Instruction Manual 262-12-001-01
DHS Lexicon Terms and Definitions
2017 Edition – Revision 2
Issue Date – October 16, 2017
Management Directorate
Department of Homeland Security
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Prepared by:
DHS Lexicographer
DHS Lexicon Program
Office of the Under Secretary for Management
Management Directorate
U.S. Department of Homeland Security
[email protected]
Version Table
No.
Date
Description
Author
0
10/07/2008
First Release
DHS Lexicographer
1
12/16/2008
Revision and update.
DHS Lexicographer
2
10/23/2009
2009 Edition
DHS Lexicographer
3
01/26/2010
2010 Edition
DHS Lexicographer
4
07/01/2010
Revision and update
DHS Lexicographer
5
07/14/2011
2011 Edition
DHS Lexicographer
6
06/10/2013
2013 Edition
DHS Lexicographer
7
10/01/2013
Revision and update
DHS Lexicographer
8
02/17/2014
2014 Edition
DHS Lexicographer
9
04/23/2014
Revision and update
DHS Lexicographer
10
09/01/2015
2015 Edition
DHS Lexicographer
11
05/13/2016
2016 Edition
DHS Lexicographer
12
02/02/2017
2017 Edition
DHS Lexicographer
13
05/26/2017
Revision and update 1
DHS Lexicographer
14
10/16/2017
Revision and update 2
DHS Lexicographer
TABLE OF CONTENTS
1 Overview ...................................................................................................................... i
2 Structured Definitions................................................................................................... i
3 Use of Definitions ....................................................................................................... iii
4 Addition and Revision Instructions ............................................................................ iii
5 Terms and Definitions ................................................................................................. 1
6 Supplemental Information ....................................................................................... 722
DHS Lexicon
2017 Edition – Revision 2 i
1 Overview
On March 31, 2004, the Department of Homeland Security’s (DHS’s) Homeland Security Advisory
Council (HSAC) Lexicon Working Group recommended to the DHS Secretary Tom Ridge that DHS
should create a Homeland Security Lexicon. HSAC believed that a lexicon was vital to DHS’s success
and to the future of the United States, and recommended that DHS “create, sustain, and promote the
Homeland Security Lexicon” so that all language associated with DHS’s work would be as descriptive,
accurate, precise, and as widely understood as possible. In response, the Secretary created the DHS
Lexicon Program in June 2004.
The DHS Lexicon is a unified controlled vocabulary that DHS and its Components can use when
communicating and sharing data. We created this lexicon by combining and standardizing the different
vocabularies used by the Department. By providing a common definition for the terms we use every
day, the Lexicon reduces the possibility of misunderstandings when communicating across the
Department and helps DHS to develop and manage knowledge, information, and data. The DHS Lexicon
is the official source for terms and definitions supporting the Department and the homeland security
community.
2 Structured Definitions
We define terms within the DHS Lexicon using an easy to follow format to help users rapidly and
consistently understand the meaning of terminology used across Component’s and all other areas of the
homeland security community, as well as by other government agencies and the general public.
Definitions for terms within the DHS Lexicon are required to:
• Be in plain language and clearly defined;
• Express only a single meaning; and
• Not require additional interpretation.
Complete instructions on how we defined terms are available in the document Standardization of
Homeland Security Terminology and Definitions. You may request this document by
emailing [email protected]ov.
2.1.1 Definition Fields
In Part 5 “Terms and Definitions,” you will find the terms listed in a chart. The columns contain the
standard fields for expressing the meaning of any DHS Lexicon term.
They include the following:
Definition – A statement of the meaning of a particular word or phrase. In its construction, a definition
will always state the main object or root meaning first, followed by appropriate modification if necessary.
Extended Definition – If the term expresses a highly complex thought, a further explanatory statement
or more detail may be required. An extended definition provides this supplemental information without
DHS Lexicon
2017 Edition – Revision 2 ii
repeating or contradicting the definition. Instead, it provides additional statements of fact further
clarifying the definition, such as:
• Identification of distinguishing characteristics;
• Supporting facts or information; and
• What is included or not included in the definition.
