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% This is based on the LLNCS.DEM the demonstration file of
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\begin{document}
\title{An Adversarial Risk-based Approach to Embedded Systems Security Modeling and Design}
%
\titlerunning{Adversarial Risk-based Security Modeling} % abbreviated title (for running head)
% also used for the TOC unless
% \toctitle is used
%
%\author{Paul Wortman \and John A. Chandy}
%
%\authorrunning{Ivar Ekeland et al.} % abbreviated author list (for running head)
%
%%%% list of authors for the TOC (use if author list has to be modified)
%\tocauthor{Ivar Ekeland, Roger Temam, Jeffrey Dean, David Grove,
%Craig Chambers, Kim B. Bruce, and Elisa Bertino}
%
%\institute{University of Connecticut, Storrs CT 06269, USA}%\\
%\email{I.Ekeland@princeton.edu},\\ WWW home page:
%\texttt{http://users/\homedir iekeland/web/welcome.html}
%\and
%Universit\'{e} de Paris-Sud,
%Laboratoire d'Analyse Num\'{e}rique, B\^{a}timent 425,\\
%F-91405 Orsay Cedex, France}
\maketitle % typeset the title of the contribution
\begin{abstract}
%AADL is a common use language that has been developed and tweaked over the years to allow the ability to
%describe model behavior and specifications, with more recent attempts to define language for security
%requirements and verification. This paper examines previous implementations of behavior, requirements, and
%security in AADL and then goes to propose a new framework for better integration and description of security
%requirements and behavior within the AADL lexicon.
Embedded systems design and verification has become more complicated as aspects of security need to be included
in examinations. The obvious implications of adding security are the need to account for impacts of
loss (risk) and accounting for the ensuing increased design costs. The considerations that are not
traditionally examined are those of the adversary and the defender of a given system. Without accounting for
the view point of the individuals interacting with any secure embedded system design, one can not verify and
select the most advantageous security design.
\keywords{security modeling, security framework, secure system design}
\end{abstract}
\section{Introduction}
%AADL, like most modeling languages, must be able to describe not only the requirements of a system, but also the constraints, capabilities, and costs of various implementations and methods for the purpose of modeling a gamut of different designs. Coupling this already large space with security causes the considerations and influences on the problem to grow considerably. This paper will choose to examine the field of modeling embedded system security through the lens of the Architecture Analysis \& Design Language (AADL).
Modeling security risk for use in systems design is a difficult problem that has not been thoroughly explored. To properly model security one has to account not only for the security requirements being imposed by a user, or organization, but also must account for the architectural components and their capabilities when designing a best-fit solution to a given security concern. The security requirements can range from such vague concepts as ``my data must remain secure'' to more concrete requirements of ``this specific communication standard must be used''. Each requirement is capable of being implemented in a variety of manners and methods. These differences are further defined by the architectural components and their capabilities. Elements ranging from time spent to complete a given task, power consumption rate, heat radiated over time, and size, or area, that a given component will require on a printed circuit board (PCB). To further complicate matters, one must take these opposing aspects of the system design process, represent them using meaningful metrics that can be calculated from some deterministic information, and then compare and contrast generated solutions for implementing the most favorable variation of produced embedded systems security model. Fortunately there are
methodologies and techniques %(e.g. Platform Based Design)
that aid in the development and improvement of security modeling approaches. For example, Platform-based design~\cite{Vincentelli2007} is a prime example of how one can take the functional space (including security requirements) and the architectural space (components and capabilities) and develop a mapping function that can produce solutions to a given design problem. As shown in Figure~\ref{fig:recursivePBD}, one can then take the mapped solution and use this as the new functional (or architectural) space for the next iteration of solution mapping.
\begin{figure}
\includegraphics[width=\textwidth]{./images/recursivePBD.png}
\caption{Visualization of Recursive PBD Model~\cite{Vincentelli2007}}
\label{fig:recursivePBD}
\end{figure}
In order to use a design process such as this, we need to be able to have metrics that are able to evaluate the quality of a design solution in relation to the quality of other possible design solutions.
How does one begin to place metrics on an arbitrary measure like security risk? Risk is generally treated as a probability that an event will occur. To define risk from an embedded systems security modeling standpoint, one must first determine how to define risk in a meaningful manner, and how to then apply this metric to the situation that involved said `security risk' (more on this topic will be explored in Section~\ref{sec:riskDefinition}). Quantitative aspects of security will be relatively simple to incorporate with risk calculations. How does one define qualitative aspects of security? One method that can be used to assign a quantitative value to a qualitative property is to use a relative ranking system to scale all available
solutions from a 0.00 -{}- 1.00 scale as explored by Ferrante et.~al.~\cite{Ferrante2013}.
First this paper will need to develop a verification and selection process for taking all of the cataloged information and possible solutions \& compare and contrast solutions that meet user-defined security requirements while categorizing solutions that are maintaining within external constraints and the capabilities of the architectural components being used to produce a best fit; measured by this paper's verification and selection process (Section~\ref{sec:riskDefinition}. To begin this approach, one will first need to define the constraints of the system, describe the considerations that must be taken into account, and standardize a method by which an individual can produce a comparable metric for generated embedded system security model designs (Seciton~\ref{sec:framework}). In the following Sections, this paper will produce examples of the verification and selection process (Seciton~\ref{sec:simpleExample}), then expand the discussion to include additional considerations (e.g. physical, adversarial). Lastly the paper will speak to some last, larger, considerations followed by the conclusions and future work towards producing an adversarial risk-based approach to embedded systems security modeling.
