A view of trust and information system security under the perspective of critical infrastructure protection

A view of trust and information system security under the perspective of critical infrastructure protection

Bako Rajaonah

LAMIH UMR CNRS 8201 – Institut Carnot ARTS Université de Valenciennes et du Hainaut Cambrésis Campus Le Mont Houy, 59313 Valenciennes, France

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Although trust is recognized as important in security issues of computer networking environments, few studies on information systems deal with both trust and security, and those existing tend to remain within the short perimeter of two-agent interactions. We propose to rethink trust research on information system security by considering the holistic approach of critical infrastructure protection (CIP). After introducing the problem, we give the definitions that are necessary for a common understanding of the concepts of critical infrastructures and trust. Some works on critical infrastructure protection involving information systems are then described briefly. Finally, we present our transdisciplinary view of trust research on information system security under the perspective of CIP.


critical infrastructure protection, information system, security, transdisciplinarity, trust

1. Introduction

Trust is recognized as central to understand modern societies (e.g., Lewis and Weigert, 2012; Misztal, 1996, 2013) and is particularly important in security issues of computer networking environments (e.g., Lamsal, 2001). However, very little studies on information systems deal with both trust and security. Among existing works in the literature, one trend is acceptance studies involving end-users of IS- based services (e.g., Mangin et al., 2014) or of social networks (e.g., Fogel and Nehmad, 2009; Shin, 2010). Other works are centred on end-users trustworthiness (e.g., Aberer and Despotovic, 2001; Swamynathan et al., 2005). Finally, another trend focuses on the design of trustworthy information systems (e.g., Offor, 2013; Ruotsalainen et al., 2014; Truong et al., 2016).

Therefore, it seems that trust research related to information system security tends to remain within a short perimeter which is mostly that of trust-based two- agent interactions (humans – systems, systems – humans, humans – humans) mediating by a specific information system. This paper proposes to open the debate on rethinking trust research on information system security. In today’s information- based  world,  it  might  be  that  the  holistic  approach  of  critical  infrastructure protection would be more enriching rather than considering trust-related issues of information system security from only a per se perspective.

Indeed, firstly, information systems and the Internet are nowadays at the very core of most businesses and services in companies, organizations and institutions. Secondly, information and knowledge that are stored and/or exchanged in those information  systems  are  of  a  great  value,  which  attracts  both  well-  and  ill- intentioned people, especially cyber-attackers among the latter. Finally, the consequences of attacks on information systems might affect vital services. This third point is a strong argument in favor of studying information system security under the perspective of critical infrastructure protection (CIP). Indeed, the very definition of critical infrastructures involves vital services, i.e., that disruption or destruction of those infrastructures due to natural disasters, extreme weather conditions, industrial accidents, deliberate attacks, human errors, etc. would have a significant impact on vital societal functions, health, safety, security, economic or social well-being, which makes their protection of government concern. See, for example, the Green Paper on a European Programme for Critical Infrastructure Protection1  (EC, 2005); the European Programme for Critical Infrastructure Protection EPCIP2  (EC, 2006); and the European New approach to EPCIP3 (EC, 2013).

1. http://eur-lex.europa.eu/legal- content/EN/TXT/PDF/?uri=CELEX:52005DC0576&from=EN

2. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2006:0786:FIN:EN:PDF.

3. http://ec.europa.eu/dgs/home-affairs/what-we-do/policies/crisis-and-terrorism/critical- infrastructure/docs/swd_2013_318_on_epcip_en.pdf.

Critical Information Infrastructure Protection (CIIP), that is a part of CIP, refers to the protection of critical infrastructures related to information and telecommunication technologies (ICT) (see EC, 2005). The sector of ICT includes the Internet, information systems, industrial control systems such as Supervisory Control  Data  Acquisition  (SCADA)  systems  and  Distributed  Control  Systems (DCS), fixed and mobile communications, satellite communication, radio communication and navigation, and broadcasting (Luiijf and Klaver, 2015; Zio, 2016). This sector is particularly sensitive because nearly all critical infrastructures have components that rely on ICT (e.g., Hämmerli, 2005). Cybersecurity  defined as the process of protecting information by preventing, detecting, and responding to attacks4 is therefore particularly important in CIIP. For instance, Article 22 of the

2013 French Military Programming Law5 is specifically dedicated to the security of vital information systems; see also the 2016 Stocktaking, analysis and recommendations on the protection of CIIs of the European Union Agency for Network and Information Security (ENISA, 2016)6 and the 2014 Framework for improving critical infrastructure cybersecurity of the US National Institute of Standards and Technology4 (NIST, 2014).