Annotation – An annotation is not considered part of the definition. Where necessary, an annotation
provides additional comment or notation about the definition. For example, annotations can provide
examples of the use of the definition, offer deeper elaboration, or cite legal use or interpretation.
Usage Sample – Usage samples are not considered part of the definition. A usage sample shows how a
term is used in a sentence in order to illustrate the context of the term in application or use.
2.1.2 Additional Fields
Acronym – If a standard acronym or abbreviation is available for the term, it is also presented with the
term and definition.
Synonym – The DHS Lexicon recognizes instances where more than one term is commonly used to
express a specific meaning. All such synonyms for any definition are identified with the main term and
definition and are also referenced back to the main term.
See Also – Sometimes, it is helpful to include references to additional items within the subject area or
contrasting areas. “See also” identifies associated terms in the DHS Lexicon.
Supplemental Information – When we have provided an illustration or additional information to help
you understand or interpret the term or to show its relationship to other terms, we identify it by
providing the name of the illustration in this field.
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3 Use of Definitions
You may use your discretion to choose how much information you extract from the DHS Lexicon to
develop a glossary for a document or for single citation. If you believe your audience and purpose
requires extra information, you may combine both the definition and extended definition in your glossary
or citation.
1. Here is an examples of referencing “continuity” from the DHS Lexicon:
continuity
Definition: state or quality of being consistent, uninterrupted, or unbroken
Extended Definition: maintain uninterrupted support to essential functions in spite of natural
or man-made disasters; efforts to assure continuance of minimum essential functions across a
wide range of potential emergencies, including localized act or nature, accidents, technologies
and/or attack related emergencies
Annotation: A generally broad term used to define the ability to continue operations with
minimum interruption.
2. Possible ways to use the information from the reference term:
a. continuity - state or quality of being consistent, uninterrupted, or unbroken
b. continuity - state or quality of being consistent, uninterrupted, or unbroken; maintain
uninterrupted support to essential functions in spite of natural or man-made disasters; efforts
to assure continuance of minimum essential functions across a wide range of potential
emergencies, including localized act or nature, accidents, technologies, and/or attack related
emergencies
c. continuity - state or quality of being consistent, uninterrupted, or unbroken (Note: A
generally broad term used to define the ability to continue operations with minimum
interruption.)
d. continuity - state or quality of being consistent, uninterrupted, or unbroken; maintain
uninterrupted support to essential functions in spite of natural or man-made disasters; efforts
to assure continuance of minimum essential functions across a wide range of potential
emergencies, including localized act or nature, accidents, technologies and/or attack related
emergencies (Note: A generally broad term used to define the ability to continue operations
with minimum interruption.)
4 Addition and Revision Instructions
You may recommend including a term not currently listed in the DHS Lexicon, or request a revision to
an existing item, by emailing the DHS Lexicographer at [email protected] - DHS Lexicon term
addition or revision.
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2017 Edition – Revision 2 iv
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DHS Lexicon
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6 Supplemental Information
Supplemental information is provided for various terms by the Communities of Practice or others
supplying definitions to provide additional explanation for the definition.
1. DHS Organization Chart ........................................................................ Page 723
2. Homeland Security / Homeland Defense / Civil Support ...................... Page 724
3. Event Tree Information .......................................................................... Page 725
4. Fault Tree Information ........................................................................... Page 727
5. Indirect Consequence Information ......................................................... Page 729
6. Information Technology Information .................................................... Page 730
7. Intelligence Community Information .................................................... Page 731
8. Likelihood Information .......................................................................... Page 732
9. Normalized Risk Information ................................................................ Page 733
10. Probability [Mathematical] Information .............................................. Page 734
11. Relative Risk Information .................................................................... Page 736
12. Risk Information .................................................................................. Page 737
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EVENT TREE INFORMATION
1) Event trees use-forward logic; they begin with an initiating event and work forward in time to
determine the possible outcomes.
2) The probabilities used in event trees are conditional probabilities because they are based on the
assumption that the initiating event has already occurred. (See Probability annotation in the DHS
Lexicon for a description of conditional probability.)
As an example, consider Figure A. The initiating event is an Attack Attempted. From the initiating
event, the tree branches into a sequence of random variables, called events. The branching point at
which a new random event is introduced is called a node and is depicted by a circle.
