Data Security

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SECURITY
Definition
Security is “The quality or state of being secure to be free from danger.” In other words,
protection against adversaries—from those who would do harm, intentionally or
otherwise—is the objective. National security, for example, is a multilayered system that
protects the sovereignty of a state, its assets, its resources, and its people. Achieving the
appropriate level of security for an organization also requires a multifaceted system.
A successful organization has multiple layers of security in place to protect its
operations:-
 Physical security, to protect physical items, objects, or areas from unauthorized
access and misuse
 Personnel security, to protect the individual or group of individuals who are
authorized to access the organization and its operations
 Operations security, toprotect the details of a particular operation or series of
activities
 Communications security, to protect communications media, technology, and
content
 Network security, to protect networking components, connections, and contents
 Information security, to protect the confidentiality, integrity and availability of
information assets, whether in storage, processing, or transmission. It is achieved
via the application of policy, education, training and awareness, and technology.
Eg.

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In a time when mobility is the present and future of IT, allowing employees to access a
network from a remote location, like their home or a project site, can increase the value
of the network and efficiency of the employee. Unfortunately, remote access to a
network also opens a number of vulnerabilities and creates difficult security challenges
for a network administrator.
As companies make an effort to adapt to new and mobile IT world, fundamental
business operations increasingly rely on the Internet, leaving them exposed to the
growing threats. Today we all need to know continually address spam and viruses,
which plague email worldwide, and spyware that attaches itself to user PC's even
through innocent Web surfing.

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Personal Data
Personal data are defined in the Data Protection Act, as follows: -
"data which relate to a living individual who can be identified: -
* from those data; or
* from those data and other information which is in the possession of, or is likely to
come into the possession of, the data controller and includes any expression of opinion
about the individual and any indication of the intentions of the data controller or any
other person in respect of the individual".
The DPA applies to all personal data relating to living individuals, including names,
addresses, etc. The DPA also distinguishes between "ordinary" personal data and
sensitive personal data, imposing more stringent conditions for processing the latter.
Sensitive personal data consists of information as to:
 racial or ethnic origin;
 political opinions;
 religious beliefs or other beliefs of a similar nature;
 membership of a trade union;
 physical or mental health;
 the commission, or alleged commission of, any offence; and
 any proceedings for any offence committed or alleged to have been committed
and the outcome of such proceedings.
Sensitive personal data does not include financial records or other information that
individuals may regard as private or confidential.
The DPA applies to data held on computers and to manual data, such as paper files,
which is structured either by reference toindividuals or to criteria relating to individuals
where that personal data is readily accessible. Where personal data in manual folders or
documents is not readily accessible (for example, a box of documents that are in no
particular order), the DPA may not apply, meaning that the data subject is not entitled
to inspect their personal data further to a subject access request. These are discussed
further below.

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Data Security
Definition
Data security is the process of protecting information systems and its data from
unauthorized accidental or intentional modification, destruction or disclosure. The
protection includes the confidentiality, integrity and availability of these systems and
data.
Risk assessment, mitigation and measurement are key components of data security. To
maintain a secure environment, data security protocols require that any changes to data
systems have an audit trail, which identifies the individual, department, time and date
of any system change. Companies utilize personnel, policies, protocols, standards,
procedures, software, hardware and physical security measures to attain data security.
Data security may include one or a combination of all of these.
Data security is not confined to the Information Services or Information Technology
departments, but will involve various stakeholders including senior management, the
board of directors, regulators, internal and external auditors, partners, suppliers and
shareholders.
Data security encompasses the security of the Information System in its entirety.
The U.S. National Information Systems Security Glossary defines Information Systems
Security (INFOSEC) as: “The protection of information systems against unauthorized
access to or modification of information, whether in storage, processing or transit,
and against the denial of service to authorized users or the provision of service to
unauthorized users, including those measures necessary to detect, document, and
counter such threats.“
Protecting data from unauthorized access is one component of data security that
receives a great deal of attention. The concern for data protection extends beyond
corporate concerns but is a high priority consumer interest as well. Data can be
protected against unauthorized access through a variety of mechanisms. Passwords,
digital certificates and biometric techniques all provide a more secure method to access
data. Once the authorized user has been authorized or authenticated, sensitive
information can be encrypted toprevent spying or theft. However, even the most
sophisticated data security programs and measures cannot prevent human error.
Security safeguards must be adhered to and protected to be effective.
Information is typically categorized as being in either a structured format or an
unstructured format. The meaning of these terms is subject to different interpretations
by divergent groups.