In fact, research on cybersecurity undertaken from the perspective of critical infrastructure protection is growing across the world (Gonzalez et al., 2006; Grimsman et al., 2016; Karabacak et al., 2015; Ten et al., 2010; Thakur et al., 2016; Zhou et al., 2011, etc.). Nevertheless, little of that research has focused on trust- related  issues  despite  the  multidisciplinarity  characteristic  of  trust,  which  is  a concept used in both soft and hard sciences, and the multifaceted nature of critical infrastructures, which include machines, technologies, humans, organizations, and institutions. Moreover, as emphasized by Dunn (2005), not much work has focused on the social and political dimensions of CIP/CIIP although they are of central importance. Concretely, debating the question of trust and information system security under the perspective of the protection of critical infrastructures would be highly relevant to find global solutions; but it would be even better to include all human and social sciences.

The paper is organized as follows. In order to facilitate common understanding of  critical  infrastructure  protection  and  trust,  these  topics  are  tackled  from definitions in Chapter 2 and Chapter 3. Chapter 4 describes briefly some works on CIP/CIIP involving information systems in order to show the trend of research. Finally, in Chapter 5, we present our human and social scientist’s view of CIP-based research on trust-related issues of information system security.

4. https://www.nist.gov/sites/default/files/documents/cyberframework/cybersecurity- framework-021214.pdf.

5. https://www.legifrance.gouv.fr/eli/loi/2013/12/18/DEFX1317084L/jo/texte

6. https://www.enisa.europa.eu/publications/stocktaking-analysis-and-recommendations-on- the-protection-of-ciis/at_download/fullReport

2. Critical infrastructures

An infrastructure can be defined as a “framework of interdependent networks and systems comprising identifiable industries, institutions (including people and procedures), and distribution capabilities that provide a reliable flow of products and services essential to the defence and economic security […], the smooth functioning of government at all levels, and society as a whole” (Moteff and Parfomak, 2004, CRS-3). This definition that explicitly includes people as part of infrastructures is very important for our purpose on trust. It echoes the definition of Bouwmans et al. (2006) who consider infrastructures as socio-technical networks combining physical networks   (man-made   systems   and   processes)   and   actor   networks   (people, institutions, and companies). Infrastructures can be viewed as complex adaptive systems (e.g., Rinaldi et al., 2001) or as systems-of-systems (e.g., Eusgeld et al., 2011). The common assumption behind those points of view (those of Bouwmans et al., Eusgeld et al., Rinaldi et al., and others) is that an infrastructure is a whole that exhibits emergent properties and behaviors which do not result from the sum of its components’  properties  and  behaviors.  That  point  is  important  for  research conducted under the perspective of critical infrastructure protection: enhancing the security and/or safety of one element of the infrastructure does not necessarily ensure the security and/or safety of the whole infrastructure. The difference between safety (sécurité) and security (sûreté) which is adopted in this paper is that the former refers to accidental harms and the latter to malicious ones (e.g., Firesmith, 2003).

As for critical infrastructure, the definition adopted by the European Council is that an EU critical infrastructure is “an asset, system or part thereof located in Member States which is essential for the maintenance of vital societal functions, health, safety, security, economic or social well-being of people, and the disruption or destruction of which would have a significant impact in a Member State”1  (EC, 2008). Another definition specifies that European critical infrastructures are those “which are of the highest importance for the Community and which if disrupted or destroyed would affect two or more Member States, or a single Member State if the critical infrastructure is located in another Member State”2 (EC, 2006). Although definitions of both infrastructure and critical infrastructure have evolved over time, even depending on nation states (e.g., Dunn, 2005; Galland, 2010; Moteff and Parfomak,  2004),  there  is  a  consensus  on  the  fact  that  critical  infrastructure protection is essential to the survival of populations and environments.

Critical infrastructure  protection (CIP)  aims at increasing CI resilience and ensuring that vital services continue to function  (EC, 2013). Resilience can be defined as the ability of those infrastructure “to anticipate, cope with/absorb, resist and recover from the impact of a hazard (technical) or disaster (social)” (Kröger and Zio, 2011, p. 4; see also Geoffroy et al., 2017; Haimes, 2009). Concretely, the protection of critical infrastructures consists in preparing for, protecting against, mitigating, responding to, and recovering for critical infrastructure disruptions or destruction (EC, 2005), which requires to understand the physical, functional, and organizational aspects of CI (Zolesio, 2010). These tasks are arduous because of the diversity of critical infrastructure sectors, the nature of their environment and of their interdependencies.  An indicative list of critical infrastructures sectors is provided in EC (2005): Energy; Information, Communication Technologies (ICT); Water; Food; Health; Financial; Public & legal order and safety; Civil administration; Transport; Chemical and nuclear industry; and Space and research. As mentioned earlier, the ICT sector is protected within the critical information infrastructure protection (CIIP).

As expressed in Rinaldi et al. (2001), infrastructures are interdependent with their environment; these authors defined the infrastructure  environment as the framework in which goals and objectives as well as value systems are set, operations are modeled and analyzed, and decisions taken. Kröger and Zio (2011) considered the following aspects that could characterize critical infrastructure environment: economic, business, public policy, legal/regulatory/strategic, technical, security, health, safety, social, political, and/or speed of development/change.

