Network Security Concepts and Policies

Evaluating and Managing the Risk

The security policy developed in your organization drives all the steps taken to secure network resources. The development of a comprehensive security policy prepares you for the rest of your security implementation. To create an effective security policy, it is necessary to do a risk analysis, which will be used to maximize the effectiveness of the policy and procedures that will be put in place. Also, it is essential that everyone be aware of the policy; otherwise, it is doomed to fail.

All design guidelines and principles, and the resulting security architecture, should be aimed at managing risk. Risk is, or should be, the building block of information security.

Levels of Risks

By its very nature, risk management is a tradeoff between the effort (cost) to protect organizational assets and the resulting level of exposure of those assets. This simple rule is a good starting point: the cost to protect an asset will likely not be greater than the value of the asset itself. There are obviously exceptions to the rule; for instance, cases that involve national security, or instances where the value of the asset is incalculable, such as cases where human life is involved.

The tradeoffs in risk management are based on its building blocks: assets and vulnerabilities, threats and countermeasures. Different values and scenarios for these components move the risk indicators up and down. Understanding these values and scenarios is critical in defining a risk management strategy.

For instance, would you use old, worn tires at high speed on a highway? The answer is obviously no. The asset that you are trying to protect (your life) is too valuable, and the countermeasure to mitigate the risk of navigating the highway, driving at a slow speed, is not good enough. It is inexpensive but not effective.

However, using a worn-down tire as a swing does not result in life-threatening risk in the majority of situations. The asset (your life) remains the same, but the threats that are able to exploit the vulnerabilities of the tire are mitigated or nonexistent. The premise changes again if you think that this worn-down tire will be used to swing your child. You may or may not risk using the old tire, but the value of the asset may prevent you from facing risk even if it is minimal.

The previous example is a simplistic view of information security risk. Imagine an organizational risk management effort, considering thousands of assets with different (and often subjective) valuation criteria, different (and often unknown) levels of vulnerability, and potentially exposed to an avalanche of threats that change by the minute. Risk management becomes a delicate balance and involves constant tuning of countermeasures in the face of sophisticated threat vectors, exploiting assets that are often located outside of corporate control.

Information security risk management is a comprehensive process that requires organizations to frame risk (in other words, establish the context for risk-based decisions), assess risk, respond to risk, and monitor risk on an ongoing basis. The result is a dynamic process in nature, evolving along with internal factors (assets, vulnerabilities, security policies, and architectures) and external factors (threats, and business, legal, and compliance forces).

Other sections in this chapter will expand on these concepts and present commonly used risk management strategies, within the context of a security policy and a security lifecycle process.

Risk Analysis and Management

Every process of security should first address the following questions:

• Which are the threats the system is facing?
• Which are the probable threats and what would be their consequence, if exploited?

The threat-identification process provides an organization with a list of threats to which a system is subject in a particular environment.

Risk Analysis

Risk analysis is the systematic study of uncertainties and risks. Risk analysts seek to identify the risks that a company faces, understand how and when they arise, and estimate the impact (financial or otherwise) of adverse outcomes. Risk managers start with risk analysis, and then seek to take actions that will mitigate these risks. Risk analysis tries to estimate the probability and severity of threats faced by an organization’s system that needs protection, and then provides to the organization a prioritized list of risks that the organization must mitigate. This allows the organization to focus on the most important threats first.

Two types of risk analysis are of interest in information security:

• Quantitative: Quantitative risk analysis uses a mathematical model that assigns monetary values to assets, the cost of threats being realized, and so on. Quantitative risk analysis provides an actual monetary figure of expected losses, which is typically based on an annual cost. You can then use this number to justify proposed countermeasures. For example, if you can establish that you will lose $1,000,000 by doing nothing, you can justify spending $300,000 to reduce that risk by 50 percent to 75 percent.
• Qualitative: Qualitative risk analysis uses a scenario model. This approach is best for large cities, states, and countries to use because it is impractical for such entities to try to list all their assets, which is the starting point for any quantitative risk analysis. By the time a typical national government could list all of its assets, the list would have hundreds or thousands of changes and would no longer be accurate.

