Horatiu Moga1,2
1.Senior Cyber Expert, PhD. Eng., National Center for Financial Information, Ministery of Finance, Brașov, Romania,
2.BlackSea Maritime Cybersecurit Center, Maritime University of Constanța
Rezumat: Cercetarea își propune să evalueze viitorul alternativ propus prin paradigma polieuristică de politică externă aflată sub constrâgerile războiului cibernetic. Paradigma polieuristică de politică externă evaluează decizia politică în două etape, prima fiind cognitivă (focalizată de prejudecăți politice – de aceea se numește polieuristică prin concatenarea prefixului politic cu decizia euristică) iar a doua rațională concentrată pe cântărirea diverselor comportamente focalizate pe obiective. Paradigma polieuristică este specifică domeniului de analiză de politică externă și psihologiei politice a relațiilor internaționale, are largi aplicații in studiile de securitate, iar acest articol se dorește o încercare de extensie a acesteia spre domeniul provocator al razboiului cibernetic care își face drum ca obiect de cercetare în studiile de securitate în ultimele două decenii. Integrarea constrâgerilor cibernetice de politică externă s-a focalizat pe studii de caz si codificări calitative ale datelor culese din surse OSINT și în acest fel s-a construit matricea polieuristică de decizie a unui actor statal care stă la baza viitorului alternativ propus de cercetarea noastră. Cercetarea nu se consideră exhaustivă ci doar una care propune să deschidă noi orizonturi în cunoaștere promovând integrarea paradigmei polieuristice de politică externă cu analiza calitativă a codificări datelor și abordarea OSINT de culere a informațiilor.
Abstract: The research aims to evaluate the alternative future proposed by the poliheuristic paradigm of foreign policy under the constraints of cyber warfare. The poliheuristic foreign policy paradigm evaluates the political decision in two stages, the first being cognitive (focused by political prejudices – that’s why it’s called poliheuristic by concatenating the political prefix with the heuristic decision) and the second rational focused on weighing various behaviors focused on objectives. The poliheuristic paradigm is specific to the field of foreign policy analysis and the political psychology of international relations, it has wide applications in security studies, and this article is an attempt to extend it to the challenging field of cyber war that is making its way as an object of research in security studies over the past two decades. The integration of foreign policy cyber constraints focused on case studies and qualitative coding of data collected from OSINT sources and in this way the poliheuristic decision matrix of a state actor was built which is the basis of the future alternative proposed by our research. The research is not considered exhaustive but only one that proposes to open new horizons in knowledge by promoting the integration of the poliheuristic paradigm of foreign policy with the qualitative analysis of data coding and the OSINT approach to information gathering.
Keywords: descriptive indicators, interpretive indicators, presumptive indicators, thematic matrix, strategic foresight.
1.INTRODUCTION
The research aims to define a new way of defining the alternative future in the foreign policy of a state under the constraints of cyber warfare with the help of the poliheuristic decision matrix. This study is intended to aid analysis in foreign policy, international relations, security studies, intelligence analysis, and cyber risk analysis with a new scientific analysis tool for assessing the future. Studies in the prospective/foresight field demonstrate that quantitative analyzes have limits in use and effectiveness (Gordon, 2008) and an effective approach is one focused on qualitative methods (Lockwood, 2013) or mixed qualitative-quantitative methods (Sokolowski & Banks, 2009), in which the concept of an alternative future is defined by qualitative and quantitative variables. Since purely quantitative assessments in foresight approaches from various fields have shown their limits in predicting the future, alternative fields have proposed to fill this gap by using alternative sciences but also involving methods, techniques and methodologies that make a discount from the science approach countries and classical positivism.
Among these methods, methodologies and qualitative techniques that are involved in the science of foresight we can mention (Adu, 2019): the phenomenological approach, the phenomenological-hermeneutic approach, interpretive phenomenological analysis, transcendental phenomenological approach, ethnography, the narrative approach, the case study approach, fundamental theory approach.
In this research we propose an investigation of empirical data based on the analysis of case studies from OSINT open sources based on qualitative coding of descriptive and interpretive-presumptive type data. This study aims to fill a gap in the fields of foreign policy, international relations, security studies, intelligence analysis and cyber risk analysis that has generally been supported in the field of strategic foresight using qualitative or qualitative-quantitative methods, methodologies and techniques and by using the concept of alternate futures providing studies that prove their scientific validity over time. The article begins with a review of the poliheuristic paradigm (and the poliheuristic decision matrix) then it will trace the concepts of cybernetic constraints, qualitative indicators of descriptive data respectively interpretive-presumptive and alternative futures, For the analysis of qualitative data specific to several case studies inductive logic is used for conceptual construction, using the thematic matrix as a complement to the qualitative analysis of the case studies.
