TY - GEN
T1 - Data quality assessment
T2 - 2012 5th International Symposium on Resilient Control Systems, ISRCS 2012
AU - Garcia, Humberto E.
AU - Lin, Wen Chiao
AU - Meerkov, Semyon M.
AU - Ravichandran, Maruthi T.
PY - 2012
Y1 - 2012
N2 - This paper presents a novel data quality model as part of a monitoring system that degrades gracefully under attacks on its sensors. The attacker is assumed to manipulate the sensor data's variance or mean, with the aim of projecting a false state of the plant. Each sensor's data is assigned a level of trust, termed data quality, as part of assessing the states of the process variables. For the variance-based attacker, it is established that the concept of data quality is not, in fact, necessary to obtain the best possible assessment. For the mean-based attacker, it is recognized that statistical means are not sufficient to discern data quality. To combat this problem, the so-called method of probing signals is proposed. The efficacy of this method is illustrated by numerical experiments categorized into two parts. The first deals with individual process variable assessment, while the second deals with the adaptation of the sensor network to obtain the best possible plant assessment.
AB - This paper presents a novel data quality model as part of a monitoring system that degrades gracefully under attacks on its sensors. The attacker is assumed to manipulate the sensor data's variance or mean, with the aim of projecting a false state of the plant. Each sensor's data is assigned a level of trust, termed data quality, as part of assessing the states of the process variables. For the variance-based attacker, it is established that the concept of data quality is not, in fact, necessary to obtain the best possible assessment. For the mean-based attacker, it is recognized that statistical means are not sufficient to discern data quality. To combat this problem, the so-called method of probing signals is proposed. The efficacy of this method is illustrated by numerical experiments categorized into two parts. The first deals with individual process variable assessment, while the second deals with the adaptation of the sensor network to obtain the best possible plant assessment.
KW - Data Quality
KW - Graceful Degradation
KW - Malicious Attacker
KW - Rational Controller
KW - Resilient Monitoring
KW - Sensor Networks
UR - https://www.scopus.com/pages/publications/84868577796
U2 - 10.1109/ISRCS.2012.6309305
DO - 10.1109/ISRCS.2012.6309305
M3 - Conference contribution
AN - SCOPUS:84868577796
SN - 9781467301633
T3 - Proceedings - 2012 5th International Symposium on Resilient Control Systems, ISRCS 2012
SP - 124
EP - 129
BT - Proceedings - 2012 5th International Symposium on Resilient Control Systems, ISRCS 2012
Y2 - 14 August 2012 through 16 August 2012
ER -