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Data Corruption

About: Data Corruption is a research topic. Over the lifetime, 435 publications have been published within this topic receiving 6784 citations.


Papers
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Patent
04 Jun 2014
TL;DR: In this paper, the last resort zone of the NVM media is associated with a higher risk of data loss or data corruption than other portions of the media and is reserved as unavailable for storing data.
Abstract: A data storage device (DSD) includes a non-volatile memory (NVM) media for storing data. A last resort zone of the NVM media is associated with a higher risk of data loss or data corruption than other portions of the NVM media and is reserved as unavailable for storing data. It is determined whether a current data storage capacity and/or an environmental condition for the NVM media has reached a threshold. The last resort zone is set as available for storing data if it is determined that the threshold has been reached and data is written in the last resort zone.

16 citations

Journal ArticleDOI
TL;DR: A set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system based on a convex and compact polyhedral robust invariant set is used as a set-induced anomaly detector.
Abstract: This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set, then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.

16 citations

Journal ArticleDOI
TL;DR: Cognizance of the causes of imperfect social network data, the importance of proper boundary specification, biases introduced via the employed data collection methods, and characteristics of social network information sources are necessary for SNA analysts to ascertain the resultant social network model's limitations and the inferences that can properly be drawn from the analysis.
Abstract: Social network analysis (SNA) conclusions are drawn on terrorist and dark network data sets that may provide erroneous results due to an indeterminate amount of missing data or data corruption. Compounding these effects, information sources reporting on terrorist groups and other dark network organizations may intentionally or unintentionally provide false data. These introduced errors may be significant as they could produce analytic results that are counter to the true situation, leading to misappropriation of resources, improper strategy adoption, and erroneous actions. Analyst cognizance of the causes of imperfect social network data, the importance of proper boundary specification, biases introduced via the employed data collection methods, and characteristics of social network information sources, particularly inherent informant accuracy assumptions, are necessary for SNA analysts to ascertain the resultant social network model's limitations and the inferences that can properly be drawn from the ana...

16 citations

Patent
Yan Li1
25 Jan 2013
TL;DR: In this paper, a system and methods for programming a set of data onto non-volatile memory elements, maintaining copies of the data pages to be programmed, as well as surrounding data pages, internally or externally to the memory circuit, verifying programming correctness after programming, and upon discovering programming error, recovering the safe copies of corrupted data to be reprogrammed in alternative nonvolatile memories elements.
Abstract: A system and methods for programming a set of data onto non-volatile memory elements, maintaining copies of the data pages to be programmed, as well as surrounding data pages, internally or externally to the memory circuit, verifying programming correctness after programming, and upon discovering programming error, recovering the safe copies of the corrupted data to be reprogrammed in alternative non-volatile memory elements. Additionally, a system and methods for programming one or more sets of data across multiple die of a non-volatile memory system, combining data pages across the multiple die by means such as the XOR operation prior to programming the one or more sets of data, employing various methods to determine the correctness of programming, and upon identifying data corruption, recovering safe copies of data pages by means such as XOR operation to reprogram the pages in an alternate location on the non-volatile memory system.

15 citations

Proceedings ArticleDOI
Keun Soo Yim1
19 May 2014
TL;DR: It is experimentally show that a single-bit error in non-control data can change the final total energy of a large-scale N-body program with ~2.1% probability and the corrupted total energy values have certain biases that can be used to reduce the expected number of re-executions.
Abstract: In N-body programs, trajectories of simulated particles have chaotic patterns if errors are in the initial conditions or occur during some computation steps. It was believed that the global properties (e.g., total energy) of simulated particles are unlikely to be affected by a small number of such errors. In this paper, we present a quantitative analysis of the impact of transient faults in GPU devices on a global property of simulated particles. We experimentally show that a single-bit error in non-control data can change the final total energy of a large-scale N-body program with ~2.1% probability. We also find that the corrupted total energy values have certain biases (e.g., the values are not a normal distribution), which can be used to reduce the expected number of re-executions. In this paper, we also present a data error detection technique for N-body programs by utilizing two types of properties that hold in simulated physical models. The presented technique and an existing redundancy-based technique together cover many data errors (e.g., >97.5%) with a small performance overhead (e.g., 2.3%).

15 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20221
202121
202025
201927
201827
201727