%\section{Motivation and Related Work}
%Work has been made to describe behavior, errors, some security properties in terms of verification and validation within the AADL language. These developments have occurred in a variety of annexes, most recently the security annex extensions and alterations that have been occurring throughout the summer of 2016~\cite{AADLSecAnnex,AADLSecAnalysis}. Attempts are always being made to improve AADL and incorporate more in the description and detail of the language. Recent work includes the definition of specific security-based properties, ranging from `AccessProteciton' to security level definitions to even such extensive work as defining all the different aspects of encryption (shown in Listing~\ref{lst:AADLSecEncryption}).
%
%\begin{lstlisting}[caption={AADL Security Annex Definitions of Encryption~\cite{AADLSecAnnex}},label={lst:AADLSecEncryption}]
%encryption : security_properties::encryption_type applies to
% {port, virtual bus, bus, memory, access};
%encryption_type : type record (
% method : security_properties::supported_encryption_method;
% algorithm : security properties::supported_encryption_algorithm;
% public_key : aadlstring;
% private_key : aadlstring;
% key : aadlstring;
% operation_mode : security_properties::supported_operation_mode;
%};
%supported_encryption_method :
% type enumeration (symmetric, asymmetric, clear);
%supported_encryption)algorithm :
% type enumeration (tripledes, des, rsa, blowfish, aes, clear);
%supported_operations_mode :
% type enumeration (ecb, cbc, pcbc, cfb, ofb, ctr);
%\end{lstlisting}
%Current language standards used to describe security concepts, requirements, and constraints has not been developed well enough to be `all-encompassing'. Recent AADL extensions to the security annex describes the security aspect of `trust' as a non-binary value, which this paper sees has not an accurate reflection of security concerns and does not allow for accurate verification and validation of security requirements and behavior. While the concept of `trust' can be influenced by aspects of reliability, the metric used for measuring trust should be binary as one can not say that they trust a component, or system, 80\% of the time; whereas reliability can be easily described as a percentage.
With all the work towards describing and defining security modeling aspects, there is a need to develop a method for calculating `estimation metrics' that can be used to compare and contrast generated solutions. To even begin development of these metrics, one needs to be able to account for a `security metric' that can represent differing solutions, algorithms, methods for tackling security concerns and requirements.
%This `security metric' value should be `relatively deterministic'. What this paper means it that the values calculated should be deterministic, but that this deterministic nature will originate from a scaling, or ranking, that is `relative' to the capabilities of the security aspect being examined (e.g. ranking encryption techniques~\cite{Ferrante2013}). Further more,
These metrics must eventually all have the same basic `unit of measure', thus allowing for a relevant interpretation of developed metrics and calculated values for various security solution implementation designs. The easiest is a monetary amount (USD). Since everything carries some weight of time (development, testing, production, design), then at some point one will need to convert a unit-less metric to a time metric to a monetary metric. To better describe these security models from a financial standpoint, it might be advantageous to have the final estimation metric be represented with a money over time unit of measurement.
% Add in an image of the drawing from the bulletjournal on the process
\begin{figure}
\centering\includegraphics[height=6cm]{./images/aadl_security_framework.png}
\caption{Visualization of Security Design Framework}
\label{fig:AADLSecFrame}
\end{figure}
Section~\ref{sec:framework} will propose a security design framework that can be used for applying a
verification and selection process by which a set of risk-based equations can be used to assign metrics to
developed embedded system security models. The proposed design framework in Figure~\ref{fig:AADLSecFrame} would
require the following steps to take place:
\begin{enumerate}
\item Creation of a low-level component library that would contain normal and secure version implementations of each base component within the architectural space used for model generation.
\item Formalized description and definition of higher level security requirements that may come from user-defined needs or from the experience of knowledge of security experts.
\item Creation of a mapping process by which security requirements and secure component specifications can be uniformly verified and selected to allow for the generation of potential secure architectural system model solutions to the given inputs.
\item Verification tools to validate mapping implementation solutions.
\end{enumerate}
Other additional aspects of this framework, that could come from the existing tools, extensions, and annexes would include code generated using the secure models.
%Work towards developing these sorts of tools for secure architectures (e.g. seL4) is already one of the focuses of current AADL security annex work~\cite{AADLSecAnalysis}.
While this framework is a vision of overall design process, in this paper, we focus on just the requirements
modeling and the verification process. Specifically, we focus on how to model security goals and requirements
in such a way that they can be measured and validated. Ideally one desires a metric that incorporates not only
the impact of design decisions on a system and the cost of producing a design, but also account for the
examination and evaluation an attacker may make of a system. However, before one can even begin to apply a
framework to this verification and selection process, one needs to first be able to define `Security Risk' so
that a relatively deterministic formula can be used to obtain a meaningful metric.
\section{Defining Risk}
\label{sec:riskDefinition}
% Risk traditionally defined
Risk is generally defined as the potential of gaining or losing something of value. Value can be seen as physical health, emotional well-being, financial wealth, etc. Another definition of risk involves viewing risk
as an intentional interaction made with some uncertainty. In this scenario, uncertainty is defined as a potential, unpredictable, and uncontrollable outcome; risk is seen as a consequence of action taken in spite of some given uncertainty. Depending on the point-of-view of the individual measuring risk, its definition and application can vary a significant amount. For example, risk can be the analysis of expected loss %(as shown in Equation~\ref{equ:expectedLoss}).
