A Proposed Modeling Protocol

for Evaluating Information Attacks

by John H. Brand II

Approved for public release; distribution is unlimited.
.

The findings in this report are not to be construed as an official

Department of the Army position unless so designated by other

authorized documents.

Citation of manufacturer’s or trade names does not constitute an

official endorsement or approval of the use thereof.

Destroy this report when it is no longer needed. Do not return

it to the originator.
Army Research Laboratory

Aberdeen Proving Ground, MD 210055067

ARL-TN-112 Januarv 1999

A Proposed Modeling Protocol

for Evaluating Information Attacks

John H. Brand II

Information Science and Technology Directorate, ARL

Approved for public release; distribution is unlimited.
Abstract

The essence of an information attack is to alter, either by intrusion into and manipulation of

a database or by deception, the scenario under which a target mind or organization evaluates and

selects future courses of action. The aim is to influence the actions of the target. The method

is alteration of the perceived desirability or expected payoff of specific courses of action. This

alteration of the information in possession of the target can be described as alteration of the

perceived reality under which the target operates. Probable success by an attacker in altering the

target’s perceived behavior, given a successful manipulation of the target’s information, has, in

the past, been subjective. A modeling protocol based on the use of game theory is proposed that

may, in certain cases, allow optimization of the scenario, or reality, imposed on the target to

force the choice of a desired course of action. It should also allow a quantitative estimate of the

likelihood of the target’s adopting a given course of action. This tool can be used to estimate

friendly susceptibility to information attack.

.

ii
Table of Contents

1.

2.

3.

4.

5.

6.

7.

.................................................

.................................................

List of Figures . . . .

Problem . . . . . . . . .

Access ...........................................................

Decisions .........................................................

The U.S. Army Decision Process ......................................

Analysis of the Effects of the Attack ..................................

Further Work-The Next Step ........................................

References ........................................................

Distribution List ...................................................

Report Documentation Page .........................................

Pap;e

V

1

2

4

5

10

20

23

25

27

..*

111
.

biTENTIONALLY LEFT BLANK.

iv
List of Figures

.

Firmre parze

1.

2.

3.

4.

5.

6.

7.

8

9.

Sample Decision Matrix (From U.S. Army Command and General Staff

College [1989], Figure 4-7, p. 4-16) . . . . . ..*............................

Sample Decision Matrix (From U.S. Department of the Army [ 19971,

Figure S- 11, p. S-25) . . . . . . . . . . ..*.................*.................

Illustration of Factors Entering a Decision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Manipulation and Analysis of the Target’s Perceived Realities and Sets

of Courses of Action for Those Realities . . ..*0.......*...................

Determination of the Target Payoff Matrix 0*0*........*......*....*.*....

Target and Attacker Payoff Matrices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Manipulation of the Analysis of Courses of Action . . . . . . . . . . . . . . . . . . . . . . . .

Determination of the Target’s Strategy Mix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Determination of the Attacker’s Best Strategy Mix and Value of the Game . . . . . .

6

7

8

13

14

15

16

17

18
hTENTIONALLY LEFT BLANK.

vi
1. Problem

An information attack is a deliberate attempt to alter the reality perceived by an enemy. In the

past, the means used to attack a target’s information base were deception and persuasion. Persuasion

is as old as mankind. Military deception also has an ancient pedigree. The Hittites deceived

Ramses II outside the walls of Kadesh around 1286 BC and very nearly destroyed the Egyptian army.

The deception means used in that operation are not so very different from the means used in the

deception operations now routinely embodied in U.S. operations planning or embodied in the Soviet

doctrine of muskirovka.*

Deception is the progenitor of a more modem form of information attack, the deliberate and

direct alteration of databases, and, hence, perceived reality, by unauthorized entry into and

manipulation of computer systems. For the purposes of this paper, an in@mution attackis assumed

to include an attempted alteration of information in a target’s possession by any means, including

intrusion or deception.

In the past, a key question has been how likely is successful manipulation of a target’s actions,

given a successful information manipulation (information attack). This has largely been subjective.

The means of coping with the quantitative uncertainty in information manipulation has been the use

of whatever resources are available to make the desired course of action look so attractive it is

irresistible. A more quantitative means of analyzing and evaluating information attacks may now

be available. This is due largely to the increased use of computer-based decision and evaluation aids.

These decision aids, such as combat simulations, produce relatively reproducible quantitative results

and are driven by scenarios, or representations of reality, that are, in general, governed by

information or databases that are numerical in nature. If the input data can be deduced, stolen, or

forced, and the decision aids can be obtained, the numerical bases for decisions may be duplicated.

