Adaptive Security for Smart Contracts using High Granularity Metrics

Abstract

In this work, we present a systems centric approach towards implementing security in Blockchain ecosystems. First, we detail the motivation for our security approach. Then, we detail the foundation of this approach by describing the concept of inline, Non-invasive High Granularity Metrics (HGMs). Following this, we outline how such metrics can be used effectively to monitor Blockchain ecosystems to detect behavior that is not deemed secure. We describe how they can be used to build whitelist and blacklist access controls in an adaptive manner, and then describe how they can be effectively used to detect potentially malicious behavior that is not yet baked into the access control structures. Finally, we discuss scalability and potential improvements for future work.