The information security industry recognizes both the necessity and the difficulty of carrying out a quantitative evaluation of ROSI, return on security investment.
The main reason for investing in security measures is to avoid the cost of accidents, errors and attacks. Direct costs of an incident may include lost revenues, damages and property loss, or direct economic loss. The total cost can be considered to be the direct cost plus the cost of restoring the system to its original state before the incident. Some incidents can cost information, fines, or even human lives.
The indirect cost of an incident may include damage to a company’s public image, loss of client and shareholder confidence, cash-flow problems, breaches of contract and other legal liabilities, failure to meet social and moral obligations, and other costs.
What do we know intuitively about the risk and cost of security measures? First, the relationship between the factors that affect risk - such as window of opportunity, value of the asset and its value to the attacker, combined assets, number of incidents and their cost, etc. - is quite complex. We also know that when measures are implemented to reduce risk, the ease of using and managing systems also decreases, generating an indirect cost of the security measures.
How do we go from this intuitive understanding to quantitative information? There is some accumulated knowledge of the relationship between investment in security measures and their results. First, there is the Mayfield paradox, according to which the cost of universal access to a system and absolutely restricted access is infinite, with more acceptable costs corresponding to the intermediate cases.
An empirical study was also done by the CERT at Carnegie Mellon University, which states that the greater the expenditure on security measures, the smaller the effect of the measures on security. This means that after a reasonable investment has been made in security measures, doubling security spending will not make the system twice as secure.
The study that is most easily found on the Internet on this subject cites the formulas created during the implementation of an intrusion detection system by a team from the University of Idaho.
E: prevented losses
T: total cost of security measures
R-ALE = ROSI, therefore ROSI = E-T
The problem with this formula is that E is merely an estimate, and even more so if the measure involved is an IDS, which simply collects information on intrusions, which means that there is no cause-effect relationship between detecting an intrusion and preventing an incident. Combining this type of estimate with basing it on mathematical formulas is like combining magic with physics.
What problems do we face in calculating return on investment of security measures? The most important is the lack of concrete data, followed closely by a series of commonly accepted suppositions and half-truths, such as that risk always decreases as investment increases, and that the return on the investment is positive for all levels of investment.
Nobody invests in security measures to make money; they invest in them because they have no choice. Return on investment demonstrates that investing in security is profitable, in order to select the best security measures with a given budget, and to determine whether the budget allocated to security is sufficient to fulfill the business objectives, but not to demonstrate that companies make money off of the investment.
In general, and also from the point of view of return on investment, there are two types of security measures: measures to reduce vulnerability and measures to reduce impact.
- Measures that reduce vulnerability barely reduce the impact when an incident does occur. These measures protect against a narrow range of threats. They are normally known as Preventive Measures. Some of these measures are firewalls, padlocks, and access control measures. One example of the narrowness of the protection range is the use of firewalls, which protect against access to unauthorized ports and addresses, but not against the spread of worms or spam.
- Measures that reduce impact to very little to minimize vulnerability if an incident does occur. These measures protect against a broad range of threats and are commonly known as Corrective Measures. Examples of these measures include RAID disks, backup copies, and redundant communication links. One example of the range of protection is the use of backups, which do not prevent incidents, but do protect against effective information losses in the case of all types of physical and logical failures.
The profitability of both types of measures is different, as the rest of the article will show.
Preventive or Vulnerability-Reduction Measures
A reduction in vulnerability translates into a reduction in the number of incidents. Security measures that reduce vulnerability are therefore profitable when they prevent incidents for a value that is higher than the total cost of the measure during that investment period.
The following formula can be used:
ROSI = CTprevented / TCP
CT = Cost of Threat = Number of Incidents * Per Incident Cost.
TCP = Total Cost of Protection
When ROSI > 1, the security measure is profitable.
Several approximations can be used to calculate the prevented cost. One takes the prevented cost into account as the cost of the threat in a period of time before and after the implementation of the security measure.
CTprevented = ( CTbefore – CTafter)
Calculating the cost of the threat as the number of incidents multiplied by the cost of each incident is an alternative with respect to the traditional calculation of the incident probability multiplied by the incident cost, provided that the number of incidents in the investment period is more than 1. To calculate a probability mathematically, the number of favorable cases and the number of possible cases must be known. Organizations rarely have information on possible cases (but not “favorable” cases) of incidents. It is impossible to calculate the probability without this information. However, it is relatively simple to determine the number of incidents that occur within a period of time and their cost.
