Visible to the public Transient Security and Dependability Analysis of MEC Micro Datacenter under Attack

TitleTransient Security and Dependability Analysis of MEC Micro Datacenter under Attack
Publication TypeConference Paper
Year of Publication2021
AuthorsLiu, Bo, Bobbio, Andrea, Bai, Jing, Martinez, Jose, Chang, Xiaolin, Trivedi, Kishor S.
Conference Name2021 Annual Reliability and Maintainability Symposium (RAMS)
KeywordsMarkov chain, Multi-access Edge Computing, Numerical models, pubcrawl, quantitative analysis, Random access memory, resilience, Resiliency, Resistance, Scalability, security, Servers, simulation, Stochastic Computing Security, Stochastic Reward Nets, Transient analysis, Virtual machining
AbstractSUMMARY & CONCLUSIONSA Multi-access Edge Computing (MEC) micro data center (MEDC) consists of multiple MEC hosts close to endpoint devices. MEC service is delivered by instantiating a virtualization system (e.g., Virtual Machines or Containers) on a MEC host. MEDC faces more new security risks due to various device connections in an open environment. When more and more IoT/CPS systems are connected to MEDC, it is necessary for MEC service providers to quantitatively analyze any security loss and then make defense-related decision. This paper develops a CTMC model for quantitatively analyzing the security and dependability of a vulnerable MEDC system under lateral movement attacks, from the adversary's initial successful access until the MEDC becomes resistant to the attack. The proposed model captures the behavior of the system in a scenario where (i) the rate of vulnerable MEC servers being infected increases with the increasing number of infected MEC servers, (ii) each infected MEC server can perform its compromising activity independently and randomly, and (iii) any infected MEC may fail and then cannot provide service. We also introduce the formulas for computing metrics. The proposed model and formula are verified to be approximately accurate by comparing numerical results and simulation results.
DOI10.1109/RAMS48097.2021.9605723
Citation Keyliu_transient_2021