Risk is not a certainty of an event occurring, but a probability that it will happen. But to develop an equation for risk one must first define the potential of events and the losses that could be incurred. Possibility, in risk, depends on two aspects: (1) threat and (2) vulnerability ~\cite{Ferrante2013}. Threat is defined as the cause of risk (e.g. fire, kidnapping, leakage of sensitive information, etc.). Vulnerability is defined as the exiting flaw or weakness which can be exploited and result in an accident. The concept of risk states that risk may result in losses for an agent, user, company, etc. Losses occur because of the consequences of an accident (defined as Impact). Depending on the impacted asset, `Impact' may be defined as a tangible (e.g. loss of revenue or financial penalties) or as intangible (e.g. loss of productivity or loss of reputation)~\cite{Mukhopadhyay2013}. An `asset' can be defined as anything valuable to a user or organization or company. An asset can be (1) a physical object, (2) secrete information, (3) business goal, etc. As mentioned earlier, risk requires an element of probability, meaning that the probability value acts as a 0.00 -{}- 1.00 scale weight. Putting everything together, risk is generally represented as follows:
\begin{equation} \label{equ:riskDefinition}
Risk = Probability * Impact
\end{equation}
% Define Risk for this paper
For the purpose of this paper, risk will be represented as a combination of probability and impact (as shown in Equation~\ref{equ:riskDefinition}). The reason for this interpretation is that from a security lens, it is much easier to quantify probability and impact. In addition to these, this paper develops a methodology for evaluating design choices based on impact (risk), cost of the design, and also incorporating the attacker's side of examining any given embedded system. Without a proper method for defining risk and cost models, one can not verify, evaluate, compare, and contrast designs in a relevant and worthwhile manner.
% Differences can occur when assessing risk depending on the point of view of the individual
Summarizing, risk is a combination of (1) a threat, (2) a vulnerability, (3) an impact. Complications in
security risk identification can come from a lack of experience and standards or due to the evolution of a system. The first comes the fact that defining `security risk' is still novel and does not have standardized procedures for dealing within the cyber-modeling domain. The second issue originates from the fact that computer systems evolve quickly over time. The system within an organization can change quickly with new technologies appearing very often; changing the landscape of `cyber risks' and other cyber-domain concerns. Risk can be assessed differently based on how it is examined. Depending on where uncertainties originate from, how impacts of actions are measured, and how these variables interact with each other, different variations of risk equations can be developed. To further complicate possible risk calculations, the equation for interpreting risk can differ based on the role of the individual measuring said risk. What may be a calculated risk to a defender, could prove to be advantageous to an attacker by causing less risk of being observed or even allow for
less risky attacks to be performed against a system. Another example would be that heavy security
implementation may cause a larger risk value for an attacker, but would produce a minimal risk value for the
defender of the same system. Further examination of attack and defense considerations will be continued in
Section~\ref{sec:attackDefense}.
\begin{equation} %\cite{Mukhopadhyay2013}
\label{equ:expectedLoss}
Expected Loss = Risk Frequency * Risk Amount
\end{equation}
One can measure risk from the probability of a failure of a given component (e.g. firewall, anti-virus, both), the loss amount for each component failure (e.g. firewall, anti-virus, both, none), and the expected loss (average loss)~\cite{Mukhopadhyay2013}. In this manner an individual can measure risk for a larger, interconnected system, but as the scope of the risk examination changes, so does do the methods by which risk is measured.
% Incorporating security into risk calculations
Different methods by which security can be incorporated into risk management include: as a weight representing implementation of security solutions, as a probability that a security concern is met or attacked, the
possibility of a security failure, etc. Given all these variations, how can one define security in a meaningful and relatively deterministic manner? The first part that needs to be tackled is why is `relatively' good enough for this security metric? The reason that a degree of `relativity' is required for developing a security metric, is that security changes and evolves over time, meaning that the algorithms and methodologies will transform and improve over time. This change means that the measurement for security must remain important relative to the existing security solution space. The reason that this value can not be fully deterministic is that security is constantly progressing and improving, meaning that any deterministic nature in the calculation of a security metric must also account for this change over time. Ideally embedded system security modeling should have more deterministic interpretations of generated security solutions, but at the current point this is not realistically achievable. Security levels can also be interdependent depending on implementation and scenario/situation.
The purpose of this paper is to propose a method for combining security and risk in a measurable and meaningful manner. Taking the already defined risk equation (i.e. Equation~\ref{equ:riskDefinition}), we move to add in the existence of a `security metric' and `cost weight' to the probability that either a direct or an indirect attack occurs to a given system.
\begin{equation} \label{equ:securityRisk}
Security Risk = \frac{p_{da} * w_c}{Security Metric}
+ \frac{p_{ida} * w_c}{Security Metic}
\end{equation}
This can be seen in Equation~\ref{equ:securityRisk}, where the probability aspect of risk is split between the
chance of how exactly an attack will occur. $w_c$ is the cost weight, i.e. the weight assigned to the cost of
the system. %XXX is this the right definition of cost weight?
$p_{da}$ represents the probability of a direct attack, where direct attack is defined as an event where an
attacker directly attempts to brute force a given security mechanism or standard. $p_{ida}$ represents the
probability of an indirect attack, where an indirect attacker is one where a malicious user attempts to circumvent existing security by some aspect that is not directly related to the mentioned security implementation.
%XXX What is the definition of security metric in the equation?
Once risk has been defined in the scope/lens of examination, one can move develop an `Estimation Metric' that can be compared and contrasted with each other to determine the `value'/`worth' of any given design. However, before these metrics can be developed, one must first determine a framework by which these calculations will be incorporated to allow for a relevant and meaningful interpretation of verification and selection metrics.
