Finding Sensitive Data in and Around Microsoft SQL Server
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SQL Server Protection Whitepaper
SQL Server Protection Whitepaper Contents 1. Introduction ..................................................................................................................................... 2 Documentation .................................................................................................................................................................. 2 Licensing ............................................................................................................................................................................... 2 The benefits of using the SQL Server Add-on ....................................................................................................... 2 Requirements ...................................................................................................................................................................... 2 2. SQL Protection overview ................................................................................................................ 3 User databases ................................................................................................................................................................... 3 System databases .............................................................................................................................................................. 4 Transaction logs ................................................................................................................................................................ -
Damage Management in Database Management Systems
The Pennsylvania State University The Graduate School Department of Information Sciences and Technology Damage Management in Database Management Systems A Dissertation in Information Sciences and Technology by Kun Bai °c 2010 Kun Bai Submitted in Partial Ful¯llment of the Requirements for the Degree of Doctor of Philosophy May 2010 The dissertation of Kun Bai was reviewed and approved1 by the following: Peng Liu Associate Professor of Information Sciences and Technology Dissertation Adviser Chair of Committee Chao-Hsien Chu Professor of Information Sciences and Technology Thomas La Porta Distinguished Professor of Computer Science and Engineering Sencun Zhu Assistant Professor of Computer Science and Engineering Frederico Fonseca Associate Professor of Information Sciences and Technology Associate Dean, College of Information Sciences and Technology 1Signatures on ¯le in the Graduate School. iii Abstract In the past two decades there have been many advances in the ¯eld of computer security. However, since vulnerabilities cannot be completely removed from a system, successful attacks often occur and cause damage to the system. Despite numerous tech- nological advances in both security software and hardware, there are many challenging problems that still limit e®ectiveness and practicality of existing security measures. As Web applications gain popularity in today's world, surviving Database Man- agement System (DBMS) from an attack is becoming even more crucial than before because of the increasingly critical role that DBMS is playing in business/life/mission- critical applications. Although signi¯cant progress has been achieved to protect the DBMS, such as the existing database security techniques (e.g., access control, integrity constraint and failure recovery, etc.,), the buniness/life/mission-critical applications still can be hit due to some new threats towards the back-end DBMS. -
ACID, Transactions
ECE 650 Systems Programming & Engineering Spring 2018 Database Transaction Processing Tyler Bletsch Duke University Slides are adapted from Brian Rogers (Duke) Transaction Processing Systems • Systems with large DB’s; many concurrent users – As a result, many concurrent database transactions – E.g. Reservation systems, banking, credit card processing, stock markets, supermarket checkout • Need high availability and fast response time • Concepts – Concurrency control and recovery – Transactions and transaction processing – ACID properties (desirable for transactions) – Schedules of transactions and recoverability – Serializability – Transactions in SQL 2 Single-User vs. Multi-User • DBMS can be single-user or multi-user – How many users can use the system concurrently? – Most DBMSs are multi-user (e.g. airline reservation system) • Recall our concurrency lectures (similar issues here) – Multiprogramming – Interleaved execution of multiple processes – Parallel processing (if multiple processor cores or HW threads) A A B B C CPU1 D CPU2 t1 t2 t3 t4 time Interleaved concurrency is model we will assume 3 Transactions • Transaction is logical unit of database processing – Contains ≥ 1 access operation – Operations: insertion, deletion, modification, retrieval • E.g. things that happen as part of the queries we’ve learned • Specifying database operations of a transaction: – Can be embedded in an application program – Can be specified interactively via a query language like SQL – May mark transaction boundaries by enclosing operations with: • “begin transaction” and “end transaction” • Read-only transaction: – No database update operations; only retrieval operations 4 Database Model for Transactions • Database represented as collection of named data items – Size of data item is its “granularity” – E.g. May be field of a record (row) in a database – E.g. -
