Security Control Processes Checklist

Published Date: 02 Nov 2017

Solution: - Auditing in data base environment is consists of very large data. Millions of transactions occur in data base and their audit information record has to be audit. For securing audit information there is a need of high care and proper security. Proper authentication and authorization measures should be used for allowing access to audit information, a gaping hole in the security of database suffer from vulnerability. Needs of understanding what authentication types are available and need of choosing strong authentication.DB2 UDB uses the rights of OS for authentication purposes which will provide secure access to audit information by allowing verification of user password. A DOS attack is one of the possible threads that will steal audit information if proper security measure is not followed by targeting account lock out. The SQL injections targets application layer outside of database, by allowing this attack security of database cloud be break and chance to steal audit information can be possible. We need various audit categories to implements in the database according to requirements of database.

After getting auditing information there is a need of some procedure (checklist) that will ensured that the audit information is secured. There is need of security provision for your auditing solution. The security of our solution needs to addresses four places.

The central repository upon it audit information always resides in the form of collected and being used.

The archive files of auditing server

Archive files in transit way

The storage location where the archived files placed.

Items

Security Control Processes Checklist

1.0

Audit Information Data Base have to secured from external access

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Used only by audit system and viewed as a single-user database, can be done by blocking access to database except internal database.

2.0

Archiving of audit trail data in the form of two steps

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An extracted set of files purged from auditing database and placed on local disk, data then encrypted and digitally signed in order to achieved security of information on requested platform.

3.0

Decrypt the information for the auditing system by ensuring digitally signed by auditing system.

4.0

Auditing server is being used for signed and encrypted purpose ,files in transit security

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Implement policy that allows availability of data for a certain period of time, ensuring of archived files at the right location, involves a secure copy.

There is a need for audit information data base only accessible internally in audit system if it is not handled in this way then there is chance of vulnerability and you will need to address the auditing and security issues. If encryption is not being done then there is a chance to lose control of data on other systems. Digital signs allowing you provides prove of accurate data of auditing system, its creation and prove of its environment on which have to be used. The secure copy gets acknowledgment security on the storage place, and backups are used to restore if file becomes lost or deleted.[4]

Question # 26:- Why should we audit the auditing information? Is this process recursive? Why or why not?

Solution:- We audit the auditing information from the purpose of securing and monitoring our working environment. An audit is considered as a reliable source from the point of view of the system protection. By implementing certain techniques of auditing the business get improvement in the form of care and auditing on regularly basis ensures that the money and the time well spent.

The main purpose of audit the auditing information is to improve a company’s profitability and efficiency by helping management to ensure that their risk in their organization is studied well and records in the database are accurate. The audit of auditing information should be a recursive process. The business must needs to ensure that the auditing information is secured. This can be achieved by getting a full audit trail to any access and changes that are made on the audited information.

If you not made full audit trial of any access and changes on the auditing information then you are vulnerable for your information deficiencies because audited information can be changed by user of audit system. So audit of audit information is necessary, if you are constructing own audited solution, make sure that system have a right hooks in order to record all the activities or using a packaged auditing system by involving audit trail.[4]

Question # 27:- Why does auditing information become large? How can this largeness be addressed?

Solution:- Full audit trails creates large amount of data especially in the case of running high through-put database in this context involvement of many store procedure and SQL calls are involved. So audit system has needs to process and store large number of records in the form of providing requested reports and many deliverables. A large number of businesses involved in numerous transactions and respected events needs to be stored in auditing systems e.g. online banking application, large call centers systems, midsize media company. So detailed auditing comes in the form of large amount of data that is kept stored and creates the situation of large auditing information.

The largeness can be addressed by implementing suitable architecture that meets the storing needs among pre computing and aggregation techniques. By implementing suitable architecture the efficiency of storing data is achieved. Data warehouse architecture is suitable for addressing largeness in various cases. The data is efficiently achieved by using data mining tools and reporting.

There are two types of tools that can provide better result for getting auditing information. Tools consist of generic reporting tools (crystal reports, business objects, OLAP solution) that are useable for creating mining environments and reporting efficiently. Another class of tools are auditing-oriented or security oriented. These tools include prepackaged reports that support auditing best practices by allowing you by exception management. In order to resolve the problem of largeness the system should be developed by keeping in view functionality of the architecture and its uses. [4]

Question # 28:- Should an auditing system automatically provide remediation, that is, allow for automatic fixes to problems? Why or why not?