\section{Introducing the Framework}
\label{sec:framework}
Now that this paper has presented a meaningful manner of representing security risk as a metric, this paper moves to show that the introduced security framework is an ideal fit for continuing development and improvement of embedded system security modeling techniques and methodologies. What does the proposed framework bring to the table that lacked in previous security framework designs? The new security framework proposed allows for generation of embedded system security models by assuming that the security requirements and architectural component capabilities can be represented in a quantitative manner. With the framework, shown in Figure~\ref{fig:AADLSecFrame}, one can take the risk equations developed in Section~\ref{sec:riskDefinition} and produce a meaningful metric estimation that can be used to compare and contrast varying security model solutions. Combination of the framework's verification process and the risk equations developed is done in the following manner:
\begin{enumerate}
\item Define the security requirements and architectural components in a numerically meaningful manner.
\item Take these unit-less metrics and apply a `conversion equation' to them in order to produce a meaningful, `monetary unit' based metric.
\item Develop a method of interpreting the metrics in terms of requirements met, not met, and additional features added to the system.
\item Combine these metrics in a unified equation that can be used to take in values from the functional and architectural space to produce a series of embedded system security model solution metrics.
\end{enumerate}
One complication of this technique is the requirement to create `libraries' for certain aspects of the security modeling framework; for example, the various solution implementations for `keeping data secure'. More will be touched upon this subject in Section~\ref{sec:additionalConcerns}. Another concern is how one ranks all the various security solutions, algorithms, and methodologies in such a manner that the capabilities of the architectural components play a part in determining the best solution models that can be generated from a given set of constraints.
% Considerations about the verification process
Ideally verification of a design should be done through validation of the requirements that were met, not met, and any additional features that were introduced due to design decisions of the developer. Certain aspects of this verification process are easier to tackle but just have not had the time and effort focused on them. One such aspect is defining security terms in a manner that can be standardized for use. However, although choosing the language to describe security concepts and ideas may be simple, having that language remain flexible and relevant over the course of security's evolution is not as easy. Working towards an effective, rigorous, and standardized security modeling framework verification methodology is something that will not only benefit the security community, but will allow for better representation and understanding in other fields as well (e.g. business).
% Development of the verification process
To begin developing the verification and selection process, one needs to create a metric of weights based on the relative importance of any given solution $s_i$ in comparison to solution $s_j$~\cite{Ferrante2013}. The purpose of these weights is to allow for comparison of varying solution elements, relative to each other, as they are used within embedded system security modeling solutions. \textit{Importance}, with respect to the aforementioned `relative importance' matrix, is defined as a ranking that will depend on the case of implementation by a given company/group. Because this value is dependent on the `source' examining a particular security model, the value will be partially arbitrary and partially cost analysis. An other influencing factor could also come from the preference/wheel house of a given company or individual.
% Explain the work done by Ferrante et. al.
Borrowing from the work of Ferrante et.~al.~ using the Analytical Hierarchy Process (AHP), this paper moves to examine the process developed for producing weights for various security solutions. First, one must create an arbitrary 1-{}-10 ranking of the importance of any given element in comparison to any other elements of the security design model; where 1 is defined that both elements are equally important and 10 is defined that one element is absolutely more important than the other. These values are then inversed to create a matrix of `relative importances' of the various security model elements with respect to each and every other element in the design. Since the elements of the matrix are based on human judgement there is the possibility that inconsistency may exists. Ferrante et.~al.~ did develop equations to recognize these inconsistencies, but further examination of the process is left to the reader. However, not all aspects of security are going to be quantitative, some will be more qualitative and thus more difficult to deterministically produce values for. A rough method of producing quantitative values from qualitative properties was also proposed by Ferrante et.~al.~; by using the weight developed for a given requirement and multiplying this value by a series of binary representations of whether or not a given feature meets the same requirement that the feature in question is attempting to meet. This is represented by the following equation from Ferrante et.~al.'s work~\cite{Ferrante2013}:
\begin{equation} \label{equ:qualitative}
L_i = \sum_{j=1}^{R} g_j * v_{ji}, i = 1,2,...,S
\end{equation}
% XXX what are the L, R, g, and v values?
One must note that there are essentially two values being spoken about in the work by Ferrante et.~al.~; first is the generation of a security metric (named security level) and second generation of a weight metric. The creation of the `security level' metric is a simple mapping of some physical property to a 0.00 -{}- 1.00 scale with 1 being the highest possible security level. Once one has created these `relativity matrix' and `security level' metrics, these values can be used to produce security metrics about a given embedded systems security model design.