Qualitative risk analysis is straightforward provided you have the resources to document all the assets. However, quantitative risk analysis is more tricky, so we will take a closer look at it.

Quantitative Risk Analysis Formula

Quantitative risk analysis relies on specific formulas to determine the value of the risk decision variables. These include formulas that calculate the asset value (AV), exposure factor (EF), single loss expectancy (SLE), annualized rate of occurrence (ARO), and annualized loss expectancy (ALE). The ALE formula is as follows: ALE = (AV * EF) *ARO.

The AV is the value of an asset. This would include the purchase price, the cost of deployment, and the cost of maintenance. In the case of a database or a web server, the AV should also include the cost of development. AV is not an easy number to calculate.

The EF is an estimate of the degree of destruction that will occur. For example, suppose that you consider flood a threat. Could it destroy your data center? Would the destruction be 60 percent, 80 percent, or 100 percent? The risk-assessment team would have to make a determination that evaluates everything possible, and then make a judgment call. For this example, assume that a flood will have a 60 percent destruction factor, because you store a backup copy of all media and data offsite. Your only losses would be the hardware and productivity.

As another example of EF, consider data entry errors, which are much less damaging than a flood. A single data entry error would hardly be more than a fraction of a percent in exposure. The exposure factor of a data entry error might be as small as .001 percent.

The SLE calculation is a number that represents the expected loss from a single occurrence of the threat. The SLE is defined as AV * EF.

To use our previous examples, you would come up with the following results for the SLE calculations:

• Flood threat
  • Exposure factor: 60 percent
  • AV of the enterprise: US$10,000,000
  • $10,000,000 * .60 = $6,000,000
• Data entry error
  • Exposure factor: .001 percent
  • AV of data and databases: $1,000,000
  • $1,000,000 * .000001 = $10 SLE

The ARO is a value that estimates the frequency of an event and is used to calculate the ALE.

Continuing the preceding example, the type of flood that you expect could reach your data center would be a “flood of the century” type of event. Therefore, you give it a 1/100 chance of occurring this year, making the ARO for the flood 1/100.

Furthermore, you expect the data entry error to occur 500 times a day. Because the organization is open for business 250 days per year, you estimate the ARO for the data entry error to be 500 * 250, or 125,000 times.

Risk analysts calculate the ALE in annualized terms to address the cost to the organization if the organization does nothing to counter existing threats. The ALE is derived from multiplying the SLE by the ARO. The following ALE calculations continue with the two previous examples:

• Flood threat
  • SLE: $6,000,000
  • ARO: .01
  • $6,000,000 * .01 = $60,000 ALE
• Data input error
  • SLE: $10
  • ARO: 125,000
  • $10 * 125,000 = $1,250,000 ALE

A decision to spend $50,000 to enhance the security of our database applications to reduce data entry errors by 90 percent is now an easy decision. It is equally easy to reject a proposal to enhance our defenses against floods that costs $3,000,000.

When you perform a quantitative risk analysis, you identify clear costs as long as the existing conditions remain the same. You compile a list of expected issues, the relative cost of those events, and the total cost if all expected threats are realized. These numbers are put into annual terms to coincide with the annual budgets of most organizations.

You then use these numbers in decision making. If an organization has a list of 10 expected threats, it can then prioritize the threats and address the most serious threats first. This prioritization enables management to focus their resources where it will do the most good.

For example, suppose an organization has the following list of threats and costs as the product of performing a quantitative risk analysis:

• Insider network abuse: $1,000,000 in lost productivity
• Data input error: $500,000
• Worm outbreak: $100,000
• Viruses: $10,000
• Laptop theft: $10,000

Decision makers could easily decide that it is of greatest benefit to address insider network abuse and leave the antivirus solution alone. They could also find it easy to support a $200,000 URL filtering solution to address insider network abuse and reject a $40,000 solution designed to enhance laptop safety. Without these numbers from a risk analysis, the decisions made would likely differ.

Building Blocks of Risk Analysis

Conducting a risk analysis starts with the gathering of pertinent information. The building blocks of the process follow the definition of risk used in this book: the organizational impact of threat vectors exploiting vulnerabilities of the assets you are trying to protect.

