Discovering Implicit Redundancies in Network Communications for Detecting Inconsistent Values

Abstract

Detecting inconsistent values received in a communication is a challenging problem faced in networked systems. Inconsistent values occur when a message contains incorrect data, even though the syntax is correct and there is no corruption due to transmission errors. In many cases, traditional schemes based on voting protocols or error detection codes cannot be used. An alternative is discovering implicit redundancies, or patterns that model a correct communication, and using these patterns to detect inconsistent values. However, existing techniques do not cover the inputs and sequential patterns needed by this problem. In this paper, we propose a novel technique that considers messages with multiple types and attributes, events involving variables, and a heuristic for reducing redundant information. Experiments show that the discovered redundancies can achieve reasonable error detection coverage in fields where sequential relations exist, without implying in a large number of false alarms or a high latency.