Qualitative/quantitative These terms indicate the (oversimplified) binary categorization of risk metrics and information risk management techniques. In reality, there is a spectrum across which these terms apply, virtually always in combination. This spectrum may be described as the degree to which the risk management process is quantified. If all elements asset value, impact, threat frequency, safeguard effectiveness, safeguard costs, uncertainty, and probability are quantified, the process may be characterized as fully quantitative. It is virtually impossible to conduct a purely quantitative risk management project, because the quantitative measurements must be applied to the qualitative properties, i.e., characterizations of vulnerability of the target environment. For example, failure to impose logical access control is a qualitative statement of vulnerability. However, it is possible to conduct a purely qualitative risk management project. A vulnerability analysis, for example, may identify only the absence of risk-reducing countermeasures, such as logical access controls (though even this simple qualitative process has an implicit quantitative element in its binary yes/no method of evaluation). In summary, risk assessment techniques should be described not as either qualitative or quantitative but in terms of the degree to which such elementary factors as asset value, exposure factor, and threat frequency are assigned quantitative values.
Probability This term characterizes the chance or likelihood, in a finite sample, that an event will occur. For example, the probability of getting a 6 on a single roll of a die is 1/6, or 0.16667. The possible range of probability values is 0.0 to 1.0. A probability of 1.0 expresses certainty that the subject event will occur within the finite interval. Conversely, a probability of 0.0 expresses certainty that the subject event will not occur within the finite interval.
Risk The potential for harm or loss is best expressed as the answers to these four questions:
The key element among these is the issue of uncertainty captured in the fourth question. If there is no uncertainty, there is no risk per se.
Risk analysis This term represents the process of analyzing a target environment and the relationships of its risk-related attributes. The analysis should identify threat vulnerabilities, associate these vulnerabilities with affected assets, identify the potential for and nature of an undesirable result, and identify and evaluate risk-reducing countermeasures.
Risk assessment This term represents the assignment of value to assets, threat frequency (annualized), consequence (i.e., exposure factors), and other elements of chance. The reported results of risk analysis can be said to provide an assessment or measurement of risk, regardless of the degree to which quantitative techniques are applied. For consistency in this chapter, the term risk assessment hereafter is used to characterize both the process and the result of analyzing and assessing risk.
Risk management This term characterizes the overall process. The first, or risk assessment, phase includes identifying risks, risk-reducing measures, and the budgetary impact of implementing decisions related to the acceptance, avoidance, or transfer of risk. The second phase of risk management includes the process of assigning priority to, budgeting, implementing, and maintaining appropriate risk-reducing measures. Risk management is a continuous process of ever-increasing complexity.
Safeguard This term represents a risk-reducing measure that acts to detect, prevent, or minimize loss associated with the occurrence of a specified threat or category of threats. Safeguards are also often described as controls or countermeasures.
Safeguard effectiveness This term represents the degree, expressed as a percent, from 0 to 100%, to which a safeguard may be characterized as effectively mitigating a vulnerability (defined below) and reducing associated loss risks.
Single loss expectancy or exposure (SLE) This value is classically derived from the following algorithm to determine the monetary loss (impact) for each occurrence of a threatened event:
ASSET VALUE x EXPOSURE FACTOR = SINGLE LOSS EXPECTANCY
The SLE is usually an end result of a business impact analysis (BIA). A BIA typically stops short of evaluating the related threats ARO or its significance. The SLE represents only one element of risk, the expected impact, monetary or otherwise, of a specific threat event. Because the BIA usually characterizes the massive losses resulting from a catastrophic event, however improbable, it is often employed as a scare tactic to get management attention and loosen budgetary constraints, often unreasonably.
Threat This term defines an event (e.g., a tornado, theft, or computer virus infection), the occurrence of which could have an undesirable impact.
Uncertainty This term characterizes the degree, expressed as a percent, from 0.0 to 100%, to which there is less than complete confidence in the value of any element of the risk assessment. Uncertainty is typically measured inversely with respect to confidence, i.e., if confidence is low, uncertainty is high.
Vulnerability This term characterizes the absence or weakness of a risk-reducing safeguard. It is a condition that has the potential to allow a threat to occur with greater frequency, greater impact, or both. For example, not having a fire suppression system could allow an otherwise minor, easily quenched fire to become a catastrophic fire. Both expected frequency (ARO) and exposure factor (EF) for fire are increased as a consequence of not having a fire suppression system.
CENTRAL TASKS OF INFORMATION RISK MANAGEMENT
The following sections describe the tasks central to the comprehensive information risk management process. These tasks provide concerned management with the identification and assessment of risk as well as cost-justified recommendations for risk reduction, thus allowing the execution of well-informed management decisions on whether to avoid, accept, or transfer risk cost-effectively. The degree of quantitative orientation determines how the results are characterized and, to some extent, how they are used.
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