The current study aims to present a consolidated way of assessing alternative futures in fields such as foreign policy analysis, international relations, security studies, intelligence analysis and cyber risk analysis based on case study analysis and thematic analysis matrix.
2.METHOD
The methodology section begins with the presentation of the poliheuristic foreign policy paradigm and how to define the concept of alternative futures connected to this paradigm.
The reason by which the alternative future is connected to the poliheuristic paradigm is related to the idea of several authors of strategic foresight, whereby in an environment that undergoes rapid and profound changes, the decision-maker is subject to quick System I type decisions (Kahneman, 2015) of a cognitively based nature on prejudice (Mintz, 2010).
That is why the poliheuristic paradigm of foreign policy is focused precisely on a set of prejudices that govern quick decisions of the System I type (Kahneman, 2015). This set of biases are seventeen in number and are as follows (Mintz, 2010): B01. “Focusing on short-term benefits rather than longer term problems”; B02. “Preference over preference”; B03. “Locking on one alternative”; B04. „Wishful thinking”; B05. „Post-hoc rationalization”; B06. „Relying on the past”; B07. “Focusing on a narrow range of policy options rather than on a wide range of options”; B08. “Groupthink” B09. “Overconfidence; over-estimating one’s capabilities and underestimating one’s capabilities”; B10. “Ignoring critical information; denial and avoidance”; B11. “Focusing on only part of the decision problem”; B12. “Turf battles leading to suboptimal decisions”; B13. “Lack of tracking and auditing of prior decisions and plans”; B14. “Poliheuristic bias”; B15. “Shooting from the hip”; B16. “Polythink” B17. “Group polarization effect”.
In general, the strategic foresight literature has dealt with the involvement of decisions based on prejudices in the area of business, business intelligence and competitive intelligence. This research aims to bring analysis tools such as alternative futures from the area of strategic foresight to foreign policy analysis using bias-based decision specific to both research areas.
In the literature of strategic foresight, the decision based on prejudices is specific to environments with deep changes where quantitative analyzes no longer have conclusive results (Gordon, 2008; Lockwood, 2013) and it is necessary to transition to qualitative modeling such as alternative futures, scenarios or other tools of this nature (Gordon, 2008; Lockwood, 2013).
This is relevant in a series of researches that are specific more to the business world and less to the political world or the foreign policy environment whether or not it is subject to cyber constraints.
Next, an introduction to the poliheuristic foreign policy paradigm proposed by the Israeli political scientist Alex Mintz (Mintz, 2010) will be presented. The paradigm is called poliheuristic from the concatenation of two elements, the concept of politics and decisions based on cognitive biases B01-B17 mentioned above (singularly or on a synthesis of them). Alex Mintz believes that his paradigm has three defining elements: the two-stage decision (the first is cognitive and the second is rational), the non-compensatory decision principle (which establishes a hierarchy of decisions specific to action-dimension pairs specific to the decision matrix) and the dimension internal of foreign policy.
2.1. The first element is to establish the management model in foreign policy – it is the first cognitive stage in the two-step decision-making process. In this stage, the actors participating in the foreign policy process are established, as well as the poliheuristic decision matrix that is the result of this stage of analysis. After determining the actors participating in the decision, the content of the poliheuristic decision matrix is determined.
The decision matrix is a tabular tool for analyzing the decision variants that the actors participating in the decision-making process have, which on the lines has several dimensions of the foreign policy objective and on the columns the different variants of foreign policies that the participating actors can follow to the decision. The layout of a decision matrix is shown in the table below in Fig.1.
Fig.1. Example of poliheuristic decision matrix with four foreign policy alternatives and three-dimensional objective
2.1.1. Alternative – represents the foreign policy behavior of a state actor. It can be of various natures, from diplomatic, economic to military. In Fig.2. the spectrum of foreign policy alternatives specific to the COPDAB foreign policy data bank (COPDAB, n.d.) is presented. This is a fifteen-step scale ranging from COPDAB15 which describes a large-scale war with great cost to the combatants to the unification into one nation of several nations described by COPDAB00. Fig. 2. it also describes the meaning of escalation (from cooperation policies to conflict) and de-escalation (from conflict policies to cooperation) in a state’s foreign policy. A modality used in other research on foreign policy subject to the constraints of cyber warfare (Cyber Operations Tracker, n.d.) combines these constraints with an alternative variant such as Fig.3. In this figure, the escalation/de-escalation course describes the dynamics of a state’s foreign policy before and after the event, and how cyberwarfare constraints specific to the US Council on Foreign Relations’ Cyber Operation Tracker database can influence foreign policy.
