Chapter No 4 Query optimization and Data Integrity & Security

What is a query optimizer? Query optimization is of great importance for the performance of a relational database, especially for the execution of complex SQL statements. A query optimizer determines the best strategy for performing each query.

Concurrent user access to the same data is one of the most central and vexing issues for applications utilizing databases. Concurrency can affect two of the most important facets of any application: the underlying integrity of the data and the performance of the application system.

The query optimizer chooses, for example, whether or not to use indexes for a given query, and which join techniques to use when joining multiple tables. These decisions have a tremendous effect on SQL performance, and query optimization is a key technology for every application, from operational systems to data warehouse and analysis systems to content- management systems.

Introduction to Data Integrity Oracle uses integrity constraints to prevent invalid data entry into the base tables of the database. You can define integrity constraints to enforce the business rules you want to associate with the information in a database.

Examples of Data Integrity

Types of Integrity Constraints NOT NULL Integrity Constraints A NOT NULL constraint requires a column of a table contain no null values. UNIQUE Key Integrity Constraints A UNIQUE key integrity constraint requires that every value in a column or set of columns (key) be unique — that is, no two rows of a table have duplicate values in a specified column or set of columns.

PRIMARY KEY Integrity ConstraintsPRIMARY KEY Integrity Constraints: It consists of one or more columns to keep the records unique in the table. It should not be empty. It helps to find a record uniquely in the table. Referential Integrity Constraints Different tables in a relational database can be related by common columns, and this rule governs the relationship of the columns must be maintained.

CHECK Integrity Constraints A CHECK integrity constraint on a column or set of columns requires that a specified condition be. Database security is the system, processes, and procedures that protect a database from unintended activity. Unintended activity can be categorized as authenticated misuse, malicious attacks or unintentional mistakes made by authorized individuals or processes.database

Database Recovery: A database recovery log keeps a record of all changes made to a database, including the addition of new tables or updates to existing ones. This log is made up of a number of log extents, each contained in a separate file called a log file.

Data Security Two Basic Categories of Computer Security:- Physical Security:- It is concerned with physical protecting the computer resources. – Physical Security Control: Data Backup. Hardware Backup. Planning and testing.

Data Security …Cont Logical Security:- It is concerned in controlling access to information. – Logical Security Control:- Unauthorized disclosure. (viewing DB). Unauthorized modification. Unauthorized withholding.

Database and Application Security, Nov Database/Application Security Ensure that only authenticated users can access the system And can access (read/update) only data/interfaces that they are authorized to access

14 Limitations of SQL Authorization SQL does not support authorization at a tuple level – E.g. we cannot restrict students to see only (the tuples storing) their own grades Web applications are dominant users of databases – Application end users don't have database user ids, they are all mapped to the same database user id – Database access control provides only a very coarse application-level access control

Access Control in Application Layer Applications authenticate end users and decide what interfaces to give to whom – Screen level authorization: which users are allowed to access which screens – Parameter checking: users only authorized to execute forms with certain parameter values E.g. CSE faculty can see only CSE grades

Privacy Aggregate information about private information can be very valuable – E.g. identification of epidemics, mining for patterns (e.g. disease causes) etc. Privacy preserving data release – E.g. in US, many organizations released “anonymized” medical data, with names removed, but zipcode (= pincode), sex and date of birth retained Turns out above (zipcode,sex,date of birth) uniquely identify most people! – Correlate anonymized data with (say) electoral data with same information

– Recent problems at America Online Released search history, apparently anonymized, but users could be easily identified in several cases – Several top officials were fired – Earlier problems revealed medical history of Massachusetts state governer. Not yet a criminal issue, but lawsuits have happened Conflict with Right To Information Act – Many issues still to be resolved

References: Database and Application Security By S. Sudarshan Computer Science and Engg. Dept I.I.T. Bombay