Figure 1. Rinaldi et al.’s examples of infrastructure interdependencies (Rinaldi et al., 2001, p. 15)

Critical infrastructures do not exist in isolation of one another, they are crucially characterized by their interdependencies (e.g., Bouchon, 2006; Rinaldi et al., 2001). Rinaldi et al. defined dependency   as a unidirectional relationship between two infrastructures when the state of one of them influences or is correlated to the state of the other; it is the case between the electric power and telecommunication infrastructures, the former being supported by the latter for, among others, the SCADA systems. Rinaldi et al. defined interdependency as a bidirectional relationship, each one depending on the other, and interdependencies as multiple connections among infrastructures (Figure 1).

The complexity of interdependencies networks illustrated in Figure 1 as well as the diversity of critical infrastructure sectors described in EC (2005) show how a failure in one infrastructure could easily affect other infrastructures and worsen the extent and nature of damage and potential consequences on health, safety, security, economic and/or social well-being. Protection of critical infrastructures requires for that matter to understand and predict cascading failures as well as their cascading impacts (e.g., Chopra and Khanna, 2015; Stergiopoulos et al., 2016)

Moreover, the type of interdependencies, which is another dimension that characterizes critical infrastructures, must also be considered in risk assessment in interdependent infrastructures (e.g., Haimes et al., 2008). Interdependencies are categorized into four classes (see Kröger and Zio, 2011; Rinaldi et al., 2001): physical  interdependency when  linkages  rely  on  each  other’s  materiel  outputs (e.g., a pipeline network providing gas to fuel a gas-fired power station while the electricity generated is used to power compressors and controls the gas supply network,  Kröger  and  Zio);  cyber  (or  informational)  interdependency  when linkages rely on each/other’s informational outputs (e.g., a telecommunications infrastructure supporting SCADA or other control systems for energy or water delivery systems, CREDC, 2016); geographic  (or spatial)  interdependency when linkages are spatial proximity (e.g., a natural gas pipeline located in the right-of-way corridor of a high-kVA transmission line, CREDC, op. cite); and logical interdependency when linkages are neither physical nor informational nor spatial (e.g.,  the  California  electricity  crisis  due  to  interdependencies  between  electric power supply and financial infrastructures, Rinaldi et al.).

Critical infrastructure protection requires to identify and classify threats, capabilities, risks, and vulnerabilities; it includes the definition of risk events in terms of their probability of occurrence, impact, and relationship to other risk areas or processes (EC, 2005). Risk describes (future) negative, undesirable consequences and  the  associated  uncertainty  (Zio,  2016).  According  to  Aven  (2011),  risk associated with an event can be formulated as uncertainty about and severity of the consequences of the event, uncertainty referring to the lack of knowledge of whether the event will occur or not and how severe would be the consequences. Although risk analysis is at the heart of critical infrastructure protection, it is out of the scope of the present paper. Readers who are interested in risk analysis in complex systems such as critical infrastructures can consult, for example, Aven (2011); Bach et al. (2013); Haimes et al. (2008); Santos et al. (2014); Zio (2009). The concept of risk is tightly related to vulnerability, but they should not be confused. Vulnerability is defined by the Society for Risk Analysis (SRA)7 as both a qualitative property and a quantitative metric. With regard to critical infrastructures, the definition of vulnerability that is often adopted refers to a property of infrastructures or of their systems: vulnerability can be seen as a degree of losses and damages due to the impact of hazards, a degree of exposure to hazards, or a degree of resilience (Kröger and Zio, 2011).

To recap, critical infrastructures are socio-technical networks whose disruption or  destruction  of  their  physical  or  cyber-physical  components  due  to  natural disasters, extreme weather conditions, industrial accidents, deliberate attacks, human errors, etc. would have serious impact on health, safety, security, economic or social well-being. Their protection is therefore a matter of political concern. For instance, the European Commission has published several Communications dealing with critical infrastructure protection (e.g., EC, 2005; EC, 2013). The protection of the sector of information and communication technologies (ICT), being particularly sensitive because of the dependencies of other sectors on ICT, has led to the emergence of working groups across the world on critical information infrastructure protection (e.g., CSS, 2008; ENISA, 2016; NISC, 2007; NIST, 2014; OECD, 2015), especially regarding political strategies to strengthen the security and resilience of critical information infrastructures. As for France, the Agence Nationale de Sécurité des Systèmes d’Information (ANSSI)8 is dedicated to the security and defense of information systems “and contributes to that of critical operators”.

Before describing briefly some works on information system security carried out within the framework on critical infrastructure protection, the next chapter gives basic definitions of concepts related to trust.

7. www.sra.org

8. http://www.ssi.gouv.fr/en/mission/audiences-and-activities/

3. Concepts and definitions around trust

In human and social sciences, the psychological functionality of trust would be to reduce perceived uncertainty and, therefore, perceived risk in complex decision- making situations (e.g., Luhmann, 2000; Numan, 1998). The mechanism that underlies  trust would be  a mental reduction of  the field  of possibles so  that a decision can be taken without considering the outcome of each possible alternative (Lewis  and  Weigert,  1985;  Thuderoz,  2003).  That  point  of  view  on  trust functionality is particularly appropriate for critical infrastructures in which uncertainty is present at any layer because of, among others, the impossibility to have holistic knowledge of them. Indeed, emergent properties and behaviors in such systems of systems could not be inferred from the knowledge of single systems, nor even of single components of each system (see, for instance, Luzeaux, 2010).