In that sense, the initial information gathering, in preparation for the risk calculations described in the previous example, should collect and define the following:

• Assets and their value: This information, shown in Table 1-1, is typically obtained from data classification, inventories of assets, and other sources. A general principle is to use discrete numerical values for the exposure factor (EF) based on discrete values that reflect the impact of losing the asset. These values are generally based on data classification techniques (confidential, secret, top secret, and so on), and the impact is based on organizationally relevant criteria (replacement cost, liability, and so on).

  Table 1-1. List of Assets and Their Value

  	Confidentiality	Integrity	Availability
  Low Value	Limited effect	Limited effect	Limited effect
  Moderate Value	Serious effect	Serious effect	Serious effect
  High Value	Severe effect	Severed effect	Severe effect

• Vulnerabilities: This information is typically gathered from vulnerability assessments, which will be discussed further later in this chapter. Several tools are available, like Nessus and other commercial vulnerability assessment products. The use of public- or platform-specific vulnerability classification databases is commonplace. They include the Common Vulnerabilities and Exposures (CVE) effort by MITRE, http://cve.mitre.org, and the National Vulnerability Database (NVD) sponsored by the National Institute of Standards and Technology (NIST), http://nvd.nist.gov. An example of vulnerability categorization is shown in Table 1-2.

  Table 1-2. Example of Vulnerability Categorization Headings

  Categorization	Procedures	Processes	Systems	Network

• Threats, their impact, and rate or probability of occurrence: This information is commonly obtained from publicly available databases, such as the MITRE Common Attack Pattern Enumeration and Classification (CAPEC), http://capec.mitre.org. Calculating the rate of occurrence is a probabilistic exercise and is often considered subjective and specific for individual organizations or industries. Table 1-3 shows an example of this information gathering.

  Table 1-3. Example of Threats, Impact, and Probability of Occurrence

  Impact Category	Critical	Serious	Moderate	Minor	Negligible
  Definition	Inability to achieve minimum requirements	Major cost and schedule increases	Moderate cost and schedule increases	Small cost and schedule increases	No effect

Risk Scores

With asset, vulnerability, and threat components defined, risk scores are obtained by applying formulas of quantitative risk analysis. Figure 1-12 illustrates the process.

Figure 1-12. Obtaining a Risk Score

A risk matrix is then calculated, including risk scores for assets and groups of assets and, ideally, an organization risk score that can be used in security monitoring, incident response, and policy reviews. These risk scores provide an idea of the landscape of assets, threats, vulnerabilities, and countermeasures, the components of risk, at a given point in time.

A Lifecycle Approach to Risk Management

Managing risk is a complex, multifaceted activity that requires the involvement of the entire organization, including the following:

• Senior leaders and executives who provide the strategic vision and top-level goals and objectives for the organization
• Midlevel leaders who plan, execute, and manage projects
• Individuals who operate the information systems supporting the organization’s mission and business functions

Figure 1-13 shows that risk management is a comprehensive process that requires organizations to do the following:

• Frame risk (that is, establish the context for risk-based decisions)
• Assess risk
• Respond to risk once determined
• Monitor risk on an ongoing basis using effective organizational communications and a feedback loop for continuous improvement in the risk-related activities of organizations
  

  Figure 1-13. Lifecycle Approach to Risk Management According to NIST 800-39

  Source: NIST 800-39, 2011

Risk management is carried out as a holistic, organization-wide activity that addresses risk from the strategic level to the tactical level. Approaching risk management in this way ensures that risk-based decision making is integrated into every aspect of the organization.

Regulatory Compliance

Compliance regulations have been a major driver for security in organizations of all kinds, and the following trends have emerged over the past decade:

• Strengthened enforcement
• Global spread of data breach notification laws
• More prescriptive regulations
• Growing requirements regarding third parties (business partners)
• Risk-based compliance on the rise
• Compliance process streamlined and automated

The compliance regulation defines not only the scope and parameters for the risk and security architectures of an organization, but also the liability for those who do not comply. Recently there have been major shifts in the compliance landscape:

• Although enforcement of existing regulations has been weak in many jurisdictions worldwide, regulators and standards bodies are now tightening enforcement through expanded powers, higher penalties, and harsh enforcement actions.
• In the future, it will be more difficult to hide information security failings wherever organizations do business. Legislators are forcing transparency through the introduction of breach notification laws in Europe, Asia, and North America as data breach disclosure becomes a global principle.
• As more regulations are introduced, there is a trend toward increasingly prescriptive rules. For example, laws in the states of Massachusetts and Nevada, which went into effect in 2010, apply not only to companies based in these states but also to all external organizations that manage the personal information of these states’ residents.
• Regulators are also making it clear that enterprises are responsible for ensuring the protection of their data when it is being processed by a business partner, including cloud service providers.
• For many organizations, stricter compliance could help focus management attention on security; but if they take a “check-list approach” to compliance, it will detract from actually managing risk and may not improve security.
• The new compliance landscape will increase costs and risks. For example, it takes time and resources to substantiate compliance. Increased requirements for service providers give rise to more third-party risks.
• With more transparency, there are now greater consequences for data breaches. For example, expect to see more litigation as customers and business partners seek compensation for compromised data. But the harshest judgments will likely come from the court of public opinion—with the potential to permanently damage the reputation of an enterprise.

Table 1-4 illustrates some examples of relevant compliance regulations (most of which were introduced earlier in the chapter) that affect organizations all over the world. Geographic boundaries are blurring as globalization makes organizations subject to regulations in several countries. Industry scope boundaries are also blurring. For instance, many service organizations providing services to the U.S. government have to comply with U.S. federal regulations related to information security.

Table 1-4. Examples of Compliance Regulations

The following are descriptions of some of the regulations listed in Table 1-4:

• The Gramm-Leach-Bliley Act (GLBA) of 1999 erased long-standing antitrust laws that prohibited banks, insurance companies, and securities firms from merging and sharing information with one another. The idea was that smaller firms would then be able to pursue acquisitions or alliances, or both, that would help encourage competition against many of the larger financial institutions. Included in the GLBA were several consumer privacy protections. Namely, companies must tell their customers what kinds of data they plan to share and with whom, and they must give their customers a chance to opt out of that data sharing.
• On the healthcare side, the Health Insurance Portability and Accountability Act (HIPAA) of 2000 requires the U.S. Department of Health and Human Services to develop a set of national standards for healthcare transactions. These standards provide assurance that the electronic transfer of confidential patient information will be as safe as, or safer than, paper-based patient records.
• The Sarbanes-Oxley (SOX) Act of 2002 is a U.S. law that was created in response to a number of major corporate and accounting scandals, including those affecting Enron, Tyco International, Peregrine Systems, and WorldCom. These scandals resulted in a decline of public trust in accounting and reporting practices.
• The Federal Information Security Management Act (FISMA) of 2002 was intended to bolster computer and network security within the U.S. government and affiliated parties by requiring yearly audits. FISMA also brought attention within the U.S. government to cyber security, which the U.S. government had largely neglected previously.

Globalization, as with any other context, is changing the face of regulatory compliance. Regulators are not just looking at ways to strengthen existing laws. Regulators are also introducing new laws that are aimed at forcing more transparency, in a way that affects organizations on a global basis.

Data breach disclosure is becoming a global principle as jurisdictions worldwide adopt privacy and data protection laws that include a general obligation to notify government agencies, individuals, and other authorities such as law enforcement of unauthorized access or use of personal data. Requirements vary, including who must be notified, the type of data that triggers notification, and if there is a risk-of-harm threshold.

California’s landmark legislation SB-1386 set off a wave of state breach notification laws that now cover almost the entire United States. Recently, this trend has spread to the European Union. The Privacy and Electronic Communications Directive (e-Privacy Directive) was amended in late 2009 to include data breach notification. It is now mandatory for telephone companies and ISPs in the EU to inform national regulatory authorities of any data security breach. Depending on the effects of the breach, they may also be required to inform subscribers. The upcoming overhaul of the EU Data Protection Directive is expected to include data breach notification requirements, which would broaden breach disclosure to cover all industries in all 27 member countries in the EU.

Table 1-5 shows how regulations are becoming the norm around the world.

Table 1-5. Acceleration of Compliance Regulation Around the World