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Unstructured Data
Structured data is data that conforms to some sort of strict data model and is confined
by that model. The model might define a business process that controls the flow of
information across a range of service-oriented architecture (SOA) systems.
Database Security Concepts
Architecturally, relational databases function in a client-server manner (although they
can certainly be used as part of multitier applications). That is, a client computer,
application, or user can only communicate directly with the database services that are
running. They cannot directly access the database files, as can be done with “desktop”
database systems, such as Microsoft Access. This is an important point, since it allows
security configuration and management to occur at the database level, instead of leaving
that responsibility to users and applications.
Databases can be used in various capacities, including:
• Application support:
Ranging from simple employee lists to enterprise-level tracking software, relational
databases are the most commonly used method for storing data. Through the use of
modern databases, users and developers can rely on security, scalability, and
recoverability features.
• Secure storage of sensitive information:
Relational databases offer one of the most secure methods of centrally storing important
data. As we’ll see throughout this chapter, there are many ways in which access to data
can be defined and enforced. These methods can be used to meet legislative
requirements in regulated industries (for example, the HIPAA standard for storing and
transferring healthcare-related information) and generally for storing important data.
• Online transaction processing (OLTP):
OLTP services are often the most common functions of databases in many
organizations. These systems are responsible for receiving and storing information that
is accessed by client applications and other servers. OLTPdatabases are characterized
by having a high level of data modification (inserting, updating, and deleting rows).
Therefore, they are optimized to support dynamically changing data. Generally, they
store large volumes of information that can balloon very quickly if not managed
properly.

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• Data warehousing:
Many organizations go to great lengths to collect and store as much information as
possible. But what good is this information if it can’t easily be analyzed? The primary
business reason for storing many types of information is to use this data eventually to
help make business decisions. Although reports can be generated against OLTP
databases, there are several potential problems: Reports might take a long time to run,
and thus tax system resources. If reports are run against a production OLTP server,
overall system performance can be significantly decreased. OLTP servers are not
optimized for the types of queries used in reporting. thus making the problem worse.
Reporting requirements are very different. In reporting systems, the main type of
activity is data analysis. OLTP systems get bogged down when the amount of data in the
databases gets very large. Therefore, production OLTP data must be often archived to
other media or stored in another data repository. Relational database platforms can
serve as a repository for information collected from many different data sources within
an organization. This database can then be used for centralized reporting and by
“decision support” systems.
Database Security Layers
Server-Level Security
A database application is only as secure as the server it is running on. Therefore,
it’s important to start considering security settings at the level of the physical
server or servers on which your databases will be hosted. In smaller, simple
configurations, you might need to secure only a single machine. Larger
organizations will likely have to make accommodations for many servers. These
servers may be geographically distributed and even arranged in complex
clustered configurations. One of the first steps you should take in order to secure
a server is to determine which users and applications should have access to it.
Modern database platforms are generally accessible over a network, and most
database administration tasks can be performed remotely. Therefore, other than
for purposes of physically maintaining database hardware, there’s little need for
anyone to have direct physical access to a database. It’s also very important to
physically protect databases in order to prevent unauthorized users from
accessing database files and data backups. If an unauthorized user can get
physical access to your servers, it’s much more difficult to protect against further
breaches.

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Network-Level Security
Databases work with their respective operating system platforms to serve users
with the data they need. Therefore, general operating system and network-level
security also applies to databases. If the underlying platform is not secure, this
can create significant vulnerabilities for the database. Since they are designed as
network applications, you must take reasonable steps to ensure that only specific
clients can access these machines. Some standard “best practices” for securing
databases include limiting the networks and/or network addresses that have
direct access to the computer. For example, you might implement routing rules
and packet filtering to ensure that only specific users on your internal network
will even be able to communicate with a server.
Of course, few real-world databases work alone. Generally, these systems are
accessed directly by users, and often by mission-critical applications. Later in this
chapter, we’ll look at some methods for mitigating risks related to Internet-
accessible applications.
Data Encryption
Another method for ensuring the safety of database information is to use
encryption. Most modern databases support encrypted connections between the
client and the server. Although these protocols can sometimes add significant
processing and data transfer overhead (especially for large result sets or very
busy servers), the added security may be required in some situations.
Additionally, through the use of virtual private networks (VPNs), systems
administrators can ensure that sensitive data remains protected during transit.
Depending on the implementation, VPN solutions can provide the added benefit
of allowing network administrators to implement security without requiring
client or server reconfiguration.
Operating System Security
On most platforms, database security goes hand in hand with operating system
security. Network configuration settings, file system permissions, authentication
mechanisms, and operating system encryption features can all play a role in
ensuring that databases remain secure. For example, on Windows-based
operating systems, only the NTFS file system offers any level of file system
security (FAT and FAT32 partitions do not provide any file system security at all).
In environments that use a centralized directory services infrastructure, it’s
important for systems administrators to keep permissions settings up to date and
to ensure that unnecessary accounts are deactivated as soon as possible.
Fortunately, many modern relational database platforms can leverage the
strengths of the operating systems that they run on.