* Muskirovka is an elegant Soviet doctrine for controlling the actions of an opponent. It embodies what we call

“deception,” as well as electronic warfare and more. It is described in Glantz (1989). The historical material is related

to the present (then, 1989) in the last chapter. It is worth remembering that the Soviets trained people in their doctrine

who we will continue to encounter for a generation to come. For that matter, the Russian military seems unlikely to

abandon this elegant and successful doctrine.

1
Once the numerical bases for decisions are produced by the decision aids-gains or losses from

adoption of some given course of action-the decision process may in some cases be emulated. The

problem analyzed is the likelihood of successful manipulation of the target’s actions, given the

alteration of the information in the target’s possession. In other words, will the target do as the

attacker wishes?

2. Access

Analysis of the results of an information attack assumes the attacker has a great deal of access

to a target’s information and decision tools. It may be argued that one cannot just assume access to

the target’s decision process and information base, and in general this is true. However, a successful

information attack by intrusion into a computer system, whether by means of a network or by a file

manipulation through a delayed action attack such as “chipping*’ or a previously seeded virus,

requires access in order to occur at all.* In general, once in a computer system, the attacker has a

great deal of freedom of action, and most intrusions are not detected at the time, if ever. Given that

a successful intrusion occurs at all, thus permitting an information attack, the access of the attacker

is likely to be very great. Because of this, the access to the information necessary for analysis of the

effect of information attack by intrusion is assumed in this analysis as well.

The method of analysis may also apply to many deception operations, as well as intrusions.

Although deception operations can be launched with little or no access to a target’s information base

or reasoning process, the majority of successful ones appears to have been conducted with some,

usually much, access. Additionally, the most successful operations have been conducted through

reinforcing the preconceived expectation of the target, which required access to the thought

processes of the target to set the goal and to the reasoning processes of the target in order to reinforce

* “Chipping,” or building malicious code or circuitry into a chip, is not a new idea. Arthur C. Clarke described it in a

story, “The Pacifist,” in 1956 about a piece of circuitry s~~~~ptitiously inserted into a military tactical planning

computer. The story has been anthologized in Talesfrom the Whire Hart (Clarke 1957).

2
that notion.* It seems reasonable that some deception operations will involve the kind of access to

information and knowledge of the target to allow predictive methods to be used.

It can, therefore, be argued that in order for an information attack to be prosecuted successfully

access is a sine qua non. Without just such access, the attack will probably not occur at all.

Therefore, if the attack occurs at all, the conditions required for a predictive protocol may well, but

not certainly, be in place.

Assuming access, a protocol for evaluating the effect of information attacks may be formed from

the union of tactical combat modeling tools and classical operations research methods for selecting

the optimum course of action among several courses of action based on the expected gain or loss for

each. Interestingly, the more elaborate the analytical tools for decision making available to a force

(e.g., U.S. Army) are, the more predictable the actions of the force may be.

Interestingly, an evaluation protocol may only be useful given an information attack. In the past,

use of classical operations research methods to emulate decision processes has often been difficult

or impossible. There are simply too many free variables in the usual decision process. A good

example is shown in the discussion that follows, which illustrates a decision process using the

command estimate process. In the context of an information attack, however, the perceived situation

is simplified by the attacker.

No information attack is conducted with the aim of leaving freedom of choice to the target. The

target of an information attack is not left with options; the intent is to channel the target’s actions.

The target is intended to either follow one course of action only, or to be paralyzed, following none.

This implies the manipulation of information so that either one course of action is overwhelmingly

* This is demonstrated in the marvelous study, “Deception Maxims: Fact and Folklore” (Central Intelligence Agency

1980). As discussed in this study, an attack through conventional deception is most successful if it aligns with the

target’s preconceived ideas and expectations. It is also worth remembering that the great deceptions of WW II and

Vietnam were conducted with inside information from agents and broken codes in the former, and the news media

and hostile intelligence services in the latter. These allowed both information for initial planning and also constant

feedback on the success of the operation.

3
attractive, even if only by comparison, or no course of action is preferable to others, and none look

attractive at all. This simplification may allow the use of mathematical methods of evaluating the

likelihood of the target’s adopting the desired course of action that are impractical in the general

case.*

3. Decisions

Evaluating the most probable outcome of a successful information attack is difficult because it

involves evaluation of the outcome of manipulation of perceptions on a decision. As stated

previously, this study assumes that the information has already been successfully transferred or

altered, and the goal is to assess the actual impact of the successful information manipulation on the

manipulation of the target’s actions. As stated previously, the information manipulation can be by

deception, intrusion, or some other means.