Besides the concept of interpersonal trust between two or more people including organizational trust (e.g., Deutsch; 1958; Kramer, 1999; Schoorman et al.,  2007),  researchers  also  consider  systemic   trust,  i.e.,  toward  impersonal structures such as institutions (e.g., Luhmann, 2000) and trust in technologies (e.g., Lee  and  See,  2004;  McKnight  et  al.,  2011).  But  what  is  trust?  Based  on  the taxonomy of Barber (1983), Muir (1987, 1994) defined trust as being composed of expectations: expectation of persistence of the natural and moral social orders, expectation of competence, and expectation of responsibility. According to that and also according to the above-mentioned functionality, trust is operationally defined in this paper as a state of expectations  resulting from a mental reduction of the field of possibles. This definition is not mutually exclusive with the idea of willingness to be vulnerable which constitutes the definitions adopted by most researchers (see the reviews of definitions in McKnight and Chervany, 2001; Schoorman et al., 2007). The  definition  is,  besides,  consistent  with  the  concept  of  distrust  as  confident negative expectations and trust as confident positive expectations (Lewicki et al., 1998).

As shown in Figure 2, trust can be considered in the form of a three-part relationship in which the trustor expects the trusted or trustee (i.e., the object of trust) to behave in a certain manner (e.g., Hardin, 2002).

Figure 2. Basic concept of trust as a three-part relationship between trustors, trustees, and expectations.

This three-part pattern, initially considered for interpersonal relationship, is in fact implicitly underpinning the studies on trust related to other objects than people. For example, Figure 3 shows possible trustors, trustees and trustors’ expectations around the information system of an organization.

Of course, with regard to an organization’s information system, objects of trust as well as trustors and their expectations are not restricted to those illustrated in Figure 4. Above all, the interrelationships between the different forms of trust are likely more developed and more complex in case of dependency or interdependency with one or more critical infrastructure(s). It is therefore obvious that trusts are mutually interdependent in critical infrastructures in the sense that trustors’ expectations rely on the achievement of other expectations from others trustors.

Figure 3. Examples of trusts around information systems. Trustors and trustees are circled, the direction of arrows point out the object of trust (i.e., the trusted), and the texts over the arrows are examples of trustors’ expectations

The main difficulty in inferring what could be the content of expectations is due to the necessity to distinguish trustors’ expectations and trust dimensions (also named antecedents in the literature) although they may overlap. For instance, system administrators may expect that users of information systems would be responsible with regard to cybersecurity; a dimension of this interpersonal trust could be the users’ awareness of security issues: the more the administrators perceive that users are  aware,  the  more  likely  they  would  trust  them  and  extend  access  rights. According to Castelfranchi and Falcone (2000), “the quantitative dimensions of trust are based on the quantitative dimensions of its cognitive constituents” (p. 7). These constituents, or “mental ingredients” are the beliefs and evaluations on which trust is based, and explain the content of expectations. In other words, trust dimensions are the core of trust’s dynamics. Indeed, the strength of expectations and, therefore, the level of trust as well vary depending on external factors related to the object of trust as well as on personal, social, and cultural characteristics related to the trustor; (e.g., Hancock et al., 2011; Hoff and Bashir, 2014; Mayer et al., 1995; McKnight and Chervany, 2001). Examples of dimensions related to the trustors are: disposition to trust; optimism bias; faith in humanity or in social order; subjective norms (e.g., Dzindolet et al., 2003; Li et al., 2008; McKnight and Chervany, 2006). Examples related to human trustees are: benevolence, integrity, morality, credibility, motives, abilities, expertise (Mayer et al., 1985; McKnight and Chervany, 2001); dimensions of trust within teams and/or organizations are: trust climate, organizational culture, culture   of   trust   (Karsenty,   2015;   Uslaner,   2012).   Examples   related   to   the technologies as trustees are:  dependability, reliability, predictability, failures rates, false alarms, transparency, safety, performance (e.g., Hancock et al., 2011; Hasselbring and Reussner, 2006; Li et al., 2008; Schaefer et al., 2016).