Fig.2. The COPDAB foreign policy scale and the meanings of escalation and de-escalation in foreign policy
Fig.3. Example of a poliheuristic decision matrix where the escalation/de-escalation course is subject to cyberwarfare constraints
The definitions of the cyber constraints in the Cyber Operation Tracker and specific to the columns in Fig. 3 are below (Cyber Operations Tracker, n.d.):
2.1.1.1.Distributed Denial of Service – consists of a large influx of data packets from multiple clients to a server.
2.1.1.2.Espionage – the ability of a state or non-state actor to collect information in digital format about a subject of international relations.
2.1.1.3. Defacement – the way in which information is exchanged in web format or other digital format in an unauthorized way about a certain state or non-state actor.
2.1.1.4.Data Destruction – logical destruction of information specific to a server or critical cyber infrastructure of a state or non-state actor.
2.1.1.5. Sabotage – consists in physically destroying a server, critical cyber infrastructure or other types of equipment with the help of a malware-type process.
2.1.1.6.Doxing – the method of gathering information about a state or non-state actor with the malicious intention of causing image, capital or other losses.
2.1.1.7.Financial Theft – clandestinely running crypto-currency processes on a server or critical cyber infrastructure of a state or non-state actor disrupting its good activity.
In strategic foresight research, the goal is not to predict the future, but to foresee those alternative futures that are favorable or unfavorable to the objective or objectives of a certain actor (Gordon, 2008). The future is seen as a leopard skin where the goals are described by the black spots then the brown and beige spots are the more or less pronounced uncertainties that govern the future and remain unknown to us. The role of the decision matrix is to define an alternative future that will express a certain favorable or unfavorable importance for the decision actor. Thus, the decision maker will focus on the alternative futures that are described by the black spots and then on the larger brown and beige lighter ones.
Fig.4. The vision of the future like a leopard skin
As mentioned above in the poliheuristic paradigm, the foreign policy decision is dependent on the internal characteristics of the state system, so the foreign policy objective has several dimensions such as: political, economic, military and civil society (Mintz, 2010). Also, in addition to the internal dimensions, it can also have international dimensions, as they are treated in a multitude of studies (Mintz, 2010).
2.1.3. Dimensions are equipped with weights that have values from 0 specific to the least important to 10 the most important, thus we establish a hierarchy between the internal dimensions and their importance in the decision process and compared to the international dimension. The weights are associated with the column with symbols W1, W2, W3 in Fig. 1 respectively Fig. 3. Thus, the hierarchy of dimensions that are subject to the non-compensatory principle of decision is implemented in the decision matrix with the help of these weights W1, W2, W3. If we have a decision matrix with political, economic and military dimensions, this establishes the hierarchy of political, economic and military objectives respectively of the interest groups in the three fields for a certain type of foreign policy action and cyber coercion. The objective with several dimensions can have values of Lose for losses incurred on these dimensions for unfavorable alternative futures (beige leopard spots, Fig.4.), Gain for gains obtained on the same dimensions for favorable alternative futures (leopard spots of black color, Fig.4.) or Neutral for alternative futures in which he suffered no losses or gains (brown leopard spots, Fig.4.). Likewise, an objective that has an alternative future may possess dimensions for which it suffers military losses, for example, economic gains or political neutralities. The hierarchy of objectives according to their outcomes of a Lose, Neutral or Gain nature is in the decision process closely related to the experience of decision actors who make decisions based on their biases B01-B17.
2.1.4. Implications and rates. By implication associated with a field of the decision matrix we mean a description of the consequence that a particular foreign policy alternative has on a dimension of the objective of the decision matrix. For a certain dimension, the implications of the consequences that can belong to the three classes of results Lose, Neutral or Gain will be evaluated and rates from -10 to +10 will be given accordingly. The dimensions for which the alternative has negative values are considered non-critical and are excluded from the structure of the decision matrix.
Fig.5. Study of the interpretation of outcome bias
a dimension with the help of the thematic matrix
Fig. 6. The rates associated with the implications organized into ten classes evaluated on the truth value of the interpretations of the dimensions of the global security indicator
In this research we consider that in building an implication the thematic matrix will be used for several case studies that are coded qualitatively from OSINT open sources such as those of Cyber Tracker Operation (Cyber Operations Tracker, n.d.), Global Cyber Index Strategy (Global Cyber Index Strategy, n.d.), etc., which expresses the interpretation that the actors involved in the decision process of foreign policy I give it to alternatives, dimensions, respective results to what kind of prejudices B01-B17 appeal.