Solution: - Auditing is done to operate system in compact and secure manner. The goal of auditing is not to generate collection of data; in spite of this the main goal is to resolve the problems in an effective and simple way. Therefore, always need arises of architecture solution that can not only provide audit facility but can also presents and provides enforcements of policy that is helpful to resolve problems that are existed during audit activities. So by using this approach auditing system is capable of providing automatic remediation that can allow automatic fixes to problems.

The Database auditing is more effective by being a part of database security solution. So there is always a need of such automatic security that resolves problems of system by implementing such strict policy in the context of database security and auditing. The system is operated in more effective way if data base security and auditing are implemented together.

However database auditing and activity monitoring is one of the greatest challenges for organizations because of the importance of data integrity and privacy purposes. To overcome heterogeneity there is always needs of such architecture that automatically provides remediation by allowing such hybrid architecture the system efficiency can be retrieved and database auditing will be done with unparalleled scalability and minimal overhead by implementing pragmatic solution. The research on this is continued.[4]

Question # 29:- In a paragraph or so, compare and contrast the overall approaches to auditing presented in (a) Ben Natan and (b) the Abrams Essays (specifically Abrams, Essay 25).

Solution:- Ben Natan presented various approaches in order to deal with auditing. Audit work as a function in terms of internal and external environment and plays a central role to provide compliance. For this purpose the availability of data is achieved in an organized and transparent way by implementing authentication and secure password mechanisms e.g. set the listener password, promote and verify the use of strong password, denying a connection instead of account lockout. After availability of data audit can be performed. Audit trails and logs are used to provide compliance of the database environment. Audit trails are used to access for sensitive data i.e. Meta data. The second category deals with security audits (assessments, penetration tests, focus on current database). For the purpose of find mistakes and problems in database vulnerability assessments and penetration testing check the configuration of your data base.

The segregation of duties is followed for the purpose of ensure compliance in more effective way by using multiple layers of audit. Many audit categories existed that you may put in your environment according to your needs i.e. Audit logon/logoff into the database, audit source of database usage such as network node connection with database, audit database usage outside normal operating hours that is related to activities during off-hours. Audit DDL activity, audit database hours, usage of database links and of replication, audit select statement for privacy sets. Besides there are many architectural details that implements pragmatic auditing solutions. [4]

Auditing approaches that followed in essay 25 are discussed below:

Audit trails is used to record every reconstruction (user access, transaction, data result and after transaction what initiation) provides support of query for auditing. For this purpose system is using data activity model that provides access to all reconstruction in database and querying mechanism. It supports two time dimension i.e. if want to do a change in an audit record then changing record value and updated value both kept in the database. For this purpose system needs two different time parameters, the first one defines transaction time o which data is stored on the database and the second parameter is the valid time on which the information in the database is valid for participation in the real world. Bitemporal relation is used to support both transactions with valid times. The database activity model supports bitemporal that keeps history of each modification, update store keeps records of updates made, query-store contains log of all queries. Besides this model supports powerful relational algebra for represents audits and quires related to relations. Model provides restricting access to the database by differentiating users based on their rights. Audit of audit information in a database called zero-information loss. The works on the perfect model is focused that will support automatic regeneration, review of database events regarding security.[5]

Question # 30:- Explain the strengths and weaknesses of the three different approaches to handling multi-tenancy discussed in the slides.

Solution:- The three approaches are discussed below:

Separate Database:-

Strengths:

It involves filtering as a intermediary layer between tenant and data source so it provides trusted database connections.

The data in the database tables remains secure throughout the process.

It provides tenant data encryption so data will be inaccessible for unauthorized parties.

Weakness:

It provides separate database to different clients that are resides on the same system and local network.

Users are separated only by access policies by providing access software.

A flaw in the software can cause compromise of security.

Shared Database Separate Schema:

Strengths:

It provides trusted database connections by allowing only trusted authorized parties.

It support separate schema, so data in the tables managing at different levels by allowing separate tables for against each tenant.

Secure data authorization.

Weakness:

Work load on the system by allowing different users access on the same local network.

Separate schema for different user slow down the network.

Operated under software that provides transparency, problem is software can break security.

Shared Database, Shared Schema:

Strengths:

Provides trusted database connection

In involves tenant view filter that fetches data of request from the shared tables of data.

Tenant data encryption.

Weakness:

Work Load of competitors.

On the same schema, an attack could be made by any subscriber.

Complex requirements of the system i.e. dynamic configuration, large scale computations.