The first of these random events is Personnel Action to Stop Attack. The Personnel Action to Stop
Attack is successful with probability 1-P
1
and fails to stop the attack with probability P
1
. If Personnel
Action to Stop Attack is successful, then the branch leads to the final outcome of Unsuccessful Attack,
No Damage (Scenario A). If Personnel Action to Stop Attack is not successful, then the branch leads to
the next node representing the random event of whether the Security Equipment to Stop Attack is
successful or not with probabilities of 1-P
2
and P
2
respectively. If the Security Equipment to Stop
Attack is successful then the branch leads to the final outcome of Unsuccessful Attack, No Damage
(Scenario B). If Security Equipment to Stop Attack fails then the branch leads to the final outcome of
Successful Attack, Damage to System (Scenario C).
Assuming that P
1
equals 10% or 0.1 and P
2
equals 30% or 0.3, then the conditional probabilities of a
Successful and Unsuccessful Attack, given that the initiating event occurs and an attack is attempted, are
calculated as follows:
Probability of Successful Attack given that an attack is attempted:
= Probability of Scenario C
= Probability that Personnel Action to Stop Attack fails and Security Equipment to Stop Attack
fails.
= P
1
× P
2
= 0.1 × 0.3
= 0.03
Therefore, the conditional probability of a Successful Attack, given the attack is attempted, is .03 or 3%.
Probability of Unsuccessful Attack given that an attack is attempted:
= Probability of Scenario A or Scenario B occurring
= Probability that Personnel Action to Stop Attack is successful or Security Equipment to Stop
Attack is successful
= (1 - P
1
) + [P
1
× (1 - P
2
)]
= 0.9 + (0.1 × 0.7)
= 0.97
Therefore, the conditional probability of an Unsuccessful Attack, given that the attack is attempted, is
.97 or 97%.
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Notice that the Probability of Successful Attack plus the probability of Unsuccessful Attack equals 1.0
because there are no alternative outcomes if an attack is attempted.
Event trees differ from fault trees by starting with an initiating event and moving forward in time to
determine possible final outcomes. Fault trees, as noted below, start with an outcome and work
backwards in time to determine the range of events that may have caused the outcome.
Attack Attempted
Success 1 - P
2
= 0.7
Personnel Action
to Stop Attack
Security
Equipment
to Stop
Attack
Final Outcome
Scenario A:
Unsuccessful
Attack, No
Damage
Success 1 -P
1
= 0.9
Failure P
1
= 0.1
Failure P
2
= 0.3
Scenario C:
Successful Attack,
Damage to System
Scenario B:
Unsuccessful
Attack, No
Damage
Figure A
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FAULT TREE INFORMATION
1) Fault trees use inductive (backwards) logic; they begin with a final occurrence and work backwards in
time to determine the possible causes.
2) A fault tree can be used to quantitatively estimate the probability of a program or system failure by
visually displaying and evaluating failure paths.
3) Fault trees can identify system components that lack redundancy or are overly redundant.
As an example, consider the diagram below. The final outcome, labelled here as Damage to System, is
shown at the top of the fault tree. All of the events that could lead to Damage to System are
diagrammed in the tree beneath the final outcome. Each event either does or does not occur, and the
events are interconnected by logical functions OR and AND.
Notice that one event that could result in Damage to System is if a Successful Attack occurs. Successful
Attack is one of the final states depicted in the Event Tree example. The occurrence of a Successful
Attack depends on: 1) an attack being attempted; 2) the failure of Personnel Action to Stop Attack;
AND 3) the failure of Security Equipment to Stop Attack. If the probability of an attack being
attempted is P
0
, then the probability of a Successful Attack is the probability that all three of these
conditions are met, equal to P
0
× P
1
× P
2
.
