Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Trace-Length Independent Runtime Monitoring of Quantitative Policies

Loading...
Thumbnail Image

Date

Authors

Du, Xiaoning
Tiu, Alwen
Cheng, Kun
Liu, Yang

Journal Title

Journal ISSN

Volume Title

Publisher

IEEE Computer Society

Abstract

Metric linear-time logic (MTL) has been widely used to specify runtime policies. Traditionally this use of MTL is to capture the qualitative aspects of the monitored systems, but recent developments in its extensions with aggregate operators allow some quantitative policies to be specified. Our interest in MTL-based policy languages is driven by applications in runtime malware or intrusion detection in platforms like Android and autonomous vehicles, which requires the monitoring algorithm to be independent of the length of the system event traces so that its performance does not degrade as the traces grow. We propose a policy language based on a past-time variant of MTL, extended with an aggregate operator called the metric temporal counting quantifier to specify a policy based on the number of times some sub-policies are satisfied in the specified past time interval. We show that a broad class of policies, but not all policies, specified with our language can be monitored in a trace-length independent way, and provide a concrete algorithm to do so. We implement and test our algorithm in both an existing Android monitoring framework and an autonomous vehicle simulation platform, and show that our approach can effectively specify and monitor quantitative policies drawn from real-world studies.

Description

Citation

Source

IEEE Transactions on Dependable and Secure Computing

Book Title

Entity type

Access Statement

License Rights

Restricted until

2099-12-31