For situations where a logical analysis is used by a target decision-making entity to determine

courses of action, the application of game theory or other related disciplines such as linear

programming might lead to predictive insight.+ The prototypical case would be a military force led

by individuals with formal training in some analytical staff methodology, such as U.S. battle staffs.

Likewise, an attacker’s own trained general staff might be increasingly vulnerable to being foxed in

turn. The method might be open, with reservations, to application to economic cases as well.

* In the general case, evaluating the probable reactions of a target, given little or no knowledge by the attacker of the

target’s knowledge of the situation, and in ignorance of the target’s values and thought processes, is a task best left

to intuition. Unfortunately, in many cases this is the only real avenue. For many people, especially the violent

personalities likely to seek, gain, and maintain power in the Third World, emotion is king. Reason is at best a

distantly related handmaiden. Curiously, cases that are subject to analysis seem more likely to occur in targets that

are better educated and better trained than in cases such as a criminal without formal training, or an emergent popular

leader. Many “popular” leaders, of course, are quite rigorously trained by some hostile nation state.

’ Zero-sum game theory and linear programming (LP) problems may be expressed in either formalism. This is

extremely convenient, as LP software is easily available. The relationship between the two formalisms is described

in Bennion (1960).

4
4. The U.S. Army Decision Process

The formalism used by U.S. Army battle staffs is illustrated in two examples of a sample

decision table from the G3 (operations) planning process. The first (Figure 1) is taken from the

Command and General Staff College (CGSC) text on the command estimate process (U.S. Army

Command and General Staff College 1989): The second (Figure 2) is reproduced from the newly

revised manual on staff operations (U.S. Department of the Army 1997).+ The “school solution”

illustrated in the text is paper-and-pencil based; field units now use sophisticated combat and

logistical simulations, but the basic logic applies. Several observations are in order.

Jn this process, a mission statement leads ultimately to the determination of possible courses of

action: “attack with three battalions here, defend with one here, a barrier here . . .” These are

formulated, evaluated by war gaming, and the decision is made in the light of war game results

conducted under a given scenario, or perceived reality. In the general case, individually chosen and

weighted factors enter the decision process. This is illustrated in Figure 3. If that reality is tailored,

then the determination of possible courses of action and the estimate of the value of the courses of

action will be altered also. The perceived relative merit of a course of action is thus determined,

based on the factors considered important by the commander. As can be seen in the example, which

is only one of many staff decision matrices, without simplification or channeling of the decision, the

judgmental factors make predictive methodologies themselves highly judgmental, unless the basic

perception of the situation is manipulated or accessed in some way. That is, however, the essence

of an information attack.

In the absence of manipulation, the analysis and selection of courses of action, the war gaming

of the courses of action, and the formulation of the decision matrix are highly subjective and full of

free variables. The process must be simplified or channeled in some way. This can be by

With the embodiment of the methodology of this ST in the latest revision of FM 101-5 (U.S. Department of the Army

1997), the text will presumably be revised.

The May 1984 edition did not incorporate this excellent material.

5
COURSES OF ACTION’ Note that the subsidiary factors do

not dominate the decision: all the

courses of action have decent C2,

etc. The driving factors in this

case are two: “surprise” and

“speed.” Furthermore, if, for

instance, an attacker left “surprise”

out of a prediction of the target’s

actions, the relative rank based on

“speed” alone would not change

from the example shown.

Decisions based on “speed” are

driven by factors such as Tables 4-

2 and 4-3, “Unopposed rates of

movement”--predictable.

Figure 1. Sample Decision Matrix (From U.S. Army Command and General Staff College [1989], Figure 4-7, p. 4-16).
CRITERIA ‘WI-

(note 1) (note 2)

COA

1

(note 3)

COA COA

2 3

(note 3) (note 3)

Maneuver 3 2 3 1

(6) (9) (3)

Simplicity 3 3 1 2

(9) (3) (6)

Fires 4 2 1 3

(8) (4) (12)

Intelligence 1 3 2 1

(3) (2) (1)

ADA 1 1 3 2

(1) (3) (2)

Mobility/

Survivability

CSS

1 3 2 1

(3) (2) (1)

1 2 1 3

(2) (1) (3)

C’ 1 1 2 3

(1) (2) (3)

Residual

Risk

c2w

TOTAL

Weighted TOTAL

I 2 1 2 ’ 3

(2) (4) (6)

1 2 1 3

(2) (1) (3)

20 18 22

(37) (31) (40)

NOTES:

1. Criteria are those assigned in Step 5 of the war-gaming process.

2. Should the CofS/XO desire to emphasize one as more important than another, he assigns weights to each

criterion based on relative importance.