% Introducing the Security Metric equation
The next consideration is how does one take these produced values and develop a meaningful equation for generating a comparable metric. Following the examination of the work by Ferrante et.~al.~, their definition of `security level' is as follows:
\begin{multline} \label{equ:securityMetric}
`Security Metric' (Security Level) = \\
weight_{element 1} * Security Level_{element 1} \\
+ weight_{element 2} * Security Level_{element 2} \\
+ {...} + weight_{element n} * Security Level_{element n}
\end{multline}
Each `element', in Equation~\ref{equ:securityMetric}, can describe different algorithms, elements, properties, and capabilities of the different components of a system or device. It is worth noting that this equation is not necessarily limited to a single use within entire process. This same style can be used at higher level abstractions of the same design to produce an overall security metric representing a larger system of components. Harking back to our discussion of risk, the following is an example of calculating aggregated security metrics of a system (i.e. network security):
\begin{multline} \label{equ:overallSecMet}
`Overall Security Metric' = weight_{anti-virus} * Security Metric_{anti-virus} \\
+ weight_{firewall} * Security Metric_{firewall} \\
+ weight_{element i} * Security Metric_{element i}
\end{multline}
% Introduction to paper's Security Risk security
This allows for a designer to now create some arbitrary metric to represent whether or not a given design is better or worse at meeting not only the requirements imposed but also in comparison to other available solutions to the same design problem. While this is a step in the right direction, there no units attached to the overall
security metrics produced by the work of Ferrante et.~al. Without a proper unit attached to a generated metric, the entire process remains arbitrary and more difficult to be used in a relevant and meaningful manner. Calling back to the equation proposed in Section~\ref{sec:riskDefinition}, allow us to make use of the same techniques Ferrante et.~al.~developed but apply them in a more meaningful, cost-based manner. In this way it is possible for a `security risk' metric to be generated but also carry a recognizable worth instead of just an arbitrary number scheme. But these values of cost must come from somewhere, and that is the purpose of the `cost weight' variable. This is because the `cost weight' is a representation of the potential loss caused by an event and the hours required to `repair' the problem. This causes the unit of our security risk metric to become cost over time.
%\begin{multline} \label{equ:securityRisk}
% `Security Risk' = Security Level * direct attacker probability * cost weight \\
% + Security Level * indirect attacker probability * cost weight
%\end{multline}
% Introduce paper's Estimation Metric equation
While having an equation for security risk is great, this does not allow for a representation of a system as a whole. Additional aspects that must be taken into account include costs of implementing a given solution, the cost of maintaining a given solution, how a generated solution's ranking will change based on the user type interacting with the system, a metric given to the solution as a whole, as well as determination of the number of requirements met, or not met, by any chosen design solution. Taking these aspects into account, this paper proposes the following equation to calculate an overall `estimation metric' for any produced embedded system security modeling design.
\begin{multline} \label{equ:estimationMetric}
`Estimation Metric' = `User Risk Type' * `Security Risk' + `implementation cost' + \\
`maintenance cost' + \frac{`solution metric'}{`requirements weight'}
\end{multline}
Some of the values for this equation, implementation and maintenance costs, are expected to be flat costs that are pre-calculated by a company or business since these values will be specific to the given organization. An important difference between these values are that the `maintenance cost' and `implementation cost' values do not incorporate the operational costs of the design, they only account for the cost of initial implementation of a system design and the cost of performing upkeep for said design.
`User risk type' comes from a business minded examination of risk~\cite{Mukhopadhyay2013} where users can be averse to risk, risk seeking, or risk neutral. The purpose of this variable is a method of representing different users of secure systems that exist within the real-world (e.g. users that are over protective and
users that treat security with a laissez-faire attitude). The User Risk Type should produce a lower value if a user is risk averse and a larger value if a given user is risk seeking. In this way, User Risk Type should `negatively' affect the cost of the system as more risk prone individuals become the user.
The `requirements weight' variable can be easily constructed using the same techniques developed by the Ferrante et.~al.~ group to produce a `relativity matrix' of the requirements met, not met, or additional features brought to a design due to the methods, components, and algorithms implemented in a given design. To simplify calculations, one can stick to a more binary representation of requirements as either being met or not being met. The behavior of this requirements weight should be such that having `negative requirements' (e.g. requirements not being met) should cause a larger cost of the design due to specific needs not being met; hence the purpose behind inverting the value.
The `solution metric' value is a more arbitrary value coming from an internal ranking of solution `worth' to a given individual or company. For the purpose of Equation~\ref{equ:estimationMetric}, this `solution metric' should be representative of the operational cost of a given design based on a monetary cost over time unit of measurement. The aspiration behind the last part of Equation~\ref{equ:estimationMetric} is that this represents that operation cost of the design being weighted by the number of requirements that are met and those that have not been met (using a 0.00 -{}- 1.00 scale).
Now that aspects of this framework's verification and selection process have been explained, allow us to apply these techniques to a sample example.
\section{Exploring a Simple Implementation}
\label{sec:simpleExample}
This paper now moves to showing a simple implementation of the security framework's verification and selection process to produce a meaningful `estimation metric' that can be used to compare design decisions. The purpose of this examination is to give a concrete example of the verification equations being used to rank a set of produced solutions to a chosen design problem, as well as illustrate how one may go about developing some of the required rankings. When initially designing a system, there are a large number of considerations that must be taken into account. From power consumption requirements, architectural needs, spacing of parts, and weight of the developed device. When incorporating security elements, the problem becomes larger. For example, allow this paper to assume that the elements in Table~\ref{elementTypes} have numerous variations that can be simplified into a few types.