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Database Backup and Recovery
An integral part of any overall database security strategy should be providing for
database backup and recovery. Backups serve many different purposes. Most
often, it seems that systems administrators perform backups to protect
information in the case of server hardware failures. Although this is a very real
danger in most environments, it’s often not the most likely. Data can be lost due
to accidental human errors, flawed application logic, defects in the database or
operating system platform, and, of course, malicious users who are able to
circumvent security measures. In the event that data is incorrectly modified or
destroyed altogether, the only real method to recover information is from
backups.
Since all relational database systems provide some method for performing
database backups while a server is still running, there isn’t much of an excuse for
not implementing backups. The real challenge is in determining what backup
strategies apply to your own environment. You’ll need to find out what your
working limitations are. This won’t be an easy task, even in the best-managed
organizations. It involves finding information from many different individuals
and departments within your organization. You’ll have to work hard to find
existing data, and make best guesses and estimates for areas in which data isn’t
available.
Tofurther complicate issues, there are many constraints in the real world that
can affect the implementation of backup processes. First, resources such as
storage space, network bandwidth, processing time, and local disk I/O bandwidth
are almost always limited. Additionally, human resources—especially
knowledgeable and experienced database administrators—may be difficult to
find. And, performance requirements, user load, and other factors can prevent
you from taking all the time you need to implement an ideal backup solution.
Typesof DatabaseBackups
In an ideal world, you would have all of the resources you need to back up all of
your data almost instantly. However, in the real world, large databases and
performance requirements can often constrain the operations that can be
performed (and when they can be performed). Therefore, you’ll need to make
some compromises. For example, instead of backing up all of your data hourly,
you might have to resort to doing full backups once per week and smaller
backups on other days. Although the terminology and features vary greatly
between relational database platforms,

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The following types of backups are possible on most systems:
• Full backups
This type of backup consists of making a complete copy of all of the data in a
database. Generally, the process can be performed while a database is up and
running. On modern hardware, the performance impact of full backups may be
almost negligible. Of course, it’s recommended that database administrators test
the performance impact of backups before implementing an overall schedule.
Full backups are the basis for all other types of backups. If disk space constraints
allow it, it is recommended to perform full backups frequently.
• Differential backups
This type of backup consists of copying all of the data that has changed since the
last full backup. Since differential backups contain only changes, the recovery
process involves first restoring the latest full backup and then restoring the latest
differential backup. Although the recovery process involves more steps (and is
more time-consuming), the use of differential backups can greatly reduce the
amount of disk storage space and backup time required to protect large
databases.
• Transaction log backups
Relational database systems are designed to support multiple concurrent updates
to data. In order to manage contention and to ensure that all users see data that
is consistent to a specific point in time, data modifications are first written to a
transaction log file. Periodically, the transactions that have been logged are then
committed to the actual database. Database administrators can choose to
perform transaction log backups fairly frequently, since they only contain
information about transactions that have occurred since the last backup. The
major drawback to implementing transaction log backups is that, in order to
recover a database, the last full (or differential) backup must be restored. Then,
the unbroken chain of sequential transaction log files must be applied.
Depending on the frequency of full backups, this might take a significant amount
of time. However, transaction log backups also provide one extremely important
feature that other backup types do not: point-in-time recovery. What this means
is that, provided that backups have been implemented properly, database
administrators can roll a database back to a specific point in time. For example, if
you learn that an incorrect or unauthorized database transaction was performed
at 3:00 p.m. on Friday, you will be able to restore the database to a point in time
just before that transaction occurred. The end result is minimal data loss.