However, Damage to System can also occur if Natural Disaster occurs, which happens with probability
of P
3
. Assuming that P
0
equals 5% or .05, P
1
equals 10% or 0.1, P
2
equals 30% or 0.3, and P
3
equals
20% or 0.2, then the overall probability of Damage to System is calculated as follows:
Probability of Damage to System = Probability that Natural Disaster occurs OR Successful Attack
occurs, which can be calculated as follows:
= 1 - [Probability that Natural Disaster does not occur AND Successful Attack does not occur]
= 1 - [(1 - P
3
) × (1 – P
0
× P
1
× P
2
)]
= 1 - [0.8 × (1 - 0.0015)]
= 0.2012, or 20.12%
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Therefore, the probability of Damage to the System from all possible hazards is approximately
20%.
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INDIRECT CONSEQUENCE INFORMATION
1) Examples of indirect consequences can include the enactment of new laws, policies, and risk
mitigation strategies or investments, contagion health effects, supply-chain economic consequences,
reductions in property values, stock market effects, and long-term cleanup efforts.
2) Accounting for indirect consequences in risk assessments is important because they often have greater
and longer-lasting effects than the direct consequences.
3) Also referred to as ripple, multiplier, general equilibrium, macroeconomic, secondary, and tertiary
effects.
4) The distinction between direct and indirect consequences is not always clear but what matters in risk
analysis is a) capturing the likely effects—be they designated as direct or indirect—that should be part
of the analysis, b) clearly defining what is contained as part of direct consequences and what is part of
indirect consequences, and c) being consistent across the entire analysis. Such consistency and clarity is
important for comparability across scenarios and risk analyses.
5) Induced consequences, such as those consequences that stem from changes in household spending,
are occasionally estimated separately from indirect consequences but more often are contained within
indirect estimates.
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INFORMATION TECHNOLOGY
Information Technology (IT) equipment is used by DHS if the equipment is used by DHS directly or is
used by DHS organizational partners (including other federal agencies, state and local governments and
private contractors) under a contract with DHS which requires the use, to a significant extent, of such
equipment in the performance of a service or the furnishing of a product.
The term IT does not include any equipment that a contractor acquires incidental to a contract or any
equipment containing imbedded IT that is used as an integral part of the product, but the principal
function of which is not the acquisition, storage, analysis, evaluation, manipulation, management,
movement, control, display, switching, interchange, transmission, or reception of data or information.
For example, heating, ventilation, and air conditioning equipment, such as thermostats or temperature
control devices, and medical equipment for which IT is integral to operation, are not IT [Federal
Acquisition Regulation 2.101]. The Enterprise Architecture Board will review all IT investments,
including any investments categorized as non-IT on the OMB E300 but that contain IT components.
The term IT includes: computers; ancillary equipment (including imaging peripherals, input, output, and
storage devices necessary for security and surveillance); peripheral equipment designed to be controlled
by the central processing unit of a computer; software; firmware and similar procedures; services
(including support services); and related resources.
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INTELLIGENCE COMMUNITY
In the United States, the term ‘intelligence community’ includes the following:
(A) The Office of the Director of National Intelligence;
(B) The Central Intelligence Agency;
(C) The National Security Agency;
(D) The Defense Intelligence Agency;
(E) The National Geospatial-Intelligence Agency;
(F) The National Reconnaissance Office;
(G) Other offices within the Department of Defense for the collection of specialized national
intelligence through reconnaissance programs;
(H) The intelligence elements of the Army, the Navy, the Air Force, the Marine Corps, the Federal
Bureau of Investigation, and the Department of Energy;
(I) The Bureau of Intelligence and Research of the Department of State;
(J) The Office of Intelligence and Analysis of the Department of the Treasury;
(K) The elements of the Department of Homeland Security concerned with the analysis of
intelligence information;
(L) The U.S. Coast Guard Intelligence and Criminal Investigations Program (CGICIP); and
(M) Such other elements of any other department or agency as may be designated by the President,
or designated jointly by the Director of National Intelligence and the head of the department or
agency concerned, as an element of the intelligence community. [National Security Act of
1947, Sec. 3, para. (4), as amended.] The Intelligence Community was established by
Executive Order 12333, enacted on December 4, 1981, by President Ronald Reagan.
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LIKELIHOOD INFORMATION
1) Qualitative and semi-quantitative risk assessments can use qualitative estimates of likelihood such as
high, medium, or low, which may be represented numerically but not mathematically. Quantitative
assessments use mathematically derived values to represent likelihood.