3. Courses of action are those selected for war gaming.

Procedure: The staff assigns numerical values for each criterion after war-gaming the COA. Values reflect the

relative advantages or disadvantages of each criterion for each COA action. The lowest number is best. The initially

assigned score in each column is multiplied by the weight and the product put in parenthesis in the column. When using

weighted value, the lower value assigned indicates the best option. The numbers are totaled to provide a subjective

evaluation of the best COAwithout weighing one criterion over another. The scores are then totaled to provide “best” (lowest

number value) COA based on weights the commander assigns. Although the lowest value denotes the best solution, the

best solution may be more subjective than the objective numbers indicate. The matrix must be examined for sensitivity.

Although COA 2 is the “best” COA, it may not be supportable from a CSS standpoint. The decision maker must either

determine if he can acquire additional support or if he must alterordelete the COA.

Figure 2. Sample Decision Matrix (From U.S. Department of the Army [1997], Figure 5-11,

p. 5-25).

7
1 mission 1

1

v

courses of action

*ground gained

weighting I’actors *LER _. .;:..:..; _,;,, __::::.-.-- * ..li::;-’ \ acasualties

Weighting factors are arbitrary factors that decrease

.

predictability unless they can be C.ol7lP1.O17li.Vecl,

tlccluc~ecl, or-.forcecl by political or social factors OIhy s~~cc~essf~rl in.fbt-tncrtion ut~nck.

~:;;;;::::::::::::::‘:~~~~-‘~ . . . . . . . . p&iZGZ-Figuves

P

Figures of merit are arbitrarily chosen and decrease

predictability unless, like the weighting factors, they

can be cot711~Y.ot11i.~ecl, clecl~.tcecl, ot-~fot-red by political

+I

I

or social factors ot- by .s~~cce.ssful itl,fbt-mutiot7 rrrtcrck.

Arguably, for 30 years U.S. figures of merit have

increasingly revolved around the goal of 110 c.~r.s~inlfies.

Slide 5

6 January 98

Figure 3. Illustration of’ Factors Entering a Decision.
external pressure (e.g., the media) or by compromise of the decision algorithm. The judgment

factors are then transparent to the attacker. The selection of the courses of action in the general case,

therefore, is not amenable to analysis with game theory or its cousins, though a judgment evaluation

may be aided considerably by combat simulations run and evaluated with the target’s decision

methodology.

The decision matrix from FM 101-5 (U.S. Department of the Army 1997) is now a rank-ordered

rating.* This may decrease the impact of initial conditions in the combat simulation used to generate

figures of merit. Note that in this example, as in the previous case, a factor dominates the decision.

This cannot be relied on in the general, unmanipulated case, even though present in the example.

An additional observation about this example is that, if the miscellaneous nondominant factors such

as combat service support are ignored in this matrix, the decision does not change. This is because,

in general, bad plans are not made deliberately. Good alternative courses of action are all

supportable, all have decent fiie support, etc.

If real battle staffs perform like the textbook examples, some key attributes will likely be the

deciding factor, picked out by the weighting functions. In fact, it can be argued that U.S. planning

has become more dependent over the last 30 years on a single, overriding imperative: low casualties.

If two or more factors should dominate, however, the protocol can also be followed for each factor,

and the course of action selection by the target estimated based on the agreement of the protocol for

all the factors for a single course of action. If the answer does not converge in this way, the assumed

manipulated reality is inadequate to channel actions with any certainty. The scenario should be

altered and the analysis performed again to fmd an unambiguous answer.

* In passing, the new school solution with forced choice rank ordered rating may meet some resistance. The method

artificially enhances differences between choices of action where there may, in fact, be little or no real difference.

It also de-emphasizes differences where there may be substantial differences. For instance, two courses of action may

be identically supportable in terms of ton-miles, but one is forced to be rated better than another (1 vs. 2). One may

produce three times the casualties of another, but the better is rated as merely better (1 vs. 2) rather than three times

as good as the other. The older method accounted for these problems.

