A Review of Security Mechanisms for Detection of Malicious Transactions in Database

Insider attacks formed the biggest threaten against database management systems. There are many mechanisms have been developed to detect and prevent the insider attacks called Detection of Malicious Activities in Database Systems DEMIDS. The DEMIDS consider as one of the last defenses mechanism of the database security system. There are many mechanisms that have been developed to detect and prevent the misuse activities like delete, and update data on the database systems. These mechanisms utilize auditing and profiling methods to detect and prevent the malicious activities. However these mechanisms still have problems to detect the misuse activities such as limit to detect the malicious data on authorized commands. This study will address these problems by propose a mechanism that utilizes dependency relationship among items to detect and prevent the malicious data by calculate a number of relations among data items. If the number of relations among items is not allowed any modification or deletion then the mechanism will detect activity as malicious activity. The evaluation parameters such as detect, false positive and false negative rate use to evaluate the accuracy of proposed mechanism

DBKnot: A Transparent and Seamless, Pluggable Tamper Evident Database

Database integrity is crucial to organizations that rely on databases of important data. They suffer from the vulnerability to internal fraud. Database tampering by internal malicious employees with high technical authorization to their infrastructure or even compromised by externals is one of the important attack vectors. This thesis addresses such challenge in a class of problems where data is appended only and is immutable. Examples of operations where data does not change is a) financial institutions (banks, accounting systems, stock market, etc., b) registries and notary systems where important data is kept but is never subject to change, and c) system logs that must be kept intact for performance and forensic inspection if needed. The target of the approach is implementation seamlessness with little-or-no changes required in existing systems. Transaction tracking for tamper detection is done by utilizing a common hashtable that serially and cumulatively hashes transactions together while using an external time-stamper and signer to sign such linkages together. This allows transactions to be tracked without any of the organizations’ data leaving their premises and going to any third-party which also reduces the performance impact of tracking. This is done so by adding a tracking layer and embedding it inside the data workflow while keeping it as un-invasive as possible. DBKnot implements such features a) natively into databases, or b) embedded inside Object Relational Mapping (ORM) frameworks, and finally c) outlines a direction of implementing it as a stand-alone microservice reverse-proxy. A prototype ORM and database layer has been developed and tested for seamlessness of integration and ease of use. Additionally, different models of optimization by implementing pipelining parallelism in the hashing/signing process have been tested in order to check their impact on performance. Stock-market information was used for experimentation with DBKnot and the initial results gave a slightly less than 100% increase in transaction time by using the most basic, sequential, and synchronous version of DBKnot. Signing and hashing overhead does not show significant increase per record with the increased amount of data. A number of different alternate optimizations were done to the design that via testing have resulted in significant increase in performance

Auditing database systems through forensic analysis

The majority of sensitive and personal data is stored in a number of different Database Management Systems (DBMS). For example, Oracle is frequently used to store corporate data, MySQL serves as the back-end storage for many webstores, and SQLite stores personal data such as SMS messages or browser bookmarks. Consequently, the pervasive use of DBMSes has led to an increase in the rate at which they are exploited in cybercrimes. After a cybercrime occurs, investigators need forensic tools and methods to recreate a timeline of events and determine the extent of the security breach. When a breach involves a compromised system, these tools must make few assumptions about the system (e.g., corrupt storage, poorly configured logging, data tampering). Since DBMSes manage storage independent of the operating system, they require their own set of forensic tools. This dissertation presents 1) our database-agnostic forensic methods to examine DBMS contents from any evidence source (e.g., disk images or RAM snapshots) without using a live system and 2) applications of our forensic analysis methods to secure data. The foundation of this analysis is page carving, our novel database forensic method that we implemented as the tool DBCarver. We demonstrate that DBCarver is capable of reconstructing DBMS contents, including metadata and deleted data, from various types of digital evidence. Since DBMS storage is managed independently of the operating system, DBCarver can be used for new methods to securely delete data (i.e., data sanitization). In the event of suspected log tampering or direct modification to DBMS storage, DBCarver can be used to verify log integrity and discover storage inconsistencies

Database forensic investigation process models: a review

Database Forensic Investigation (DBFI) involves the identification, collection, preservation, reconstruction, analysis, and reporting of database incidents. However, it is a heterogeneous, complex, and ambiguous field due to the variety and multidimensional nature of database systems. A small number of DBFI process models have been proposed to solve specific database scenarios using different investigation processes, concepts, activities, and tasks as surveyed in this paper. Specifically, we reviewed 40 proposed DBFI process models for RDBMS in the literature to offer up- to-date and comprehensive background knowledge on existing DBFI process model research, their associated challenges, issues for newcomers, and potential solutions for addressing such issues. This paper highlights three common limitations of the DBFI domain, which are: 1) redundant and irrelevant investigation processes; 2) redundant and irrelevant investigation concepts and terminologies; and 3) a lack of unified models to manage, share, and reuse DBFI knowledge. Also, this paper suggests three solutions for the discovered limitations, which are: 1) propose generic DBFI process/model for the DBFI field; 2) develop a semantic metamodeling language to structure, manage, organize, share, and reuse DBFI knowledge; and 3) develop a repository to store and retrieve DBFI field knowledge

SQL Injection - Threats to Medical Systems: The Issues and Countermeasures

A vast majority of medical information systems use Standard Query Language databases (SQL) as the underlying technology to deliver medical records in a timely and efficient manner. SQL is a standardised and well entrenched database technology, which allows for the development of robust, customised applications for information management. In recent years, SQL has been used as the back-end to many successful web client accessible applications. The use of SQL in this manner has been greatly enhanced through the development of server side scripting languages such as Microsoft ASP and open source systems such as PHP. These allow for the representation and extraction of data from a database and have a range of manipulation and display possibilities allowing a developer a rich tapestry of options. However, these scripting languages have enabled the ability for malicious users to directly modify, manipulate or destroy SQL databases. In addition to those server side scripting language problems there is also malicious software in the form of worms specifically targeting SQL databases