ORACLE DATABASE SECURITY

This paper presents some security issues, namely security database system level, data level security, user-level security, user management, resource management and password management. Security is a constant concern in the design and database development. Usually, there are no concerns about the existence of security, but rather how large it should be. A typically DBMS has several levels of security, in addition to those offered by the operating system or network. Typically, a DBMS has user accounts that require a login password to be authenticated to access the data.data security, password administration, Oracle HTTP Server, OracleAS, access control

Austrian Social Security Database

The Austrian Social Security Database (ASSD) is a matched firm-worker data set, which records the labor market history of almost 11 million individuals from January 1972 to April 2007. Moreover, more than 2.2 million firms can be identified. The individual labor market histories are described in the follow- ing dimensions: very detailed daily labor market states and yearly earnings at the firm-worker level, together with a limited set of demographic characteris- tics. Additionally the ASSD provides some firm related information, such as geographical location and industry affiliation. This paper is a short description of this huge data base and intended for people using this data in their own empirical work.

Strong and Provably Secure Database Access Control

Existing SQL access control mechanisms are extremely limited. Attackers can leak information and escalate their privileges using advanced database features such as views, triggers, and integrity constraints. This is not merely a problem of vendors lagging behind the state-of-the-art. The theoretical foundations for database security lack adequate security definitions and a realistic attacker model, both of which are needed to evaluate the security of modern databases. We address these issues and present a provably secure access control mechanism that prevents attacks that defeat popular SQL database systems.Comment: A short version of this paper has been published in the proceedings of the 1st IEEE European Symposium on Security and Privacy (EuroS&P 2016

Statistical and fuzzy approach for database security

A new type of database anomaly is described by addressing the concept of Cumulated Anomaly in this paper. Dubiety-Determining Model (DDM), which is a detection model basing on statistical and fuzzy set theories for Cumulated Anomaly, is proposed. DDM can measure the dubiety degree of each database transaction quantitatively. Software system architecture to support the DDM for monitoring database transactions is designed. We also implemented the system and tested it. Our experimental results show that the DDM method is feasible and effective

DATABASE SECURITY

Ensuring the security of databases is a complex issue. The more complex the databases are the more complex the security measures that are to be applied are. Network and Internet connections to databases may complicate things even further. Also, each and every additional internal user that would be added can create further serious security problems. The purpose of this paper is to highlight and identify the main methods and facets of attack on a database, as well as ways to deflect attacks, through focusing on the delicate issue of data inference.This paper will examine the different topics related to database security and see the adaption of the research to the changing environment

Quantum Private Queries: security analysis

We present a security analysis of the recently introduced Quantum Private Query (QPQ) protocol. It is a cheat sensitive quantum protocol to perform a private search on a classical database. It allows a user to retrieve an item from the database without revealing which item was retrieved, and at the same time it ensures data privacy of the database (the information that the user can retrieve in a query is bounded and does not depend on the size of the database). The security analysis is based on information-disturbance tradeoffs which show that whenever the provider tries to obtain information on the query, the query (encoded into a quantum system) is disturbed so that the person querying the database can detect the privacy violation.Comment: 12 pages, 1 figur