9
The most important thing to glean from the discussion of gaming of courses of action in the text

is that the gaming approach outlined in ST 100-9 (U. S. Army Command and General Staff College

1989) is essentially a zero-sum decision. That is, one side gains according to some measure; the

other side loses. For example, the measure may be ground gained or casualties. One side gains

ground; the other loses it. One side loses men and vehicles; another side gains kills, and so on.

Mathematically, the application of non-zero-sum theory is more appropriate, but as of now, the

doctrinal approach is simpler. Perhaps with the increasing use of more complicated simulation tools,

that will change. The attacker is, of course, not only well aware of the difference in goals and the

disparity of values, but in this scenario has acquired the necessary predictive tools to generate them.

Non-zero-sum game theory is thus essential for the attacker’s decision, but not needed for the

attacker’s evaluation of the target’s decisions.

It should be noted that, in the absence of an information attack or detailed inside information,

the problem may still be analyzed, but with less confidence. With only the information in either of

these two example decision matrices, a prediction can be made, but game theory is not adequate for

the prediction. The necessary payoff matrix cannot be filled out. The decision process can likely

be emulated, however, if the combat simulation used by the target to calculate measures of

effectiveness can be used to fill out a likely payoff matrix that the attacker feels is consistent with

the target’s values and past judgement. The intermediate steps in the war-gaming process are

necessary. Given those, a payoff matrix the attacker feels is similar to what the target would

generate can be filled out and an estimate made using the formalism of game theory, which should

emulate the judgment call of the staff.

process should be at least indicative.

The fidelity of the emulation cannot be guaranteed, but the

5. Analysis of the Effects of the Attack

As mentioned, the basis of the attack is the manipulation of a perceived reality in such a way that

the problem is simplified and analyzed with the appropriate decision aids to generate payoff

.

10
matrices. One question that must be addressed is, “How robust are combat simulations under

different initial scenarios, or perceived realities?”

Higher-level headquarters have increasingly sophisticated combat and logistic simulation tools

available, with output that may or may not be believable in absolute terms. The output is usually

regarded as at least consistent. That consistency is important. Although one may not have a lot of

confidence in the probable absolute accuracy of a given prediction of a measure such as casualties,

the accuracy of the relative results of two courses of action seems reasonably well founded by

experience with combat simulations. That is, the casualty ratios in two “battles” that are

subsequently “fought” in a combat simulation will likely be reasonably accurate, but the actual

values of the casualties predicted by a given simulation using historical data as the scenario may

differ substantially from the real battle. Thus, at least for the game theory formalism, the strategy

mix should be robust, but the value ofthe game (wins or losses) will be altered by any multiplicative

factor that relates the war game results to real battles.

The strategy mix is the determining factor for prediction of the selection of a course of action,

and should be robust within a given simulation, although the value of the game might be less so.

That is, an information attack should increase the probability of a course of action so that it

dominates the strategy mix, and the others have low probabilities. The value of the game is

important in estimating whether the target may be induced to act at all. This is important in

analyzing an attack aimed at paralyzing the target. Such an attack should aim at no course of action

predominating, and the value of the game being so poor that action is not taken.

The outcome of a given course of action also depends on what an enemy might do. That is,

course of action i might have outcomes j depending on how the enemy reacts. This immediately

suggests a rectangular payoff matrix, and the formalism of a decision optimization discipline such

as game theory or, for the zero-sum case, linear programming. The discussion in this report is based

on the formalism of game theory. This is because, although there is an extensive and mature

analytical discipline of optimization of courses of action (linear programming is one methodology),

the writer is more familiar with the game theoretical formalism than the others, and the game

theoretical formalism extends to the non-zero-sum case.

11
Once a payoff matrix is generated, game theory allows determination of the optimum mix of

strategies. That is, for a player playing the same game many times, independently of previous

results, choice of strategy can be made randomly within the probabilities in the strategy mix. That

is, the formalism of evaluation of an m xp payoff matrix, corresponding to m friendly courses of

action and p enemy courses of action, allows the determination of a series of probabilities for the

optimum mix of the m friendly courses of action. If the game were played according to the optimum

strategy mix, and the individual strategies in the strategy mix were randomly selected according to

those probabilities, the outcome would be optimal. This is also the expected outcome of an

evaluation process by a good staff and commander. Indeed, the long-term payoff, the value of the

game, can also be determined from the payoff matrix.* As stated previously, the goal of an

information attack would be to alter the reality that produces a perceived payoff matrix so that either

action is paralyzed (no strategy predominated in the strategy mix, or all look about equally likely,

and the value of the game is bad) or a single strategy predominated the mix (action is channeled).