% Add in the table of elements and variations
\begin{table*}[]
\centering
\caption{Table illustrating different component variations}
\label{elementTypes}
\begin{tabular}{@{}llllll@{}}
\toprule
\multicolumn{6}{c}{Component Types Table} \\ \midrule
\multicolumn{1}{c}{\multirow{2}{*}{{\underline{\textbf{Elements}}}}} & \multicolumn{5}{c}{\textbf{Types}} \\
\multicolumn{1}{c}{} & \multicolumn{1}{c}{{\underline{\textbf{I}}}} & \multicolumn{1}{c}{{\underline{ \textbf{II}}}} & \multicolumn{1}{c}{{\underline{\textbf{III}}}} & \multicolumn{1}{c}{{\underline{\textbf{IV}}}} & \multicolumn{1}{c}{{\underline{ \textbf{V}}}} \\
Memory & Unprotected & Protected & Encrypted & Obfuscated & Combo \\
Bus & Unprotected & Encrypted & Non-sniffable & & \\
Processor & Simple & Embedded Encryption & Pure Encryption & & \\
Data & Plain-text & Encryption & Protected & & \\
Port & Normal & Encrypted & Protected & & \\ \bottomrule
\end{tabular}
\end{table*}
This table will represent the possible architectural components choices that can be made when attempting to develop a new security embedded systems design. The simple example that this paper will examine is that of a wireless transmitter. Listing~\ref{lst:AADLUserDefineLow} shows the AADL user-defined description of the wireless transmitter element being discussed. This paper makes use of AADL to aid in modeling embedded systems with security properties and constraints for giving a practical example of our proposed adversarial risk-based approach to embedded systems security modeling. AADL has a large and active community that works towards development and improvement of new annexes or other extensions to the existing AADL lexicon. In addition to the ease of extensibility, AADL is an easy language to pick up and learn. This paired with the way in which AADL has been intuitively built, allows for ease of extension by other users or even the community at large.~\cite{AADLV2Overview}
\begin{lstlisting}[caption={Example of User-defined Lower Level Components},label={lst:AADLUserDefineLow}]
system implementation transmitter.encrypt_i
-- Subcomponents of the transmitter
subcomponents
ant_in : system recv_antenna.normal_i;
ant_out : system trns_antenna.encrypt_i;
encrproc : processor procbase.encryptembedded_i;
-- Connection definitions of the transmitter
connections
c0 : port ant_in.wired_out -> encrproc.input_port;
c1 : port encrproc.output_port -> ant_out.wired_in;
-- Flow path definition for the transmitter
flows
f0 : end to end flow ant_in.f0 -> c0 -> encrproc -> c1 -> ant_out.f0;
-- Additional properties of the transmitter
properties
securityspecs::has_encryption => true;
end transmitter.encrypt_i;
processor implementation procbase.encryptembedded_i
properties
securityspecs::has_encryption => true;
securityspecs::encryptmodule_class => embedded;
securityspecs::encryption_class => AES;
securityspecs::encryption_variation => b256;
securityspecs::has_PUF => false;
securityspecs::has_TPM => false;
securityspecs::has_encryptedflash => false;
securityspecs::isTamperProof => false;
end procbase.encryptembedded_i;
\end{lstlisting}
In this example, the paper assumes that there are four variations that exist of said transmitter:
\begin{enumerate}
\item Non-encrypted communication with a separate input and output buses.
\item Encrypted communication with separate input and output buses.
\item Non-encrypted communication with a single IO bus.
\item Encrypted communication with a single IO bus.
\end{enumerate}
The four instances of a single possible solution being generated based on two aspects of the architectural space: (1) the number of IO buses available and (2) whether or not communication should be encrypted. To further simplify the considerations of this example, the paper chooses to ignore the influence of IO bus variation and focus on the implementation, or lack of, encryption. In this manner, the examination goes from four variations to two variations (encryption enabled or encryption disabled). To better pad out this encryption scenario we choose to examine the wireless transmitter under use of an optimal AES256 encryption algorithm using a MIPS processor, the `good enough' use of AES128 encryption algorithm also on MIPS architecture, and a complete lack on implementation of encryption. It is worth noting that while in theory having no encryption should cause for the lowest values possible (0.00) but in order to show the effect of these elements this paper assumes the lowest value obtainable is 0.10.
%For the sake of simplicity, this paper makes use of the `relativity matrix' developed by Ferrante et.~al.~\cite{Ferrante2013} for representing the security level metrics on the encryption standards used.
How does one create the security metric based on the given example? The first step requires the creation of `relativity matrix'~\cite{Ferrante2013} for developing a relatively deterministic security metric value. The point of this is to generate a ranking for all known solutions that ranges from 0.00 -{}- 1.00 that can be used as a weight or security level with other known cost variables to produce a metric that can be used to compare potential generated solutions. For the purpose of this paper, we will be making use of the encryption standard rankings developed by Ferrante et.~al.
The next step is how to consider differences between the implementations of the wireless transmitter. Differences from values can come from alternative design choices and/or algorithm and policy implementations of security or other standard constraints being imposed onto the design problem. For this simple example, the main difference examined is the implementation of encryption. These different aspects can be compared by assigning weights for allowing relative importance, thus representing (in some arbitrary manner) the user-defined requirements imposed on the design being generated. This human-related favoritism causes the generated metric to alter from a small amount to notable change based on the chosen importance of different features. Other areas originate from the development of `user risk type' and `solution metric', where there are some arbitary decisions made on ranking of users or generated solutions.
Before being able to calculate out the estimation matrix for our wireless transmitter example, we make some
simplifications and assumptions to smooth the process. First we will take the assumption that there will be three separate implementations of encryption for the wireless transmitter: AES256 (MIPS), AES128 (MIPS), and no encryption. Drawing from the work by Ferrante et.~al.~, the corresponding security level (SL) values are {1.00, 0.60, 0.10} respectively. Since we have simplified the example to having a single requirement (i.e. encryption of data), then the weight value used for calculating the Security Metric (SM) is 1.00. Now that we have values for SL and the weight, we can move to calculating the SM value for our different encryption scenarios. However, first we must make some assumptions about the cost weight ($w_c$), direct attack probablity ($p_{da}$), and indirect attack probability ($p_{ida}$). For the $w_c$ value we make the assumption that some company may find that the data collected by this wireless transmitter is worth \$20 if lost and would take one person about 8 man-hours to repair a failure; thus the $w_c$ for loss becomes \$20 per 8 man-hours. % XXX is the cost weight really the impact? Should you use impact or $i$ as the variable name?