2) The likelihood of a successful attack occurring is typically broken into two related quantities: the
likelihood that an attack occurs (which is a common mathematical representation of threat), and the
likelihood that the attack succeeds, given that it is attempted (which is a common mathematical
representation of vulnerability). In the context of natural hazards, likelihood of occurrence is typically
informed by the frequency of past incidents or occurrences.
3) Probability is a specific type of likelihood. Likelihood can be communicated using numbers (e.g. 0-
100, 1-5) or phrases (e.g. low, medium, high), while probabilities must meet more stringent conditions.
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NORMALIZED RISK INFORMATION
1) Typically, normalized risk divides the risk of each scenario by the sum of the risk across the set of
scenarios under consideration. For example, if you are considering the expected number of fatalities
from three different biological agents A, B and C, then the total risk posed by these biological agents is
the sum of the risk posed by each of them. If agent A has expected fatalities of 10,000, Agent B has
7,000, and Agent C has 3,000, then the total risk is 20,000 fatalities and the normalized risks are 0.5 for
Agent A, 0.35 for Agent B, and 0.15 for Agent C. This particular way of normalizing risk is commonly
referred to as “normalizing to 1” because now the risk from all the scenarios in the considered set sums
to 1.
2) Risk can be normalized by dividing by an existing sample space value. For example, if there are 100
car accidents this year and were 800 last year, then normalizing these values with respect to the total
vehicle trips each year permits a more appropriate comparison of the risk of last year versus this year. If
there were 10,000 vehicle trips this year then 100/10,000, or 1% of all trips ended in accidents. Whereas
if last year there were 100,000 vehicle trips then 800/100,000, or 0.8% of all trips ended in accidents.
Without normalization, it would appear that it was more risky to drive last year, but in reality, the
opposite is the case.
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PROBABILITY [MATHEMATICAL] INFORMATION
1) Probability can be roughly interpreted as the percent chance that something will occur. For example,
a weather forecaster’s estimate of a 30 percent chance of rain in the Washington, DC area is equivalent
to a probability of 0.3 that rain will occur somewhere in Washington, DC.
2) A probability of 0 indicates the occurrence is impossible; a probability of 1 indicates that the
occurrence will definitely happen.
3) Probability is used colloquially as a synonym for likelihood, but in statistical usage there is a clear
distinction.
There are many concepts in probability that are used regularly in the field of risk analysis. This
extension provides an elaboration on some of these concepts.
4) The probability that event A occurs is written as P(A).
5) Event A and event B are mutually exclusive if they cannot occur at the same time. For example, a
coin toss can result in either heads or tails, but both outcomes cannot happen simultaneously.
6) Event A and event B are statistically independent if the occurrence of one event has no impact on the
probability of the other. Examples of two events that are independent are the systems designed to
prevent an attack as described the Fault Tree example and Event Tree example. The probability that the
Personnel Action to Stop Attack is successful is not impacted by whether the Security Equipment to
Stop Attack is successful and vice versa. Two events that may not be independent are the collapse of a
bridge and the occurrence of a major earthquake in the area. Clearly the probability of a bridge collapse
can be impacted by the occurrence of a major earthquake. However, the two events may also be
independent; a bridge can survive an earthquake and a bridge can collapse in the absence of any
earthquake.
7) Conditional probability is the probability of some event A, given the occurrence of some other event
B, written as P(A|B). An example is the conditional probability of a person dying (event A) given that
they contract a pandemic flu (event B).
8) Joint probability is the probability of two events occurring in conjunction. That is, the probability
that event A and event B both occur, written as P(AB) and pronounced A intersect B. The probability of
someone dying from the pandemic flu is equal to the joint probability of someone contracting the flu
(event A) and the flu killing them (event B). Joint probabilities are regularly used in Probabilistic Risk
Assessments and Event Trees.