One problem is that an attacker, unless a graduate of the American staff system, is unlikely to

evaluate his or her courses of action in the same way or to choose the same figures of merit. That

is, his or her payoff matrix may be considerably different. This is especially so if the chosen figure

of merit is radically different from U.S. usage; an enemy may be completely indifferent to casualties,

or even desire them for their effect on the media or the U.S. intelligentsia. This leads to the necessity

for two sets of payoff matrices-one based on the U.S. methodology and figure of merit, and another

based on both that payoff matrix and the hostile methodology and figure of merit. This dual-entry

matrix, by the way, automatically requires the methods of non-zero-sum game theory.

The generation of the set of target payoff matrices based on the alternate realities that may be

forced on the target by the attacker is illustrated in Figures 4-9. This first step is to generate the set

of alternative courses of action that the target and attacker might use, under all the proposed

perceived realities, shown in Figure 4. The use of the target’s evaluation method to determine the

attractiveness of a course of action under the supposed conditions of a perceived reality is illustrated

* As discussed previously, a complication is the fact that a given battle or conflict is not truly a zero-sum game, although

decisions in combat often are. l%is simple outline is based on the assumption of a mix of zero-sum and non-zero-sum

decisions, depending on by whom and why the decision is made.

12
Consider a battle staff formulating alternative courses of action and then

gaming them to obtain relative value.

(base case)

course of action 4

I course of action 6

I

course of wtion 1

co&se of action 4

i ,.

izourse of action 5

course of action 6

Slide 8

20 October 97

Figure 4. Manipulation and Analysis of the Target’s Perceived Realities and Sets of Courses of Action for Those Realities.
P

Perceived

Reality 1:

target decision based on a zero sum approach:

Payoff matrix for perceived reality l? M, =

Al,, Al,2 Al,, Al II -.-..

AL, AL2 Ahi A124....

7 Figures of merit Al ,,, Al ,?, Al ,I, Al 14”. ...

Likewise, figures of merit A12,, A L2, Al,,, A124r....

-

Figure 5. Determination of the Target Payoff Matrix.

r

16
I I I I

I -

target’s

perceived i---A target’s stm tegy nxx ST0 I

1 payoff matrix M, 1

target’s

perceived I--+ target’s strategy mxx ST,

1 payoff matrix M, 1

, ,

1 I

target’s

perceived

payoff matrix M;

target’s b

strategy m.kx ST,

Figure 8. Determination of the Target’s Strategy Mix.

in Figure 5. As mentioned previously, if the situation cannot be simplified to a single, dominating

factor, the analysis can be run for each factor and the tar,oet’s selection guged on the basis of

whether the course of action desired by the attacker looks attractive to the target according to each

factor. If it does not, the target has an ambiguous choice and the attacker must change the scenario

of real i ty.

17
a
The different courses of action are war gamed, using the target’s war-gaming method, under the

conditions pertaining to the perceived alternate views of reality or scenarios chosen by the attacker,

to determine what value the target would assign to a given course of action. The result is a series

of payoff matrices, one for each scenario or perceived reality.

It seems at this point that the matrix for each perceived reality must include values assigned to

each course of action in the consolidated list of courses of action across all perceived realities. If a

given course of action really is not appropriate for a given perception of reality, no harm will be done

as its payoff would be very poor, and its chance of being invoked in a strategy mix minuscule.

The attacker must then determine the payoff from the attacker’s own point of view. This is

illustrated in Figure 6. The attacker strategy mix for each possible perceived reality can then be

determined from the non-zero-sum payoff matrix formed from the perceived values for target and

attacker under that reality. It is important to remember that the target values are based on a target

style war game under the conditions of the perceived reality, and the attacker values are generated

by use of an attacker style war game based on the ground truth reality. This process is illustrated in

Figure 7.

The likelihood of a target staff and commander adopting the desired strategy can then be

estimated, the alternate reality adjusted if necessary, and the process run again. This determines the

desired form of the alternate reality, facilitating planning of an integrated information attack with,

for instance, military deception, manipulation of the press, and possibly covert manipulation of

databases. The value to the hostile strategist can then be estimated based on the hostile methodology

for evaluating courses of action, with the difference in the uncontaminated reality vs. the adjusted

reality clearly delineated. This is illustrated in Figure 8.

