabilities. Although state-of-the-art address space layout randomization (ASLR) runtime-based solutions provide a robust way to mitigate code-reuse attacks, they have fundamental limitations; for example, the need for system modifications, and the need for recompiling source codes or restarting processes. These limitations are not appropriate for mission-critical services because a seamless operation is very important. In this paper, we propose a novel ASLR technique to provide memory rerandomization without interrupting the process execution. In addition, we describe its implementation and evaluate the results. In summary, our method provides a lightweight and seamless ASLR for critical service applications.

Keywords: address space layout randomization (ASLR); rerandomization; code-reuse attack; return-oriented programming (ROP); seamless memory randomization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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