How to Conduct Transaction Log Analysis for Web Searching And
Search Log Analysis: What is it; what’s been done; how to do it Bernard J. Jansen School of Information Sciences and Technology The Pennsylvania State University 329F IST Building University Park, Pennsylvania 16802 Email: [email protected] Abstract The use of data stored in transaction logs of Web search engines, Intranets, and Web sites can provide valuable insight into understanding the information-searching process of online searchers. This understanding can enlighten information system design, interface development, and devising the information architecture for content collections. This article presents a review and foundation for conducting Web search transaction log analysis. A methodology is outlined consisting of three stages, which are collection, preparation, and analysis. The three stages of the methodology are presented in detail with discussions of goals, metrics, and processes at each stage. Critical terms in transaction log analysis for Web searching are defined. The strengths and limitations of transaction log analysis as a research method are presented. An application to log client-side interactions that supplements transaction logs is reported on, and the application is made available for use by the research community. Suggestions are provided on ways to leverage the strengths of, while addressing the limitations of, transaction log analysis for Web searching research. Finally, a complete flat text transaction log from a commercial search engine is available as supplementary material with this manuscript. Introduction Researchers have used transaction logs for analyzing a variety of Web systems (Croft, Cook, & Wilder, 1995; Jansen, Spink, & Saracevic, 2000; Jones, Cunningham, & McNab, 1998; Wang, 1 of 42 Berry, & Yang, 2003). Web search engine companies use transaction logs (also referred to as search logs) to research searching trends and effects of system improvements (c.f., Google at http://www.google.com/press/zeitgeist.html or Yahoo! at http://buzz.yahoo.com/buzz_log/?fr=fp- buzz-morebuzz). -
Cohesity Dataplatform Protecting Individual MS SQL Databases Solution Guide
Cohesity DataPlatform Protecting Individual MS SQL Databases Solution Guide Abstract This solution guide outlines the workflow for creating backups with Microsoft SQL Server databases and Cohesity Data Platform. Table of Contents About this Guide..................................................................................................................................................................2 Intended Audience..............................................................................................................................................2 Configuration Overview.....................................................................................................................................................2 Feature Overview.................................................................................................................................................................2 Installing Cohesity Windows Agent..............................................................................................................................2 Downloading Cohesity Agent.........................................................................................................................2 Select Coheisty Windows Agent Type.........................................................................................................3 Install the Cohesity Agent.................................................................................................................................3 Cohesity Agent Setup........................................................................................................................................4 -
Django-Transaction-Hooks Documentation Release 0.2.1.Dev1
django-transaction-hooks Documentation Release 0.2.1.dev1 Carl Meyer December 12, 2016 Contents 1 Prerequisites 3 2 Installation 5 3 Setup 7 3.1 Using the mixin.............................................7 4 Usage 9 4.1 Notes...................................................9 5 Contributing 13 i ii django-transaction-hooks Documentation, Release 0.2.1.dev1 A better alternative to the transaction signals Django will never have. Sometimes you need to fire off an action related to the current database transaction, but only if the transaction success- fully commits. Examples: a Celery task, an email notification, or a cache invalidation. Doing this correctly while accounting for savepoints that might be individually rolled back, closed/dropped connec- tions, and idiosyncrasies of various databases, is non-trivial. Transaction signals just make it easier to do it wrong. django-transaction-hooks does the heavy lifting so you don’t have to. Contents 1 django-transaction-hooks Documentation, Release 0.2.1.dev1 2 Contents CHAPTER 1 Prerequisites django-transaction-hooks supports Django 1.6.x through 1.8.x on Python 2.6, 2.7, 3.2, 3.3 and 3.4. django-transaction-hooks has been merged into Django 1.9 and is now a built-in feature, so this third-party library should not be used with Django 1.9+. SQLite3, PostgreSQL (+ PostGIS), and MySQL are currently the only databases with built-in support; you can exper- iment with whether it works for your favorite database backend with just a few lines of code. 3 django-transaction-hooks Documentation, Release 0.2.1.dev1 4 Chapter 1. -