Two aspects characterize trust dynamics:  how it is built and how it evolves. In the absence of direct experience with the trusted, a priori trust or initial  trust is built based on information from third parties, reputation, first impressions, or documents, and depends on personal characteristics such as the disposition to trust (e.g.  McKnight  and  Chervany,  2006).  Once  interactions  between  trustors  and trustees are established, good reasons-based  trust is built from facts, relying on trustors’ trial and error experience, understanding of the trustees’ characteristics, predictability and limits, etc. (e.g., Lewicki and Bunker, 1996; Muir, 1994; Numan,

1998). Trust and distrust are alive, they increase or decrease depending on how expectations are met (or unmet as, for example, in trust violation in interpersonal relationships). Trust and distrust also evolve locally based on situational factors: they may be inappropriate in some situations. The concept of trust calibration (Muir,  1994)  illustrates  this  need  to  adjust  trust,  and  thus  expectations,  to  the context. For example, in the field of automation, in the case of choice between manual and automated control, human operators should distrust automation in contexts in which they know that automation cannot perform well; and they should trust automation when their own performance might be worse than that of automation. In a general way, appropriate distrust favors protective attitudes and behaviors against potential harmful actions (e.g., Lewicki et al., 1998).

To end this chapter, let us introduce two other concepts around trust. Besides the understanding of human relationships and behaviors for establishing trustworthy interactions, for instance, in organizations (Whitener et al., 1998), other objectives of research on trust and its dimensions are to design trustworthy technical systems, i.e., that would induce appropriate trust for appropriate reliance on those systems (e.g., Lee and See, 2004) and, trustworthy ICT, i.e., that would be safe and/or secure. Logically, designing trustworthy interactions, socio-technical systems, or technologies should be based on trust dimensions, making it worthwhile to study these dimensions. Finally, we define trustworthiness as a quality, more precisely the degree to which an object could be trusted given the expectations toward it. Here also, the properties of trustworthiness are closely linked to trust dimensions. For instance, in computer science, trustworthiness combines reliability and security (Yasinsac and Irvine, 2013).

To recap, trust is a state of expectations held by trustors toward the object of their trust (the trusted). Dimensions of trust are the factors that make levels of trust varying. These dimensions refer not only to the object of trust, but also to the individual, social, cultural, and contextual characteristics. Finally, what is important in the concept of trust is its dimensions: knowing the factors involved in trust building,   maintaining,   decline,   and   recovery   allows   researchers   to   design trustworthy relationships, socio-technical systems, or IC technologies as well as to create metrics of trustworthiness for decision-making.

Before describing our view on trust research on information systems security, the following chapter describes some trends in research on critical infrastructure protection involving information systems.

4. Trends in research on critical infrastructure protection involving information systems

The main purpose of scientific works carried out within the framework of the protection of critical infrastructures is to identify, understand, and analyze their vulnerabilities and interdependencies in order to predict, prevent, mitigate, and respond to security threats, cascading failures and their impacts. Research on critical infrastructures involving ICT can be categorized into two groups: on the one hand, research focusing on critical infrastructures that are dependent on or interdependent with information infrastructure or ICT; on the other hand, research aiming to contribute to the protection of critical information infrastructure. As mentioned earlier,  the  sector  of  ICT  includes  the  Internet,  information  systems,  industrial control systems such as SCADA and DCS systems, fixed and mobile communications, satellite communication, radio communication and navigation, and broadcasting. Nevertheless, in this paper we consider only the work involving information  systems,  and  only  in  terms  of  their  security,  but  a  lot  of  work  is dedicated to other information and communication technologies (see, for example, for SCADA systems in critical infrastructures, Miller and Rowe, 2012 and Ten et al., 2010; for communication networks, Duan et al., 2016 and Ericsson, 2010; etc.).

As emphasized by O’Brien and Marakas (2010), value of information systems to the  modern  organization  is  unlike  any  other  system  ever  created  (p.  31).  That renders  them  particularly  vulnerable  (see  Bisogni  and  Cavallini,  2010).  The definition of information systems (IS) adopted in this paper is that of both technical and social perspectives, that is to say, an information system is the combination of human and material resources (people, hardware, software, data, networks, etc.) which work together to achieve a common goal by collecting, retrieving, processing, storing, and disseminating data and information (e.g., Arduin et al., 2015; Huber et al., 2017; O’Brien and Marakas, 2010). It means therefore that any part of information systems may be vulnerable and induce vulnerability to the whole of any IS-based critical infrastructure. The reminder of the chapter presents examples of academic works related to information system security that were carried out to contribute to critical infrastructure protection. These works can be categorized into two groups: theoretical and empirical research.

4.1. Examples of theoretical works

The report by Anderson (1999) summarizes the results of a workshop held in California in August 1999 on research and development initiatives concerning the prevention,   detection,   and   response   to   insiders’   misuse   of   critical   defense information systems. The workshop was carried out within the program to protect America’s infrastructures9. The report is very rich and instructive, contains useful definitions and, above all, many tracks of research, for instance, developing an insider trust model.

The article by Bialas (2006) explains the similarities and differences between the concepts of information security management and critical information infrastructure protection  (CIIP).  While  information  security  management  concerns  one organization and is well defined by standards (see, for example, Pinheiro and Júnior

2016), there are not yet dedicated standards to CIIP although knowledge and guidelines do exist: Bialas cited, among others, Bruce et al., 2005, but the reader can also refer to works mentioned earlier (i.e., ENISA, 2016; NISC, 2007; NIST, 2014; OECD, 2015). However, although CIIP covers a larger scale than even the biggest organization, Bialas considered that some tools of information security management could be adapted to CIIP (e.g., the plan-do-check-act scheme), but the best would be to develop new ones that would take dependencies into account: intra-dependencies between the different layers of a critical infrastructure (physical layer, cyber layer, organizational layer, and strategic business layer at national or international level) and interdependencies between infrastructures.