As for the attack probabilities, this paper assumes that attacking any other wireless transmitter (indirect attack) would be the same as attacking a chosen wireless transmitter and that attacking a central aggregation computer would be out of scope for this example, therefore the indirect attack probability can be taken as 0\%. Assuming that an employee has a less than enthusiastic installation of the transmitter, the $p_{da}$ value is taken to be 25\% chance of an adversary brute forcing encryption to see the transmitted data. Using Equation~\ref{equ:riskDefinition}, one finds that the SR values for the {AES256, AES128, None} encryption implementations are {0.625, 1.04, 6.25} respectively.
From this point, we make further assumptions about the implementation cost ($c_i$), the maintenance cost ($c_m$), and `solution metric'/operational cost ($c_o$) since these values would come from metrics internal to a company or organization. $c_i$ is taken to be \$50 in parts and design per 40 man-hours, $c_m$ is taken to be \$50 in drive out cost per 4 man-hours to check the system, and $c_o$ is assumed to be \$3 in power costs per 12 hours of operation. The RW value is assumed to be 1.00 if the system is encrypted and 0.10 is not; since the effect of not meeting requirements can be viewed more clearly. Taking the calculation of the estimation metric (EM) from Equation~\ref{equ:estimationMetric}, we produce the contents of Table~\ref{tbl:estimationMetrics} which represents the estimation metric for each encryption scenario {AES256 (MIPS), AES128 (MIPS), None} and how different User Risk Types (URT) also further influence the metric.
% Please add the following required packages to your document preamble:
% \usepackage[normalem]{ulem}
% \useunder{\uline}{\ul}{}
\begin{table}[]
\centering
\label{tbl:estimationMetrics}
\begin{tabular}{|c|c|c|c|l}
\hline
& \multicolumn{3}{c|}{User Risk Type} & \\ \cline{2-5}
& Risk Averse & Risk Neutral & Risk Seeking & \\ \hline
AES256 (MIPS) & 14.07 & 14.13 & 14.31 & \\ \cline{1-4}
AES128 (MIPS) & 14.12 & 14.21 & 14.52 & \\ \cline{1-4}
No Encryption & 16.94 & 17.50 & 19.38 & \\ \hline
\end{tabular}
\caption{Calculated Estimation Metrics for Wireless Transmitter (USD/man-hour)}
\end{table}
Now that a simple example has been shown, allow this paper to now expand the considerations that are made for this simplistic example. The following section will examine further expansion of `estimation metric' considerations, showing how the calculation of comparable metrics can become more involved and complicated.
\subsection{Expanding Considerations}
Despite the efforts to simplify the embedded system security modeling problem, there are a plethora of additional variables that can be taken into consideration depending on the environment and user, or company, at risk. When calculating the estimated cost metrics used for making larger system design decisions, one ideally accounts for as many aspects of the system as possible. When dealing with the constrained domain of embedded systems, this is doubly so. Physical costs of the system carry a heavy weight when making choices about design implementations. Power costs, heat generated, run time, area requirement, etc. are all aspects that must be considered. When incorporating software, the assumption of this paper is that software has been designed correctly with no error or malicious behavior embedded within. To that case, this means that when comparing software implementations, the main considerations of the developer are run time, bits used (in the case of encryption and authentication), and power consumed (with respect to total battery life; total system run time on a single charge). To further add the weight of additional design considerations to our proposed verification and selection process, one can account for any additional features as a result of design decisions. This would mean that the inverted requirements weight would need to be further tailored to account for additional features that a design receives due to the decisions made by a development team. In this manner a design team can further tweak the generation of certain design solutions based on the requirements met and additional features produced as result.
There can also be additional considerations that come about due to how probabilities, risk, and weights are chosen to be interpreted. Should an individual choose to incorporate features such as exposure or concentrate on sensitivity and security level of individual data, then one could attempt to produce a `probability rating' that represents these concerns, as shown in Equation~\ref{equ:probRating}.
\begin{multline} \label{equ:probRating}
`Probability Rating' = weight_{sensitivity of data} * `known vulns metric' \\
+ weight_{exposure} * Security Level Metric_{data?}
\end{multline}
Complications of this examination range from simple questions, such as how does one measure exposure of an element, to more complicated concerns, such as how does one rank known vulnerabilities or how can one be aware of all vulnerabilities within a system. As such, this is perhaps not the best equation for producing an over system metric, but may play a role in a more bounded examination.
Another method of examination would be to focus on the total `wealth' of a system over time. In this case one's focus would be more towards the future and use of a given system within an organization.~\cite{Ferrante2013}
\begin{multline} \label{equ:wealthFunction}
`Wealth Function' = Probability Nothing Happens * Initial Wealth \\
+ Probability Event Happens * (Initial Wealth - Losses)
\end{multline}
`Initial Wealth' can be calculated from the design model generated, while the probability of events occurring will require more statistical harvesting of information relating to known attacks or event occurring within a given system. While advantageous from a business standpoint, this equation is also tailored to a specific point of view for examination of a given embedded systems security model. Expanding on this concept of point-of-view, then next section moves to examining the generated secure embedded system models through the eyes of both the defender and the attack as well as considerations that arise.