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Database Auditing and Monitoring
The idea of accountability is an important one when it comes to network and
database security. The process of auditing involves keeping a log of data
modifications and permissions usage. Often, users that are attempting to
overstep their security permissions (or users that are unauthorized altogether)
can be detected and dealt with before significant damage is done; or, once data
has been tampered with, auditing can provide details about the extent of loss or
data changes. There’s another benefit to implementing auditing: when users
know that certain actions are being tracked, they might be less likely to attempt
to snoop around your databases. Thus, this technique can serve as a deterrent.
Unfortunately, in many environments, auditing is overlooked.
Though it won’t necessarily prevent users from modifying information, auditing
can be a very powerful security tool. Most relational databases provide you with
the ability to track specific actions based on user roles or to track actions on
specific database objects.
Although auditing can provide an excellent way totrack detailed actions,
sometimes you just want to get a quick snapshot of who’s using the server and for
what purpose. Most databases provide easy methods for viewing this information
(generally through graphical utilities). You may be able to get a quick snapshot of
current database activity or view any long-running transactions that are currently
in process.
The Data Protection Principles
 Personal data shall be processed fairly and lawfully and shall not be processed
unless certain conditions are met (set out in schedules 2 and 3 to the DPA).
 Personal data shall be obtained only for one or more specified and lawful
purposes, and shall not be further processed in any manner incompatible with
that purpose or those purposes.
 Personal data shall be adequate, relevant and not excessive in relation to the
purpose or purposes for which it is processed.
 Personal data shall be accurate and, where necessary, kept up to date.
 Personal data processed for any purpose or purposes shall not be kept for longer
than is necessary for that purpose or those purposes.
 Personal data shall be processed in accordance with the rights of data subjects
under the DPA.
 Appropriate technical and organizational measures shall be taken against
unauthorized or unlawful processing of personal data and against accidental loss
or destruction of, or damage to, personal data.
 Personal data shall not be transferred toa country or territory outside the EEA
unless that country or territory ensures an adequate level of protection for the
rights and freedoms of data subjects in relation to the processing of personal
data.

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The Eight Data Protection Act Principles
The act contains eight “Data Protection Principles”. These specify that personal data
must be:
 Processed fairly and lawfully.
 Obtained for specified and lawful purposes.
 Adequate, relevant and not excessive.
 Accurate and up to date.
 Not kept any longer than necessary.
 Processed in accordance with the “data subject’s” (the individual’s) rights.
 Securely kept.
 Not transferred to any other country without adequate protection in situ.
Data Collection
When collecting personal data make sure that people know:
1. Who you are
2. What the data will be used for
3. Towhom it will be disclosed.
This information can often be provided on an application form or similar. It is equally
important NOT to collect more personal data than is actually needed.
Handling Data
When handling, collecting, processing or storing personal data, ensure that:
1. All personal data is both accurate and up to date
2. Errors are corrected effectively and promptly
3. The data is deleted/destroyed when it is no longer needed
4. The personal data is kept secure at all times (protecting from unauthorized disclosure
or access)
5. The Data Protection Act is considered when setting up new systems or when
considering use of the data for a new purpose. Note that this may affect the existing
registration with the Data Protection Authority
6. Written contracts are used when external bodies process/handle the data explicitly
specifying the above requirements with respect to the data
It is equally important NOT to:

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1. Access personal data that you do not need for your work
2. Use the data for any purpose it was not explicitly obtained for
3. Keep data that would embarrass or damage YOUR-COMPANY if disclosed (eg: via a
subject access request – see below)
4. Transfer personal data outside of the European Economic Area unless you are certain
you are entitled to or consent from the individual concerned has been obtained
5. Store/process/handle sensitive personal data (see below) unless are certain you are
entitled to or consent from the individual concerned has been obtained
Subject Access
Individuals, who the data relates to, have various rights:
1. To receive on request details of the processing relating to themselves. This includes
any information about themselves including information regarding the source of the
data and about the logic of certain “fully automated decisions”
2. To have any inaccurate data corrected or removed in a timely fashion
3. In certain circumstances to stop processing likely to cause “substantial damage or
substantial distress”.
4. To prevent their data being used for advertising or marketing
5. Not to be subject to certain “fully automated decisions” if they significantly affect
him/her.
When a subject access request is received, it is important to act promptly and effectively
as certain time scales are imposed regarding response
('Sensitive Data' means data pertaining to: racial or ethnic origin; religious or similar
beliefs; trade union membership; physical or mental health or sexual life; political
opinions; criminal offences. This data may only be held in strictly defined situations or
where explicit consent has been obtained.
'Data Controller' is a person who determines the purposes for which and the manner in
which any personal data are, or are to be, processed.
'Subject Access' is the right of individuals to have access to the data about them and
other related information.
'Notification' is the process of notifying the Data Protection Authority of the purposes
for which personal data is held/processed.)

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