Detecting Inconsistent Values Caused by Interaction Faults Using Automatically Located Implicit Redundancies

This paper addresses the problem of detecting inconsistent values caused by interaction faults originated from an external system.This type of error occurs when a correctly formatted message that is not corrupted during transmission is generated with a field that contains incorrect data.When traditional schemes cannot be used, one alternative is resorting to receiver-based strategies that employ implicit redundancies - relations between events or data, often identified by a human expert.We propose an approach for detecting inconsistent values using implicit redundancies which are automatically located in examples of communications.We show that, even without adding any redundant information to the communication, the proposed approach can achieve a reasonable error detection coverage in fields where sequential relations exist.Other aspects, such as false alarms and latency, are also evaluated.

[1]  Carl E. Landwehr,et al.  Basic concepts and taxonomy of dependable and secure computing , 2004, IEEE Transactions on Dependable and Secure Computing.

[2]  Heikki Mannila,et al.  Levelwise Search and Borders of Theories in Knowledge Discovery , 1997, Data Mining and Knowledge Discovery.

[3]  Terran Lane,et al.  An Application of Machine Learning to Anomaly Detection , 1999 .

[4]  Heikki Mannila,et al.  Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.

[5]  P. S. Sastry,et al.  Discovering frequent episodes and learning hidden Markov models: a formal connection , 2005, IEEE Transactions on Knowledge and Data Engineering.

[6]  Gemma C. Garriga Discovering Unbounded Episodes in Sequential Data , 2003, PKDD.

[7]  Donald E. Knuth,et al.  The art of computer programming, volume 3: (2nd ed.) sorting and searching , 1998 .

[8]  Robert S. Swarz,et al.  Reliable Computer Systems: Design and Evaluation , 1992 .

[9]  Marek Wojciechowski Discovering Frequent Episodes in Sequences of Complex Events , 2000, ADBIS-DASFAA Symposium.

[10]  Antal van den Bosch,et al.  Spotting the ‘Odd-one-out’: Data-Driven Error Detection and Correction in Textual Databases , 2006 .

[11]  Heikki Mannila,et al.  Discovering Frequent Episodes in Sequences , 1995, KDD.

[12]  Takashi Nanya,et al.  Injecting Inconsistent Values Caused by Interaction Faults for Experimental Dependability Evaluation , 2008, 2008 Seventh European Dependable Computing Conference.