\section{Examining Attack and Defense with Detail}
\label{sec:attackDefense}
The purpose of this section is to take the framework, along with the verification and selection process, and examine the stages of encryption and authentication and how including attack and defense considerations changes the landscape. Depending on the point of view of the individual examining a system, the risk and cost analysis will yield different results to different individuals based on produced incentive and attractiveness of obtainable information in comparison to the defenses that must be circumvented and the related cost. This means that when accounting for the attacker and defender view, there will be further levels of considerations and some that can be wholly arbitrary. Certain aspects may be similar, such as the number of steps an individual must go through to interact with a system (e.g. subnets). While these do exist, the area of greater interest are the aspects that differ between the two points of view. To begin this process one needs to detail out any and all statistical information about attacks on various systems, how the hardware and software nuances affect the overall ranking of different methodologies, and most difficult, one must determine a method for applying the arbitrary qualitative sense of worth for specific data to one's equations in a meaningful way. Otherwise the generated estimation metric becomes unintelligible.
\begin{lstlisting}[caption={User-defined Higher Level Security Requirement},label={lst:AADLUserDefineHigh}]
abstract implementation sysreq.wireless_sensor_i
subcomponents
serv_ADConv: abstract sysserv.ADConv_i {
servatrb::dynamicRange => 0..5 V;
secatrb::integrity::atkImpact => 300;
};
serv_wrlsTrans: abstract sysserv.wrlsTrans_i {
servatrb::distance => 100 m;
secatrb::authentication::atkValue => 600;
secatrb::authentication::atkImpact => 400;
secatrb::authorization::atkImpact => 1200;
secatrb::dataleakage::atkImpact: => 800;
secatrb::dataleakage::atkValue: => 800;
};
fnc_data: abstract security_props.data_i {
dataatrb::data_class => Sensor;
secatrb::atkImpact => 800;
properties
secatrb::hasProtection => false;
secatrb::AuthGroup => Employees;
end sysreq.wireless_sensor_i;
\end{lstlisting}
One can further complicate these calculations by including a difference in examining the costs from the standpoint of both the defender of some sensitive information and the attacker trying to acquire any and all `useful' data. One example of this are the `atkImpact' and `atkValue' fields in Listing~\ref{lst:AADLUserDefineHigh}. These represent potential metrics of importance for different elements, attack vectors, or worth of data that can be obtained by attacking a given system. As a defender, one can work towards detailing a system's defenses to have a better interpretation of the attack landscape. For example: one can create a `correlation matrix' of the enacted defenses and the affect of failure of one defense on the other existing defense (0-1 scaled as well), as this would allow for greater detail of the system from the point of the defender. Additionally, this same information would be of great importance to a would-be attacker.
\subsection{Expansion of Details}
While the examinations proposed here are specific to the system under examination, considerations can extend to a far larger scope of concern. One can begin to account for the worth of data to external parties (e.g. any other individual that is not the attacker or defender; black market or customers). Then one must account for the arbitrary worth of that information to another individual, which could also vary greatly. For example: an encrypted file that a computer novice comes across will have little worth to them, but to an individual whom has experience this may pass some calculated risk threshold. Additionally, a person could act as an `information broker' that may not have a `worth' value attached to data at this point, but in the future the worth associated with specific information could easily rise or fall depending on content and `liveliness'.
\section{Additional Concerns}
\label{sec:additionalConcerns}
While the considerations, up to this point, have mainly been focused on how to define risk, how to interpret qualitative values of security into quantitative one, and even how the examination of a system changes when incorporating attacker and defender points of view, there are still larger problems that must be addressed.
One of the largest problems facing security verification and validation techniques is the requirement for a `security expert' to formulate `libraries' of information and other data that will be needed for greater formalization of calculated values. Unfortunately these `libraries' are almost entirely arbitrary with respect to the knowledge and experience of a given security expert. This allows a great deal of room for inconsistencies due to human input. While Ferrante et.~al.~developed a method for locating inconsistencies within their work, there is no standardized methodology for determining inconsistencies in general. this means that these values can not be calculated in a deterministic manner and require a more `relatively deterministic' touch.
An other concern is that current attempts at developing security metrics produce unit-less metrics; due to their arbitrary nature. For example: in the work by Ferrante et.~al.~they are able to produce a metric value, but the interpretation of that value requires an explanation by the researchers instead of allowing for a glance-interpretation of the data. This complicates manners of comparison and is a known problem when trying to develop new benchmarks and standards for comparison. This paper proposed a standard of maintaining a monetary-time value since most aspects of security incorporate time to some degree and it is relatively simple to associate a financial value to time spent.
The last, and perhaps largest concern, is that there are still aspects of the proposed process that are arbitrarily decided upon. This is an extremely difficult element to remove from the current examination of security framework verification and selection using an adversarial risk-based approach to embedded systems security modeling due to the need for qualitative input to a system that has yet to have standard quantitative input. While this work will continue to attempt to minimize the use of arbitrary values and rankings, it will take the effort of the entire security community to help move security measurements from a qualitative scale for a more quantitative one.
\section{Conclusion}
Having examined a new security modeling framework, coupled with the examination of its verification and selection process, it is the hope of the paper that the reader has begun to see not only how to produce meaningful security and risk-based metrics, but also see how additional consideration of worth to attacking and defending parties can complicate calculations due to a lack of knowledge and experience of how to measure and relate them. As the security community continues to develop and grow new techniques and methodologies, they must also rigorously standardize their method of examination to allow for better, more effective verification and selection of `best fit' embedded system security modeling solutions.
Future work include further development of the mapping process using a risk-based methodology, continue creating more deterministic means for describing security requirements and architectural component capabilities in a meaningful and comparable manner, and development towards an automated method for comparing generated solutions within a constrained and directed manner to arrive at best solutions for generated embedded systems security models.
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\end{document}