For a known probability to be predictive, it is also necessary to have a large enough number of cases, and conditions must also remain the same. Taking into account the complexity of the behavior of attackers and the organizations that use information systems, it would be foolish to assume that conditions will remain constant. Calculating the cost of a threat using probability information is therefore unreliable in real conditions.
One significant advantage of calculating the cost of a threat as the product of the number of incidents and their unit cost is that this combines the cost of the incidents, the probability, and the total assets (since the number of incidents partly depends on the quantity of the total assets) into a single formula. To make a profitability calculation like this, real information on the incidents and their cost is required, and gathering this information generates an indirect cost of an organization’s security management. If this information is not available, the cost of the threats will have to be estimated to calculate the ROSI, but the value of the calculation result will be low as the estimate can always be changed to generate any desired result.
The profitability of a vulnerability reduction measure depends on the environment. For example, in an environment in which many incidents occur, a security measure will be more profitable than in the case of another environment in which they do not occur. While using a personal firewall on a PC connected to the Internet twenty-four hours a day may be profitable, using one on a private network not connected to the Internet would not. Investing in a reinforced door would be profitable in many regions of Colombia, but in certain rural areas of Canada, this investment would be a waste of money.
Sample profitability calculation:
- Two laptops out of a total of 50 are stolen in a year.
- The replacement cost of a laptop is 1800 euros.
- The following year, the company has 75 laptops.
- The laptops are protected with 60€ locks.
- The following year only one laptop is stolen.
ROSI = ( Rbefore – Rafter) / TCP
ROSI = ( ( 1800+Vi )*3 - (( 1800+Vi )*1+75*60) )/( 75*60 )
(The number of incidents is adjusted for the increase in the number of targets).
If a laptop was worth nothing (Vi=0), the security measure would not be profitable (ROSI < 1). In this example, the 60€ locks are profitable when a laptop costs more than 2700€, or when, based on historical information, the theft of 5 laptops can be expected for the year in question.
Using this type of analysis, we could:
- Use locks only on laptops with valuable information.
- Calculate the maximum price of locks for all laptops (24€ when Iv=0).
Corrective or Impact-Reduction Measures
Since impact-reduction measures do not prevent incidents, the previous calculation cannot be applied. In the best case scenario, these measures are never used, while when there are two incidents which could result in the destruction of the protected assets, they are apparently worth twice the value of the assets. Now then, who would spend twice the value of an asset on security measures? Profitability of corrective measures cannot be measured. These measures are like insurance policies; they put a limit on the maximum loss suffered in the case of an incident.
What is important in the case of impact-reduction measures is the protection that you get for your money. The effectiveness of this protection can be measured, for example depending on the recovery time after an incident. Depending on their effectiveness, there are measures that range from backup copies (with some added cost) to fully redundant systems (which cost more than double).
One interesting alternative to calculating the ROSI of a specific security measure is to measure the ROSI of a set of measures – including detection, prevention, and impact reduction – that protect an asset. In this case, the total cost of protection (TCP) is calculated as the sum of the cost of all of the security measures, which the effort to obtain the information on the cost of the threats is practically identical.
Budget, cost, and selection of measures
The security budget should be at most equal to the annual loss expectancy (ALE) caused by attacks, errors, and accidents in information systems for a tax year. Otherwise, the measures are guaranteed not to be profitable. The graph below shows the expected losses as the area under the curve. To clarify the graph, it represents a company with enormous expected losses, of almost 25% of the value of the company. In the case of an actual company, legibility of the graph could be improved using logarithmic scales.
An evaluation of the cost of a security measure must take into account both the direct costs of the hardware, software, and implementation, as well as the indirect costs, which could include control of the measure by evaluating incidents, ethical hacking (attack simulation), audits, incident simulation, forensic analysis, and code audits.
Security measures are often chosen based on fear, uncertainty and doubt, or out of paranoia, to keep up with trends, or simply at random. However, the calculation of the profitability of security measures can help to select the best measures for a particular budget. Part of the budget must be allocated to the protection of critical assets using impact-reduction measures, and part to the protection of all of the assets using vulnerability-reduction measures and incident and intrusion detection measures.
The main conclusions that can be drawn from all of this are that:
- To guarantee maximum effectiveness of an investment, it is necessary, and possible if the supporting data is available, to calculate the return on the investment of vulnerability-reduction measures.
- In order to make real calculations, real information is needed regarding the cost of the incidents for a company or in comparable companies in the same sector.
- Both incidents and security measures have indirect and direct costs that have to be taken into account when calculating profitability.