For the case study data coding process, descriptive indicators can be used when the researched documents explicitly describe the interpretations of the decision-makers about the topics to be studied. Interpretive or presumptive indicators (Adu, 2019) can also be used when making the connection between decision biases B01-B17 and dimensions of the global security indicator that we consider as the dimension of inertia of critical cyber infrastructure in the face of foreign policy cyber constraints. Thus in Fig.5. the construction of the thematic matrix is presented for one of the political, economic or military dimensions, the type of result Lose/Neutral/Gain and the dimensions of the global security indicator (Legislative, technical, organizational, development and cooperation (Global Cyber Index Strategy, n.d.)) and the descriptive indicators who, what, where, when. The interpretive/presumptive why, how, for how long indicators are found in the right column of the thematic matrix that compares each dimension of the global security indicator with the type of outcome bias on a given dimension. In the figure Fig. 6 shows the way to evaluate implicit rates by bits and Boolean algebra with the help of the conclusions reached by the researcher with the help of thematic matrices such as the one in Fig. 5. There are five classes from 0 to 4 associated with weak or lack of technical measures in critical cyber infrastructure leading to Lose bias. The other dimensions make the separation within the Lose prejudices between the rates of values 1, 2 and 3. The same happens with the Gain prejudices between the values 6 and 10 specific to the technical measures strongly implemented in the critical cyber infrastructure. There is also a value rate of 5 that is specific to the Neutral bias. The table in Fig. 6 has only a reference character for this study because it exemplifies the way to evaluate the rates of descriptive, interpretative or presumptive indicators from the thematic matrices of each dimension.
2.2. Determining the decision rules – in this second stage, after establishing the rates for each field of the decision matrix, the decision rules will be determined that establish a hierarchy of the decision-maker’s actions to achieve a specific objective-result. As shown in the example in Fig. 7 yields a diagonal matrix that represents certain alternatives that the state actor has when subject to the constraints of cyber warfare, for each objective dimension. From Fig. 7 a stratified organization of its dimensional objectives can be observed, similar to the principle of non-compensatory decision organized as an alternative future that exposes for a multidimensional objective-result for specific constraints what kind of consequences a state actor can rely on in his foreign policy.
Fig. 7. Example of the alternative future organized as a decision matrix with the hierarchical organization of dimensional objectives according to the non-compensatory decision principle
3.CONCLUSIONS
The research began by reviewing the poliheuristic paradigm and highlighting its ability to include the concept of alternative futures in strategic foresight. In this way, the absence of the concept of an alternative future was highlighted in the political literature in general. Thus, among the elements of the poliheuristic foreign policy paradigm, the poliheuristic decision matrix is presented as an analysis tool associated with the concept of an alternative future borrowed from strategic foresight.
The research tried to integrate the concept of an alternative future with the specific elements of the decision matrix: alternatives, dimensions, weights, rates, implications. Thus, the role of components of the alternative future is played by the hierarchical organization of the dimensions of the objective and the non-compensatory decision principle as a form of consistency with a strategic foresight approach and a theoretical bridge to foreign policy analysis. The first positive aspect of this research is the way in which qualitative thematic analysis was involved in the first step of the foreign policy decision of a de facto state that can produce new valences in foreign policy research in the future by involving new fields of interpretive epistemology such as be grounded theory. We believe that the openings that this research offers towards the area of mixed qualitative-quantitative research methods by using thematic analysis in the interpretation of the five dimensions of the global cyber security indicator have a great future potential in understanding the interpretations that the studied actors give to the statistical indicators according to which they are evaluated. This evaluation of global security indicator dimensions using the thematic decision matrix as interpretations opens up new future ways of evaluation based on Boolean logic and the psychology of cognitive dissonance. Our research opens a great future of research in the selection of cases expressed by quantitative values as statistical indicators according to their dimensions that can be analyzed as interpretations of the actors who are involved in the research. As a future of research this study aims to include the poliheuristic evaluation of the alternative future with the scenario approach.
References
[1] Gordon A., (2008). Future Savvy: Identifying Trends to Make Better Decisions, Manage Uncertainty, and Profit from Change, AMACOM
[2] Lockwood J., (2013). The Lockwood Analytical Method for Prediction (LAMP): A Method for Predictive Intelligence Analysis, Bloomsbury Academic; 1 edition
[3] Sokolowski J.A., & Banks C.M., (2009). Modeling and Simulation for Analyzing Global Events, Wiley; 1 edition
[4] Adu P., (2019). A Step-by-Step Guide to Qualitative Data Coding, Routledge, 1 edition
[5] Kahneman D., (2015). Gândire Rapida Gândire Lenta, Publica
[6] Mintz A., (2010). Understanding Foreign Policy Decision Making, Cambridge University Press
[7] COPDAB (n.d.), Retrieved September 22, 2022, from https://www.icpsr.umich.edu/web/ICPSR/ studies/07767
[8] Cyber Operations Tracker of the Council of Foreign Relations (n.d.), Retrieved September 22, 2022, from https://www.cfr.org/interactive/cyber-operations
[9] Global Cyber Index Strategy (n.d.), Retrieved September 22, 2022, from https://www.itu.int/en/ITU-D/Cybersecurity/Pages/global-cybersecurity-index.aspx