Transactions.Pdf
BIT 4514: Database Technology for Business Fall 2019 Database transactions 1 1 Database transactions • A database transaction is any (possibly multi-step) action that reads from and/or writes to a database – It may consist of a single SQL statement or a collection of related SQL statements ex: Adding a new lunch to the class database – requires two related INSERT statements 2 2 Transactions (cont.) • A successful transaction is one in which all of the SQL statements are completed successfully – A consistent database state is one in which all data integrity constraints are satisfied – A successful transaction changes the database from one consistent state to another 3 3 1 Transaction management • Improper or incomplete transactions can have a devastating effect on database integrity Ex: INSERT only items into the Lunch_item table • If a DBMS supports transaction management, it will roll back an inconsistent database (i.e., the result of an unsuccessful transaction) to a previous consistent state. 4 4 Properties of a transaction • Atomicity • Consistency • Isolation • Durability • Every transaction MUST exhibit these four properties 5 5 Properties of a transaction • Atomicity – The "all or nothing" property – All transaction operations must be completed i.e. a transaction is treated as a single, indivisible, logical unit of work • Consistency – When a transaction is completed, the database must be in a consistent state 6 6 2 Properties of a transaction • Isolation – Data used during the execution of a transaction cannot be used by a second -
Database Systems 09 Transaction Processing
1 SCIENCE PASSION TECHNOLOGY Database Systems 09 Transaction Processing Matthias Boehm Graz University of Technology, Austria Computer Science and Biomedical Engineering Institute of Interactive Systems and Data Science BMVIT endowed chair for Data Management Last update: May 13, 2019 2 Announcements/Org . #1 Video Recording . Since lecture 03, video/audio recording . Link in TeachCenter & TUbe . #2 Exercises . Exercise 1 graded, feedback in TC in next days 77.4% . Exercise 2 still open until May 14 11.50pm (incl. 7 late days, no submission is a mistake) 53.7% . Exercise 3 published and introduced today . #3 CS Talks x4 (Jun 17 2019, 5pm, Aula Alte Technik) . Claudia Wagner (University Koblenz‐Landau, Leibnitz Institute for the Social Sciences) . Title: Minorities in Social and Information Networks . Dinner opportunity for interested female students! INF.01014UF Databases / 706.004 Databases 1 – 09 Transaction Processing Matthias Boehm, Graz University of Technology, SS 2019 3 Announcements/Org, cont. #4 Infineon Summer School 2019 Sensor Systems . Where: Infineon Technologies Austria, Villach Carinthia, Austria . Who: BSc, MSc, PhD students from different fields including business informatics, computer science, and electrical engineering . When: Aug 26 through 30, 2019 . Application deadline: Jun 16, 2019 . #5 Poll: Date of Final Exam . We’ll move Exercise 4 to Jun 25 . Current date: Jun 24, 6pm . Alternatives: Jun 27, 4pm / 7.30pm, or week starting Jul 8 (Erasmus?) INF.01014UF Databases / 706.004 Databases 1 – 09 Transaction Processing Matthias Boehm, Graz University of Technology, SS 2019 4 Transaction (TX) Processing User 2 User 1 User 3 read/write TXs #1 Multiple users Correctness? DBS DBMS #2 Various failures Deadlocks (TX, system, media) Constraint Reliability? violations DBs Network Crash/power failure Disk failure failure . -
Destiny® System Backups
Destiny® system backups Establishing a backup and restore plan for Destiny Overview It is important to establish a backup and restore plan for your Destiny installation. The plan must be validated and monitored to ensure that your data is sufficiently backed up and can be recovered in the event of hardware failure or other disaster. IMPORTANT Follett recommends deploying a comprehensive backup solution and testing and monitoring all backup processes. There are tradeoff decisions to be made in the backup strategy that will be shaped by your organization’s risk tolerance, technology constraints, and ability to absorb data loss or downtime. This document provides an overview of standard backup and restore for the Destiny system. IMPORTANT This content does not cover high-availability configurations such as clustered servers or log shipping. Please contact Follett School Solutions, Inc. Technical Support should you have any questions about backing up your Destiny installation. For details, see Destiny® system backups. Backing up Destiny: an overview SQL database The heart of the Destiny data resides in the SQL database. These are the main components of SQL data to be backed up: The Destiny SQL database. This database contains the main Destiny data. Proper SQL backup configuration of this database is essential. NOTE If your installation is a consortium, you will have to ensure a proper backup of multiple SQL databases (one per member). The Destiny SQL transaction log. The Master SQL database. This system database is useful when restoring to a replacement server. It is not necessary to back up the tempdb database. This is a SQL Server work area and is recreated automatically. -
Infosphere MDM Collaboration Server: Installation Guide
