The importance of security varies by organization. The variations exist because of the differing values placed on information and networks within organizations. For example, organizations involved in banking and healthcare will likely place a greater priority on information security than organizations involved in selling greeting cards. However, in every organization there exists a need to classify data so that it can be protected appropriately. The greeting card company will likely place a greater value on its customer database than it will on the log files for the Internet firewall. Both of these data files have value, but one is more valuable than the other and should be classified accordingly so that it can be protected properly.
Data classification is the process used to identify the value of data and the cost of data loss or theft. Consider that the cost of data loss is different than the cost of data theft. When data is lost, it means that you no longer have access to the data; however, it does not follow automatically that someone else does have access to the data. For example, an attacker may simply delete your data. This action results in lost data. Data theft indicates that the attacker stole the data. With the data in the attacker’s possession, the attacker can sell it or otherwise use it in a way that can damage the organization’s value. The worst case scenario is data theft with loss. In this case, the attacker steals the data and destroys the copies. Now the attacker can use the data, but the organization cannot.
When classifying data, then, you are attempting to answer the following questions:
- How valuable is the data to the organization?
- How valuable is the data to competitors or outside individuals?
- Who should have access to the data?
- Who should not have access to the data?
It might seem odd to ask both of the latter two questions, but it can be very important. For example, you may identify a group who should have access to the data with the exception of one individual in that group. In this case, the group should have access to the data, but the individual in that group should not, and the resulting permission set should be built accordingly. In a Microsoft environment, you would create a group for the individuals needing access and grant that group access to the resource. Next, you would explicitly deny access to the individual who should not have access. The denial overrides the grant and you accomplish the access required.
Many organizations will classify data so that they can easily implement and maintain permissions. For example, if data is classified as internal only, it’s a simple process to configure permissions for that data. Simply create a group named All Employees and add each internal employee to this group. Now, you can assign permissions to the All Employees group for any data classified as internal only. If data is classified as unclassified or public, you can provide access to the Everyone group in a Windows environment and achieve the needed permissions. The point is that data classification leads to simpler permission (authorization) management.
From what I’ve said so far, you can see that data classification can be defined as the process of labeling or organizing data in order to indicate the level of protection required for that data. You may define data classification levels of private, sensitive, and public. Private data would be data that should only be seen by the organization’s employees and may only be seen by a select group of the organization’s employees. Sensitive data would be data that should only be seen by the organization’s employees and approved external individuals. Public data would be data that can be viewed by anyone.
Consider the following applications of this data classification model:
- The information on the organization’s Internet web site should fall in the classification of public data.
- The contracts that exist between the organization and service providers or customers should fall in the classification of sensitive data.
- Trade secrets or internal competitive processes should be classified as private data.
The private, sensitive, and public model is just one example of data classification, but it helps you to determine which data users should be allowed to store offline and which data should only be access while authenticated to the network. By keeping private data off of laptops, you help reduce the severity of a peer-to-peer attack that is launched solely to steal information.
This data classification process is at the core of information security, and it can be outlined as follows:
- Determine the value of the information in question.
- Apply an appropriate classification based on that value.
- Implement the proper security solutions for that classification of information.
From this very brief overview of information classification and security measures, you can see why different organizations have different security priorities and needs. It is also true, however, that every organization is at risk for certain threats. Threats such as denial of service (DoS), worms, and others are often promiscuous in nature. The attacker does not care what networks or systems are damaged or made less effective in a promiscuous attack. The intention of such an attack is often only to express the attacker’s ability or to serve some other motivation for the attacker, such as curiosity or need for recognition. Because many attacks are promiscuous in nature, it is very important that every organization place some level of priority on security regardless of the intrinsic value of the information or networks they employ.