Paper 2015/728

Provable Virus Detection: Using the Uncertainty Principle to Protect Against Malware

Richard J. Lipton, Rafail Ostrovsky, and Vassilis Zikas

Abstract

Protecting software from malware injection is the holy grail of modern computer security. Despite intensive efforts by the scientific and engineering community, the number of successful attacks continues to increase. We have a breakthrough novel approach to provably detect malware injection. The key idea is to use the very insertion of the malware itself to allow for the systems to detect it. This is, in our opinion, close in spirit to the famous Heisenberg Uncertainty Principle. The attackers, no matter how clever, no matter when or how they insert their malware, change the state of the system they are attacking. This fundamental idea is a game changer. And our system does not rely on heuristics; instead, our scheme enjoys the unique property that it is proved secure in a formal and precise mathematical sense and with minimal and realistic CPU modification achieves strong provable security guarantees. Thus, we anticipate our system and formal mathematical security treatment to open new directions in software protection.