Using codewords to protect database data from a class of software errors

Bohannon, Philip; Rastogi, Rajeev; Seshadri, S.; Silberschatz, Abraham; Sudarshan, S.

doi:10.1109/icde.1999.754943

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…By logging the identity of the data items read by each transaction, i.e. R(T), previously suggested in [1] to handle application corruption via wild stores of data in a main memory database system, we have enough information recorded on the log to perform the computation of C(T c ) in section 3.1.…”

Section: Tracking Readsmentioning

confidence: 99%

Recovery from "bad" user transactions

Lomet

Vagena

Barga

2006

Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data

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User written transaction code is responsible for the "C" in ACID transactions, i.e., taking the database from one consistent state to the next. However, user transactions can be flawed and lead to inconsistent (or invalid) states. Database systems usually correct invalid data using "point in time" recovery, a costly process that installs a backup and rolls it forward. The result is long outages and the "de-commit" of many valid transactions, which must then be re-submitted, frequently manually. We have implemented in our transaction-time database system a technique in which only data tainted by a flawed transaction and transactions dependent upon its updates are "removed". This process identifies and quarantines tainted data despite the complication of determining transactions dependent on data written by the flawed transaction. A further property of our implementation is that no backup needs to be installed for this because the prior transaction-time states provide an online backup.

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Section: Tracking Readsmentioning

confidence: 99%

Recovery from "bad" user transactions

Lomet

Vagena

Barga

2006

Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data

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“…Researchers have also proposed techniques for protecting critical DBMS structures against errors [5], [29]. These techniques mainly deal with abnormal corruption caused by software errors, not deliberate attacks.…”

Section: Related Workmentioning

confidence: 99%

An Architecture for Regulatory Compliant Database Management

Mitra

Winslett

Snodgrass

et al. 2009

2009 IEEE 25th International Conference on Data Engineering

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Abstract-Spurred by financial scandals and privacy concerns, governments worldwide have moved to ensure confidence in digital records by regulating their retention and deletion. These requirements have led to a huge market for compliance storage servers, which ensure that data are not shredded or altered before the end of their mandatory retention period. These servers preserve unstructured and semi-structured data at a file-level granularity: email, spreadsheets, reports, instant messages. In this paper, we extend this level of protection to structured data residing in relational databases. We propose a compliant DBMS architecture and two refinements that illustrate the additional security that one can gain with only a slight performance penalty, with almost no modifications to the DBMS kernel. We evaluate our proposed architecture through experiments with TPC-C on a high-performance DBMS, and show that the runtime overhead for transaction processing is approximately 10% in typical configurations.

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“…POSTGRES [24] and Dali [4] were two different approaches of protecting critical DBMS data structures against software errors. The former used hardware protection, while the latter used a wordcode software mechanism and also proposed a recovery algorithm for the corrupted transactions.…”

Section: Related Workmentioning

confidence: 99%

Tamper Detection in Audit Logs

Snodgrass¹,

YAO²,

COLLBERG³

2004

Proceedings 2004 VLDB Conference

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Audit logs are considered good practice for business systems, and are required by federal regulations for secure systems, drug approval data, medical information disclosure, financial records, and electronic voting. Given the central role of audit logs, it is critical that they are correct and inalterable. It is not sufficient to say, "our data is correct, because we store all interactions in a separate audit log." The integrity of the audit log itself must also be guaranteed. This paper proposes mechanisms within a database management system (DBMS), based on cryptographically strong one-way hash functions, that prevent an intruder, including an auditor or an employee or even an unknown bug within the DBMS itself, from silently corrupting the audit log. We propose that the DBMS store additional information in the database to enable a separate audit log validator to examine the database along with this extra information and state conclusively whether the audit log has been compromised. We show with an implementation on a high-performance storage engine that the overhead for auditing is low and that the validator can efficiently and correctly determine if the audit log has been compromised.

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Using codewords to protect database data from a class of software errors

Cited by 6 publications

References 15 publications

Recovery from "bad" user transactions

Recovery from "bad" user transactions

An Architecture for Regulatory Compliant Database Management

Tamper Detection in Audit Logs

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