IBM InfoSphere Master Data Management Collaboration Server Version 11.6 Fix Pack 15 Installation Guide IBM Note Before using this information and the product that it supports, read the information in “Notices” on page 159. Edition Notice This edition applies to version 11.6 of IBM® InfoSphere® Master Data Management and to all subsequent releases and modifications until otherwise indicated in new editions. © Copyright International Business Machines Corporation 2000, 2020. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Chapter 1. Planning to install.................................................................................1 Installation scenarios.................................................................................................................................. 1 Installation and configuration worksheets................................................................................................. 3 Installation directory worksheet............................................................................................................3 IBM Db2 data source worksheet............................................................................................................4 Oracle data source worksheet............................................................................................................... 5 WebSphere Application Server installation worksheet.........................................................................6 -
Database Management Systems Introduction Transaction ACID
Introduction What is Concurrent Process (CP)? • Multiple users access databases and use computer Database Management systems simultaneously. • Example: Airline reservation system. Systems œ An airline reservation system is used by hundreds of travel agents and reservation clerks concurrently. Transaction, Concurrency and Why Concurrent Process? Recovery • Better transaction throughput and response time • Better utilization of resource Adapted from Lecture notes by Goldberg @ Berkeley Transaction ACID Properties of transaction • What is Transaction? • Atomicity: Transaction is either performed in its entirety or not performed at all, this should be DBMS‘ • A sequence of many actions which are responsibility considered to be one atomic unit of work. • Consistency: Transaction must take the database • Basic operations a transaction can include from one consistent state to another if it is executed in —actions“: isolation. It is user‘s responsibility to insure consistency œ Reads, writes • Isolation: Transaction should appear as though it is œ Special actions: commit, abort being executed in isolation from other transactions • Durability: Changes applied to the database by a committed transaction must persist, even if the system fail before all changes reflected on disk Concurrent Transactions Schedules • What is Schedules œ A schedule S of n transactions T1,T2,…Tn is an ordering of the B B operations of the transactions subject to the constraint that, for each transaction Ti that participates in S, the operations of Ti in Smust CPU2 A appear in the same order in which they occur in Ti. CPU A 1 œ Example: Sa: r1(A),r2(A),w1(A),w2(A), a1,c2; CPU1 T1 T2 time Read(A) Read(A) t1 t2 t1 t2 Write(A) interleaved processing parallel processing Write(A) Abort T1 Commit T2 1 Oops, something‘s wrong Another example • Reserving a seat for a flight • Problems can occur when concurrent transactions execute in an uncontrolled manner. -
Data Definition Language (Ddl)
DATA DEFINITION LANGUAGE (DDL) CREATE CREATE SCHEMA AUTHORISATION Authentication: process the DBMS uses to verify that only registered users access the database - If using an enterprise RDBMS, you must be authenticated by the RDBMS - To be authenticated, you must log on to the RDBMS using an ID and password created by the database administrator - Every user ID is associated with a database schema Schema: a logical group of database objects that are related to each other - A schema belongs to a single user or application - A single database can hold multiple schemas that belong to different users or applications - Enforce a level of security by allowing each user to only see the tables that belong to them Syntax: CREATE SCHEMA AUTHORIZATION {creator}; - Command must be issued by the user who owns the schema o Eg. If you log on as JONES, you can only use CREATE SCHEMA AUTHORIZATION JONES; CREATE TABLE Syntax: CREATE TABLE table_name ( column1 data type [constraint], column2 data type [constraint], PRIMARY KEY(column1, column2), FOREIGN KEY(column2) REFERENCES table_name2; ); CREATE TABLE AS You can create a new table based on selected columns and rows of an existing table. The new table will copy the attribute names, data characteristics and rows of the original table. Example of creating a new table from components of another table: CREATE TABLE project AS SELECT emp_proj_code AS proj_code emp_proj_name AS proj_name emp_proj_desc AS proj_description emp_proj_date AS proj_start_date emp_proj_man AS proj_manager FROM employee; 3 CONSTRAINTS There are 2 types of constraints: - Column constraint – created with the column definition o Applies to a single column o Syntactically clearer and more meaningful o Can be expressed as a table constraint - Table constraint – created when you use the CONTRAINT keyword o Can apply to multiple columns in a table o Can be given a meaningful name and therefore modified by referencing its name o Cannot be expressed as a column constraint NOT NULL This constraint can only be a column constraint and cannot be named.