System dependency on networking any issues such as service disruptions can reduce cloud utility.[6][3]

Question # 31:- Data in cloud computing is typical outside the control of the data owner. How does this impact security?

Solution:- In the cloud computer data owner ship is the main issue. In traditional IT environments, data is managed by the user or organization. The data on cloud computer is outside the control of data owner is also a complex issues regarding security. The cloud computer provides transparency to users by providing direct user control. User can do attack on the system because data is not fully controlled by the data owner.

In the context of personal and private information, data owners are responsible for allowing access i.e. what type of information is gathering, allow use of personal information or to stop collection. In terms of data transfer only encryption is not reliable, confidentiality and integrity should be ensured in order to provide security measure to data from the stealing of unauthorized access. For this purpose data owners should allow to perform role in the context of transferring data by allowing integrity and confidentiality.

In the context of storage the effectiveness of encryption can be achieved by the use of symmetric encryption algorithm and key management. The key management should be responsibility of data owner instead of cloud providers. Since security can be breached by the mismanagement of cloud providers. The integrity problem is also the main issue without the involvement of data owner because there is not any way to check integrity of data on the cloud. So data is not ensured where to place on the cloud. There are also many threads on availability of data i.e. external attacks, services of cloud computing. In this way there is essential needs of data owner that will provide CIA accuracy.[2]

Question # 32:- What are the benefits and disadvantages of the techniques used to run queries on encrypted data stored in the cloud?

Solution:-

Benefits:-

The data model and query semantics are supported of time-based and order-based operations i.e. querying 10 next items, or give items in the next 10 minutes.

Quires are eligible to returns new results as new data items are arrived on the cloud.

System is supported for long-running, continuous, and constant conditions.

Query has support of ORDBMS focus.

Disadvantages:-

One problem using data model and query semantics is that exact results are not returned due to incapability to store complete stream.

It involves the use of approximations for giving result of query.

For getting results entire input is seen and then respected result is produced.

Needs to avoid blocking operators that usually suffer from the condition of entire input consumption.

There are storage and performance constraints due to which the query cannot backtrack on the cloud data from where it fetches result for a operation.

It is supported for long running queries but there is need to deal with changes in system conditions i.e. data streaming variable rates or other system changes.

Scalability is also a major focus that needs to be performed in a way allow shared query execution.

In case of static data used by cloud based applications such as PaaS or SaaS model, data encryption in various situations in not suitable. Encryption leads to problem of indexing and querying.[6][2]

Question #33:- Of transactional data and analytical data, which can be moved more securely to cloud settings? Explain.

Solution: - The transactional data application requires a Acid guarantee. Almost transactional data management applications considered not likely to be deployed in the cloud. This is not almost using shared nothing architecture. So it is non-trivial, by using a single site transactions cannot be restricted to accessing data. It is very difficult to establish ACID guarantees over data replication transversely large geographic distances. In this case it is not supported of CAP theorem because only two of them can be achieved. When it is replicated on wide distance area it compromise only consistency and availability. There should be huge risk in storing transactional data on an untrusted host. This type of data contains very sensitive information and privacy violations in this case are typically unacceptable.

In case of analytical data decision support is needed. It involves applications that query a data store for use in business planning, decision support and problem solving. The scale of analytical data is greater than transactional systems. The shared nothing architecture is a good contest for analytical data. ACID guarantee in this case is not needed. In analytical data there is ever increasing amount of data is involved and data analysis workload is the primary goal for the choice of shared nothing architecture. The involvement of infrequent writes in the workloads has terminated the needs of complex locking and commits protocols. It performs sufficient analysis on a recent snap of data. It supports atomicity, consistency and isolation of ACID and easy to get required result. By allowing a reliable analysis sensitive data can often be left out. By using an anonymization function the damaging data should be leave out from the analytical store or including it by supporting encryption.

Thus it is considered that transactional data management applications are not well suited for cloud deployment. In spite of this analytical data is well suited for cloud environment due to above discussed reasons. By keeping in view characteristics of data and workloads for analytical data management is consider well for cloud. It uses a window of data warehouse and through it data proposed to be viewed by public, for this purpose data security is not an issue.[3]

Question # 34:- What issues make object- and object-relational database systems harder to secure than traditional relational database systems?