The article by Dunn (2005) contains several observations. Among them, firstly, CIIP is mainly handled by engineers, consultants, practitioners and security experts who do not deal with the socio-political dimensions of CIIP. Secondly, critical infrastructure protection (CIP) and CIIP are ill-defined if the aspects of services, role and function for society are not taken into account in the objects of protection. That plus the inherent socio-political and cognitive dimensions of CIP/CIIP make a new problem that requires new analytical techniques and methodologies. Thirdly, the question of policies depends on the country (see CSS, 2008), the emphasis of CIIP may be on rather national security; rather economics; or rather law enforcement: the consequence is that determining appropriate protection efforts, goals, strategies, and instruments will depend on the key actors who are involved (respectively: security establishment, private sector, and law enforcement establishment). The conclusion of Dunn is the same as Bialas’s: CIP and CIIP require new holistic approaches, methods, and tools.

4.2. Examples of empirical works

The work of Rieke (2004) presents an approach that carefully analyzes the parts of critical information infrastructure which really need protection. An operational formal model of information systems of government/enterprise and their attackers’ behavior is proposed in order to carry out vulnerability analysis of government/enterprise  networks.  His  model  includes  a  model  of  the  network structure and configuration; a model of vulnerabilities; and a model of attacker capabilities and profile (Figure 4). Based on the graph of all possible attack paths, the operational model allows to detect attack in an early phase and/or find out the best protection to block attack paths.

9. President’s Commission on Critical Infrastructure Protection (1997). Critical foundations. Protecting America’s infrastructures: https://fas.org/sgp/library/pccip.pdf.

Figure 4. Component of Rieke’s model of enterprise network vulnerabilities (in Rieke, 2004, p. 6)

The work of Keeney et al. (2005) reports a deep analysis of computer system sabotage perpetrated by organizations’ insiders across US critical infrastructures. The findings were utilized by Gonzalez et al. (2006) in their empirical work on “social engineering”, a concept defined from the point of view of the hacker: social engineering is “the term that hackers give to acquiring information about computer systems through non-technical means” (Winkler, 1996), in other words, a “manipulation of people” by “psychological forcing” in order to breach the security system. Gonzalez et al. proposed to model critical ICT infrastructures and threats, particularly social engineering attacks in order to recognize attack patterns through the modeling of archetypes inspired by chess game.

The work of Leszczyna et al. (2011) proposes an approach to the security assessment of the information systems of critical infrastructures, based on the simulation of attacks with MAISim (Mobile Agent Malware Simulator) that can simulate well-known malware as well as generic behaviors (e.g., file sharing propagation) and non-existent configurations. The steps of the approach are the following: analysis of the ICT system of the critical infrastructure; reconstruction of the evaluated information system in a computer security laboratory; identification of use scenarios from a prior analysis of the utilization of the system by its users as well  as  from  operational  procedures,  security  policies,  etc.;  experiments;  and analysis of results. What is interesting is that these results are employed to build a tool that help users to decide on the trustworthiness of the system. The tool named “trust case” is graphic-based document. The approach had been applied to the verification of the security of industrial controls systems and power plants. For more details on MAISim, see Leszczyna et al. (2010).

The work of Bisogni and Cavallini (2010) presents the Vulnerability of Information Systems (VIS) model dedicated to the assessment of the economic sectors that are most vulnerable to critical information system breakdowns. The model is based on the simulation of information systems (IS) like in Leszczyna et al. (2011). More precisely, the VIS model simulates IS disruptions and assesses their socio-economic impact on the affected sectors. It also ranks sectors according to the vulnerability to IS disruptions.

To conclude this presentation of works on information system security under the perspective of critical infrastructure protection, it must be emphasized that it was not the objective to carry out an exhaustive review of research on information system security within the framework of critical infrastructure protection (CIP) and critical information infrastructure protection (CIIP). The presented empirical works address an important aspect of CIP in general which is the identification of vulnerabilities, here, seen as the degree of exposure to cyber-threats. However, apart from the VIS model in Bisogni and Cavallini (2010), most of proposed solutions remain within the perimeter of two-agent interactions (system - user or attacker or both). That confirms that Bialas (2006) and Dunn (2005) were right: CIP and CIIP require new holistic approaches and methods. Moreover, we failed at distinguishing CIP and CIIP in the literature that we reviewed. Therefore, it may be that, at least with regard to research on the security of information systems (IS), the French designation of “systèmes d’information d’importance vitale” (see SGDSN, 201610) would be a relevant operational definition regarding the protection of IS-based critical infrastructures.