Also illustrated in Figure 8, a successful analysis can indicate which reality is most likely to yield

the target’s adoption of the course of action desired by the attacker. The strategy mix determined

for the target by the target’s analytical methodology indicates the probability of the target actually

adopting a given course of action within that reality. If the desired attacker goal is paralysis, the

19
strategy mix should end up with all courses of action having about the same probability, and the

value of the game, to the target, appearing really poor. If the desired goal to the attacker is for one

strategy or course of action to be the most likely choice, the strategy mix will indicate a high

probability for that strategy or course of action, and the value of the game will be such as to induce

action.

These are likely to be relatively robust as long as the relative outcome between two or more

strategies in a combat simulation or other analytical method is reasonably believable, but less

confidence can be invested in the computed value of the game. The attacker may then use

non-zero-sum game methods to compute the optimum strategy mix, illustrated in Figure 9.

An interesting question poses itself at this point. A reasonable information attack would almost

certainly not be a one-shot deal, aimed and fired like an unguided missile. The attacker would very

likely monitor the progress of the attack and continue to feed the preconceptions by a deception

operation or further intrusion, or both. Historically, at least in deception operations, the target has

been fed substantiating information right along. The target will also be systematically looking for

confirmatory information as the operation continues by targeting key areas for reconnaissance, and

so forth, which should be provided. Whether it is desirable to risk the information attack by further

deception or by continuing access through further intrusions and manipulations is an interesting issue

that is beyond the scope of this report.

6. Further Work-The Next Step

The protocol is tried out next. For simplicity, a single means of war-gaming is used. This may

be the manual war game method or use of the Modular, Semi-Automated Forces (Mod&IF) model.

Mod&W is highly desirable, but manipulation of the scenario using Mod&W may not be practical.

The great merit of ModSAF, however, is that the operator can fight a poor battle under the conditions

of ground truth. The poor battle under the ground truth is the battle corresponding to a course of

action that seems desirable under a perceived reality. The difficulty lies in changing the scenario

20
enough to obtain different, distinguishable realities. These variations on the basic scenario are

essential for evaluation of the course of action under the presumed conditions of the perceived, but

false, realities imposed on the target during a successful information attack. A useful method may

be to alter the input tables for a key parameter such as trafficability. This also has the merit of being

the kind of alteration an information attack might exploit.

When the zero-sum payoff matrices are generated, the game will be recast as a linear

programming problem and the matrix solved using any standard linear programming package. The

means of solving the non-zero-sum game is not yet determined. There does not appear to be a

general solution (Vorob’ev 1971), although there are approaches that may suffice.’ However, the

information and method asymmetry in an information attack may allow for a simplification that

permits a solution.

The normal discussion of non-zero-sum games assumes equal knowledge of the payoff to both

sides, and a common methodology. That is, both are playing the game. In fact, the game is very

different for attacker and target. A successful information attack that channels action will reduce the

freedom of action of the target to one course of action. This will be a I xp game, which should be

easier to analyze. This is so because the choice of courses of action by the target is assumed to be

based on zero-sum reasoning; hence, the target choice of action can be easily analyzed. The assumed

reality is also assumed to be structured so that the choice of courses of action by the target can be

assumed to be degraded to a single choice. This yields an attacker payoff matrix with one row. If

it is not, the protocol must be repeated with a different set of scenarios, or perceived realities, until

the attacker’s choice of target strategies dominates in the target strategy mix. The attacker is then

free to select his or her own strategy based on maximizing gain for the attacker, or inflicting

maximum hurt on the target, or some mix. Note that this essentially converts the two independent

payoff values into some utility function, resulting in a simple choice of maximizing or minimizing

components of a vector.

* The first,try will use the method outlined on pp. 213 and 214 of The Cornpleat Strutegyst (Williams 1954), one of a

RAND series. One assumes both sides are playing against a neutral mother nature.

21
If the attacker is indifferent to whether the target chooses one or many courses of action, the

problem becomes much more difficult. The strategies can be examined for strict dominance and an

equilibrium point sought, but the solution is not clear in the general case. A geometrical approach

may work in some cases.*

A further step to aid this analysis might be the construction of a stochastic model of computer

network models. This would describe a net in terms of numbers of elements, type of security, and

known historical probabilities of successful intrusion through poor security practices, etc. Whether

this type of model would be useful is unknown at this time, but it would allow estimation of

likelihood of successful intrusion without the use of detailed engineering models, which is the only

method now available. A generalization such as this would also allow for historical data on factors

such as inadequate training and carelessness, which are difficult to build into an engineering model

but are always present.+

It is proposed that a survey of the various means of evaluating courses of action used by friendly

and possible enemy decision entities (staffs) be conducted, and, if enough information can be

gathered, the result of an information attack be played out for some limited scenario. A sensitivity

analysis should be conducted to determine whether this methodology is indeed robust to

uncertainties expected in realistic cases. This will require a team approach, the content to be

determined by the elaboration of the demonstration involved.