Solution: - The aim of both database systems is object centric applications, extended query language, reference types. There are some differences that should not be ignored such as OODBMS supports OOPL and ORDBMS is imposed focused on OOPL. The ORDBMS focus on query support where as OODBMS focus upon persistence support. The object-relational database systems are not managed in fully optimized way. Since it encapsulates aspects of object oriented programming, it can be use able by method-centric and data-centric.

There are some issues that are related to security that made object oriented database systems harder to secure. There is relatedness with objects because they are fully depended upon each other. They are always access in synchronization way. It has concurrency mechanisms that need to be modified in such a way that low users must not assume high user appearance by allowing concurrent access. So there is a need of separate way so that high and low user performs there task in separate way without appearing each other existence. The RDBMS should not allow concurrent access, it maintains user access in totally separation way. It is the main reasons regarding the point of view of security.

There are a highly effective needs of garbage collection and needs of proper implementation of their conversions into channels. Because there is not proper management of low objects that objects presented in the system after their usability but remains uncollected.[6]

Question # 35:-    What issues make object- and object-relational database systems easier to secure than traditional relational database systems?

Solution: -Object oriented database system is a techniques being used for persistent data management. For various applications its flexibility, performance and development is better. It has additional schemas that are not part of RDBMS. OO structure features including inherence and polymorphism are part of it. It has adopted the query centric approach of RDBMS. Persistent with the idea of a data language that is declarative. From the architectural point of view implemented as central server program.

The object-relational database systems provide facility of data-centric viewpoint that involves extension of relational data base management system security. There are techniques that make the object-relational database systems easier to secure by applying RDBMS security knowledge to classes, composite classes and inheritance. It also provides support to method centric viewpoint that is actually extension of object security. It provides authorization that is based upon methods. It has summarized all aspects of OOP. So it provides reusability concepts that are not presents in relational database. [6][3]

Data-centric security in Object Oriented Databases:

Since it is dealing with objects so we access to class name in the same way as we access to row is RDBMS. In dealing with classes, the access with class name is basically an access to table as do in RDBMS. Total authorizations given to users in a manner a by allowing access to classes and partial access is by allowing parts of class. In order to deal with inheritance providing access to classes by allowing sub classes, super classes. Read and write access can also be managed. In order to deal with composite classes, access to class involves access to component classes in the sequence.

Method-centric security in object oriented databases:

In OOP the methods are presented in the form of private, public and protected manner. The scope of these methods are depends upon their usage in the certain conditions. Authorizations to methods are given by allowing read up, write down, MAC, trusted methods. In order to blocking illegal flow the flow of information is checked among objects, in violation of security policy the respected information flow will be blocked. Low methods are capable of returning only low data and will not provide access to high data. The authorizations are assigns by specifying conditions. The above mentioned information is highly effective and providing easier approach to manage data then relational database.[6][2]

Question # 36:- What issues make XML database systems (a) harder and (b) easier to secure than traditional relational database systems?

Solution: - The xml data base has verities of data i.e. structured, semi-structured and unstructured data. Xml querying is used as X Path and X query whereas RDMBS used SQL quires. There are various similarities and differences to OODBMS, ORDBMS and RDBMS in the context of securing XML databases. XML deals verities of data. In structured data DBMS schema strictly ensures certain constraints to manage data. The another approach is semi- structured data, it entails Ad hoc data that is collected before storage but it is not identical structure so in this context management of storage becomes an issue. It contains self-defining data that is followed by blended schema. Another variety is unstructured data that allow limited data type i.e. embedded with text information.

Semi-Structured Data:-

The data in this context is represents as directed graph, schema name are represented by directed edges on tags, entity types, object types, names of attributes. In this context internal nodes are used to presents individual objects. Actual data are represented by Leaf nodes.

Semi. Structure Data and XML:-

They are normaly treated as missing or additional attributes, heterogeneous collection. The data has not priori structure, irregular data. In XML the elements becomes part of the data because XML supports self describing data. The main advantage of XML is it flexibility because data tags can be self generated. XML is more complex structure of data as compared with traditional RDBMS.

XQuery is cover which depends upon XML-QL. By using xpath expression the queries are represented on more XML documents. FLWR expressions are used by XQuery form. The security issues of XML database are relevant to relational database systems. Some complications are due to structure of XML documents because an XML document supports graphical structure. To provides support to graphical structure ides are taken from object and ORDBMS. There are security needs that are to be fulfilled regarding XML documents should be addressed at rest and in transit encryption should play a vital role. For easily querying point of view encryption needs should be not essential but if you not involve encryption then chance insecurity will occur. [6][2][3]