Runtime verification of hyperproperties for deterministic programs
Paper i proceeding, 2018

In this paper, we consider the runtime verification problem of safety hyperproperties for deterministic programs. Several security and information-flow policies such as data minimality, non-interference, integrity, and software doping are naturally expressed formally as safety hyperproperties. Although there are monitoring results for hyperproperties, the algorithms are very complex since these are properties over set of traces, and not over single traces. For the deterministic input-output programs that we consider, and the specific safety hyperproperties we are interested in, the problem can be reduced to monitoring of trace properties. In this paper, we present a simpler monitoring approach for safety hyperproperties of deterministic programs. The approach involves transforming the given safety hyperproperty into a trace property, extracting a characteristic predicate for the given hyperproperty, and providing a parametric monitor taking such predicate as parameter. For any hyperproperty in the considered subclass, we show how runtime verification monitors can be synthesised. We have implemented our approach in the form of a parameterised monitor for the given class, and have applied it to a number of hyperproperties including data minimisation, non-interference, integrity and software doping. We show results concerning both offline and online monitoring.

Monitoring

Security

Information-flow

Runtime Verification

Författare

Srinivas Pinisetty

Göteborgs universitet

Gerardo Schneider

Göteborgs universitet

David Sands

Chalmers, Data- och informationsteknik, Informationssäkerhet

Proceedings - International Conference on Software Engineering

02705257 (ISSN)

20-29 3193995
978-145035718-0 (ISBN)

6th ACM/IEEE Conference on Formal Methods in Software Engineering, FormaliSE 2018, co-located with International Conference on Software Engineering, ICSE 2018
Gothenburg, Sweden,

Ämneskategorier

Annan data- och informationsvetenskap

Datavetenskap (datalogi)

Datorsystem

DOI

10.1145/3193992.3193995

Mer information

Senast uppdaterat

2019-07-08