This paper describes security issues for data warehousing and data mining. It first provides an overview of data warehousing and security issues for data warehouses. Then a discussion of data mining , security implications of data mining, as well as data mining as a tool to handle security problems are given.

Database Security

Using traditional and emerging access control approaches to develop secure applications for the Web.

Security models for web-based applications

We consider recovery from malicious but committed transactions. Traditional recovery mechanisms do not address this problem, except for complete rollbacks, which undo the work of good transactions as well as malicious ones, and compensating transactions, whose utility depends on application semantics. We develop an algorithm that rewrites execution histories for the purpose of backing out malicious transactions. Good transactions that are affected, directly or indirectly, by malicious transactions complicate the process of backing out undesirable transactions. We show that the prefix of a rewritten history produced by the algorithm serializes exactly the set of unaffected good transactions. The suffix of the rewritten history includes special state information to describe affected good transactions as well as malicious transactions. We describe techniques that can extract additional good transactions from this latter part of a rewritten history. The latter processing saves more good transactions than is possible with a dependency-graph based approach to recovery.

Rewriting Histories: Recovering from Malicious Transactions

Numerous sensitive databases are breached every year due to bugs in applications. These applications typically handle data for many users, and consequently, they have access to large amounts of confidential information.This paper describes IFDB, a DBMS that secures databases by using decentralized information flow control (DIFC). We present the Query by Label model, which introduces new abstractions for managing information flows in a relational database. IFDB also addresses several challenges inherent in bringing DIFC to databases, including how to handle transactions and integrity constraints without introducing covert channels.We implemented IFDB by modifying PostgreSQL, and extended two application environments, PHP and Python, to provide a DIFC platform. IFDB caught several security bugs and prevented information leaks in two web applications we ported to the platform. Our evaluation shows that IFDB's throughput is as good as PostgreSQL for a real web application, and about 1% lower for a database benchmark based on TPC-C.

/pdf/ifdb-decentralized-information-flow-control-for-databases-57zd9autdl.pdf

IFDB: decentralized information flow control for databases

https://liacs.leidenuniv.nl/~stefanovtp/courses/StudentenSeminarium/Papers/DB/Database%20Security.pdf

Database security: research and practice

Consideration is given to the application of multiversion schedulers in multilevel secure database management systems (MLS/DBMSs). Transactions are vital for MLS/DBMSs because they provide transparency to concurrency and failure. Concurrent execution of transactions may lead to contention among subjects for access to data, which in MLS/DBMSs may lead to security problems. Multiversion schedulers reduce the contention for access to data by maintaining multiple versions. A description is given of the relation between schedules produced in MLS/DBMSs and those which are multiversion serializable. The authors also propose a secure multiversion scheduler. They show that the scheduling protocol gives correct schedules and is free of covert channels due to contention for access to data, i.e. the scheduler is data-conflict-secure. >

W.T. Tsai

Papers

Multiversion concurrency control for multilevel secure database systems