It may also be, as noticed by Dunn (2005), that new mindsets are necessary. Indeed, only new approaches could consider a holistic perspective of vulnerabilities in the whole of critical infrastructures. The next chapter presents our view of a CIP- based approach to trust research with regard to the security of information systems that are vital for the society.

10. https://www.ssi.gouv.fr/uploads/2016/06/communique_presse-cybersecurite-des-oiv.pdf

5. A human and social science view of research on trust and information system security under the perspective of critical infrastructure protection

This chapter presents our view of the research that should be applied to information   system   security   under   the   perspective   of   critical   infrastructure protection, with a particular focus on trust. Firstly, we adopt the French terminology of vital information systems to mean clearly information systems that are vital to the society, that is to say, which disruption or destruction would have a significant impact on vital societal functions, health, safety, security, economic or social well- being. This definition reproduces the definition of critical infrastructures, which allows us to remain in the context of critical infrastructure protection (CIP). Secondly, our view hinges on transdisciplinarity. We first explain why, and then we concretize this view through examples of future work.

As previously mentioned, the main objectives of research on trust are, firstly, to understand the role of trust in individual and social decisions and behaviors and, secondly to design trustworthy relationships, socio-technical systems, and technologies such as ICT. Research on decisions and behaviors involves not only disciplines of human and social sciences such as psychology, sociology, organizational science, economics, politics, etc. but also cognitive engineering. Human and social sciences are mainly interested in interpersonal trust, systemic trust, and trust in technology while cognitive engineering is interested in trust in technology. As for ICT, the design of trustworthy ICT has even led to the discipline of trustworthy computing (see Yasinsac and Irvine, 2013). The concept of trust is considered in that field through properties of trustworthiness (e.g., reliability and security) which respond to standards and trust requirements. All those kinds of trust can be addressed at all levels of critical infrastructures that are made up of man- made systems as well as of people, organizations, and institutions.

However, in view of those many disciplines working mostly separately, it is more than likely that the understandings of trust do not necessarily overlap. For instance, dimensions of trust in information systems viewed by software developers are not the same as those of trust viewed by end-users and yet their trusts (i.e., their expectations) are not necessarily independent each other. It is a simplistic example, but  at  the  scale  of  vital  information  systems,  the  interdependence  of  trust expectations of various actors may lead to a lack of mutual comprehension. The lack of mutual comprehension due to a lack of trust may be disastrous in situations of crisis management (Karsenty, 2015). For this author, trust management should be carried out prior to the occurrence of the crisis.

With regard to the security of information systems that are vital to the society, trust research should be considered from a non-disciplinary perspective, more precisely research should be transdisciplinary. It should not be surprising since it is the only way to produce new methodologies and tools as it was emphasized as necessary for critical infrastructure protection by Bialas (2006) and Dunn (2005). Indeed, while disciplinary research remains within the boundaries of disciplinary fields,  non-disciplinary  research  combines  elements  from  various  disciplines  in order to answer practical questions and to solve practical problems; “the interaction may range from communication and comparison of ideas, and the exchange of data, methods and procedures, to the mutual integration of organizing concepts, theories, methodology, and epistemological principles” (Van den Besselaar and Heimeriks, 2001, p. 706). Rosenfield (1992) distinguished three levels among non-disciplinary research. Multidisciplinarity is the first level: researchers work in parallel or sequentially   from   disciplinary   specific   base   to   address   common   problems. Interdisciplinarity is the second one: researchers work jointly but still from disciplinary-specific basis to address common problems. Finally, in transdisciplinarity, researchers work jointly using shared conceptual framework drawing together disciplinary-specific theories, concepts, and approaches to address common problems. More precisely, at the level of transdisciplinarity, researchers, stakeholders, and practitioners aim at joint  problem solving based  on a common view built from the integration of various disciplinary scientific knowledge as well as experience of stakeholders and practitioners (Gibbons and Nowotny, 2001; Pohl et al., 2008; Rosenfield, 1992).

That transdisciplinary perspective is closed to that hybrid one proposed by Le Coze (2011) for industrial safety assessment. Le Coze considers that articulating not only  technological  and  human  factors,  but  also  organizational  factors  (because socio-technical systems have organizational properties) around a framework model (modèle cadre) is the best way to apprehend the complexity of industrial safety.

Getting back to trust research within the protection of critical infrastructures in general and of vital information systems in particular, concretely, an important step is to unify knowledge and experience of trust issues in critical infrastructure protection. That does not exclude to create new knowledge, but it should encompass human, technology, and society dimensions by crossing disciplines from human and social  sciences  (psychology,  sociology,  economics,  etc.)  to  engineering  and computer sciences. Organizational sciences might be the link between these soft and hard sciences because, as it is emphasized in Boy (2013) and Le Coze (2011), organization is at the heart of the functioning of socio-technical systems.