* This procedure is discussed exhaustively in Games and Decisions (Lute and Raiffa 1957). lhe geometrical

representation approach mentioned is illustrated on pp. 93ff.

’ For example, the choice of passwords can be an obvious weakness. Historically, a large fraction of passwords are

chosen in such a way that they are cracked relatively easily. Thus, some proportion of attempted access might be

assessed as having encountered a password that can be cracked in a shorter time than in other cases. This likelihood

can be also parameterized in terms of the type of net that is attacked: commercial nets might not have password

strength checking routines and password aging; tactical nets almost certainly will.

22
7. References

U.S. Army Command and General Staff College. The Command Estimate. ST 100-9, Fort

Leavenworth, KS, July 1989.

,

U.S. Department of the Army. StujfOrganization and Operations. FM 101-5, Washington, DC,

May 1997.

. Bennion, E. G. Elementary Mathematics of Linear Programming and Game Theory. Ann Arbor,

MI: Michigan State University, 1960.

Central Intelligence Agency. “Deception Maxims: Fact and Folklore.” Deception Research

Program, Office of Research and Development, Washington, DC, April 1980 (ADB 199481).

Clarke, Arthur C. “The Pacifist.” Tales From the White Hart, New York: Ballentine Books, 1957.

Glantz, D. M. Soviet Military Deception in the Second World War. London: Frank Cass, 1989.

Lute, R. D., and H. Raiffa. Games and Decisions. New York: John Wiley and Sons, 1957.

Vorob’ev, N. N. The Development of Game Theory. Translated by Erika Schwoediaver, Working

Paper No. 2, Department of Economics, New York University, August 1971.

Williams, J. D. The Compleat Strategyst. New York: McGraw Hill, 1954.

23
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REPORT DOCUMENTATION PAGE Fomn Ap/woved

OMB No. 0704.0186

bubllc ~WXU~O bwda lor this cokUOn of InfonnNlOn IS &a&d to rWnga 1 hour pr rrp~nw, ineludl~ the Urns for mlrrrl

wihWn0 and malntalnlng the data nandad. md 00mplaUng md wkwing the colluUori ol Inlonnmlon. Sand commnb r#&jmdng thla bwh @hiMa ai MY 0th~ npacttz

ng ranlcuo~, Mmhlng *xhting data

COIIOCUO~ of Infom~ailon, lneludi

2182040 6U-6UOl

P611102.H48 *TRPlO

BFTAO S18129

John Brand II

REPORT NUMBER

U.S. Army Research Laboratory

A’ITNz AMSRL-IS-T ARL-TN-112

Aberdeen Proving Ground, MD 21005-5067

B. SPONSORING/MONITORING AGENCY NAMES(S) AND ADDREBS(ES) lO.SPONSORING/MCjNITORlNG

AGENCY REPORT NUMB’ER

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4pproved for public release; distribution is unlimited.

13. ABSTRACT(hlaxlmum 200 words)

The essence of an information attack is to alter, either by intrusion into and manipulation of a database or by

deception, the scenario under which a target mind or organization evaluates and selects future courses of action. The

aim is to influence the actions of the target. The method is alteration of the perceived desirability or expected payoff ot

specific courses of action. This alteration of the information in possession of the target can be described as alteration d

the perceived reality under which the target operates. Probable success by an attacker in alterhrg the target’s perceived

behavior, given a successful manipulation of the target’s information, has, in the past, been subjective. A modelin8

protocol based on the use of game theory is proposed that may, in certain cases, allow optimization of the scenario, OI

reality, imposed on the target to force the choice of a desired course of action. It should also allow a quantitative

estimate of the likelihood of the target’s adopting a given course of action. This tool can be used to estimate friendly

susceptibility to information attack.

14. SUBJECT TERMS 15. NUMBER OF PAGES

30

information warfare, game theory, linear programming 16. PRICE CODE

17. SECURITY CLASSlFlCATlON 18. SECURITY CLASSlFlCATlON 19. SECURITY CLABSlFlCATlON

OF REPORT

29. LIMITATION OF ABSTRACT

OF THIS PAGE OF ABSTRACT

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