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9) Conditional and joint probabilities are related by the following formula:
P(A|B) = P(AB)/P(B)
If events A and B are statistically independent then
P(A|B) = P(A)
and the relationship above becomes
P(A) × P(B) = P(AB)
Consequently, for statistically independent events, the joint probability of event A and event B is equal
to the product of their individual probabilities. An example of the joint probability of two independent
events is given in the Event Tree example. If the probability that Personnel Action to Stop Attack fails
equals P(A) and the probability that Security Equipment to Stop Attack fails equals P(B) then
Probability of Successful Attack = P(AB)
= P(A) × P(B)
= 0.1 × 0.3
= 0.03 or 3%
as calculated in the Event Tree example.
10) Marginal probability is the unconditional probability of event A, P(A). It is the probability of A
regardless of whether event B did or did not occur. If B can be thought of as the event of a random
variable X having a given outcome, then the marginal probability of A can be obtained by summing (or
integrating, more generally) the joint probabilities over all outcomes for X.
Suppose for example, that event A is the occurrence of an illegal alien entering the country and X is the
random variable of where he entered the country. Then there are two possible outcomes of X: either he
entered through an official point of entry (event B), or he did not (event B’, pronounced B-not). Then
the probability of the person entering the country, P(A), is equal to the sum of the joint probabilities of
him entering by traveling through a point of entry plus the probability of him entering by not traveling
through a point of entry. P(A) = P(AB) + P(AB’). This is called marginalization.
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RELATIVE RISK INFORMATION
1) The relative risk value of a scenario is meaningful only in comparison to other similarly constructed
risk values.
2) Due to inherent uncertainties in risk analysis, relative risk may be more useful to decision-makers
than risk measured in expected annualized dollars lost or lives lost.
As an example, decision-makers may try to decide for which three biological agents they should invest
the most in mitigation or medication stockpiles. A risk assessment estimates that the absolute risk
measured in expected fatalities from the three different biological agents are 10,000 fatalities from
Agent A, 4,000 from Agent B, and 200 from Agent C. However, there is uncertainty surrounding these
values and decision-makers do not want to communicate the actual number of expected fatalities
because of security concerns. What the decision-makers ultimately need is the relative risk. The
relative risk of Agent B to C is 20 (4,000/200), and the relative risk of Agent A to C is 50 (10,000/200).
These relative risks tell decision-makers that Agent A has the highest risk of the three, 50 times that of
Agent C and 2.5 times that of Agent B.
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RISK INFORMATION
1) Risk is defined as the potential for an unwanted outcome. This potential is often measured and used
to compare different future situations.
2) Risk may manifest at the strategic, operational, and tactical levels.
3) Risk is a measure of the potential inability to achieve acquisition objectives within defined cost and
schedule constraints. It has two components: the probability of failing to achieve a particular outcome;
and the consequences or impact of failing to achieve that outcome. Risk management is a process of
developing an organized, comprehensive, and iterative approach to identifying, assessing, mitigating,
and continuously tracking, controlling, and documenting risk; it is tailored to each investment.
Investments are designated “high risk” through two routes:
(1) The assignment of the category by Office of Management and Budget per its memorandum
05-23, dated August 4, 2005, and
(2) Approval of the designation by the Milestone Decision Authority after review and
discussion, leading to the designation of a higher investment level for greater DHS scrutiny
and identification of the program risk. Two risk factors, the probability of failing to achieve
a particular outcome and the consequences or impact of failing to achieve that outcome, are
used to determine the priority (high, medium, low) of a risk.
4) Risk has two components, Risk Identification and Risk Management. Risk Management is an
iterative process that includes risk management planning, risk identification, risk analysis (quantitative
and qualitative), risk response planning (mitigation plan for risks with a probability of occurrence of less
than 100, and contingency plan for risks that have occurred [probability = 100; also known as issues]),
and risk monitoring and control. Typically, high priority risks receive the most attention and should be
escalated for senior management attention based on pre-determined criteria.
5) Risk is a function of the vulnerability of one or more assets when exposed to some hazard(s) or
threat(s) that has some likelihood of occurring and, in the case of a deliberate threat, some probability of
being successful.
6) The terms hazard, risk, and threat are often used as synonyms. The term risk is not interchangeable
with the terms hazard or threat, because hazards and threats are components of risk.
7) Risk can be measured and used to compare different future situations. There are numerous ways to
break down the components of risk for analysis, but risk is most simply and commonly expressed using
the equation risk = probability x consequences.
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