The techniques of ontology (e.g., Gruber, 1995), ontology alignment (e.g., Shvaiko and Euzénat, 2008), and ontology modularization (e.g., d’Aquin, 2012)  are perfect tools for creating transdisciplinary knowledge bases composed of heterogeneous information from various domains and that would be understandable by and sharable among all actors of critical infrastructure protection. Examples of competency questions (Ushold and Gruninger, 1996) that could guide ontologies building from a transdisciplinary view of critical infrastructure protection may be: How to characterize vulnerabilities in terms of their potential societal impacts (for instance, economic, health, and environmental costs)? What are the invariant characteristics of information systems that are vital to the society?  How to identify vulnerabilities that could be due to inappropriate trust and distrust? How to identify interdependencies between trust expectations at people, technologies, organizational, and institutional levels which, if not fulfilled, could lead to vulnerabilities to a whole infrastructure?

Another important step is to work on meta-trustworthiness metrics of vital information systems, that is to say, metrics that would measure the degree to which these systems would be trustworthy, not only from a computer science viewpoint, but also from human and social sciences angle; and not only from the per se perspective, but also in view of the interdependencies between those systems and critical infrastructures of other sectors. The mathematical concept of trust reputation 

used in the domain of computer science (e.g. Alcaraz and Zeadally, 2015) could serve as a basis for research on such new metrics of meta-trustworthiness. These metrics would help managers, stakeholders, and institutions to prevent, mitigate, or respond to security threats due to lack of trustworthiness of the global vital information system including people.

Those   two   examples   of   works   that   could   be   carried   out   through   a transdisciplinary protection of vital information systems are a small sample of what could be done. An agenda of research has first to be defined, of course, with a prior transdisciplinary dialogue between researchers, practitioners, experts, stakeholders, and governmental institutions.

6. Conclusion

This paper addresses issues of trust research related to the security of vital information   systems   (VIS).   We   propose   to   use   the   framework   of   critical infrastructure protection to deal with the complexity of such systems and avoid analyzing trust from only a two-agent interaction perspective, which could not be relevant given the society issues of the security of those systems. Indeed, the very definition of critical infrastructures involves vital services, that is to say, disruption or destruction of those infrastructures due to natural disasters, extreme weather conditions, industrial accidents, deliberate attacks, etc. would have a significant impact on vital societal functions, health, safety, security, economic or social well- being.

Until  now,  research  in  the  framework  of  critical  infrastructure  protection  is mainly carried out in engineering and computing sciences. Given the society issues, it is astonishing that the disciplines of human and social sciences are almost absent from the research on that topic. And yet, to speak only about trust, they have a solid background of knowledge and savoir-faire.

Research on trust is fundamental to understand its role in individual and social behaviors  and  decisions,  and  to  design  trustworthy  technologies.  The  former involves disciplines of human and social sciences as well as cognitive engineering. Human and social sciences are interested in interpersonal trust, systemic trust, and trust in technology while cognitive engineering is mainly interested in trust in technology. All these aspects of trust are useful for the protection of VIS. As for the design of trustworthy technologies, research is mainly carried out in the domain of computer science and has even led to the discipline of trustworthy computing. The concept of trust is considered in that discipline through properties of trustworthiness which respond to standards and trust requirements, of course, in the language of computer science.

It is not at all sure that researchers of the disciplines mentioned above have the same understanding of trust neither of security. That could be particularly appalling in  today’s  world  relying  on  information  and  communication  technologies  and because  the  worse  of  cyber-attacks  is  to  come  given  the  deployment  of  cloud computing and the Internet of Things.

With regard to the protection of VIS, trust research should be considered from a transdisciplinary perspective. It is the only way to produce new knowledge, methodologies and tools necessary for critical infrastructure protection. Researchers, stakeholders, and practitioners will work jointly based on a common view of the physical, functional, and organizational aspects of VIS, which will be built from the integration of various disciplinary knowledge as well as experience of stakeholders and practitioners. The first step would be, therefore, to build transdisciplinary knowledge bases (for instance, with techniques such ontology, ontology matching, and ontology modularization) that would be understandable by all parties. Another step is to work on metrics of meta-trustworthiness of VIS, that is to say, metrics that would measure the degree to which these systems would be trustworthy, not only from a computer science viewpoint, but also from human and social sciences angle; and not only from a per se perspective, but also in view of their interdependencies with critical infrastructures of other sectors.

To conclude, a preliminary working program is proposed:

– Organizing national, European, and/or international workshops gathering together experts in the domain of critical infrastructure protection and vital information systems in order to present safety, security and society issues of critical infrastructures and vital information systems as well as to provide definitions that could constitute a basis for a common background.

– Identifying researchers in each scientific discipline who could work on trust issues of vital information systems, as well practitioners and institutional experts.

– Organizing workshops with these identified actors to: (1) discuss about the conceptual approaches, methods, and tools in each discipline which could be used to create common conceptual and methodological approaches; and (2) define a short-, medium-, and long-term working agenda.


The author warmly thanks Kathia Oliveira and Pierre-Emmanuel Arduin to have offered her the opportunity to write on the topic of trust in the field of computer science. She also thanks the three anonymous reviewers for their precious comments and suggestions.


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