Decision support for choice of security solution: the Aspect-Oriented Risk Driven Development (AORDD)framework

In security assessment and management there is no single correct solution to the identified security problems or challenges. Instead there are only choices and tradeoffs. The main reason for this is that modern information systems and security critical information systems in particular must perform at the contracted or expected security level, make effective use of available resources and meet end-users' expectations. Balancing these needs while also fulfilling development, project and financial perspectives, such as budget and TTM constraints, mean that decision makers have to evaluate alternative security solutions.\ud \ud This work describes parts of an approach that supports decision makers in choosing one or a set of security solutions among alternatives. The approach is called the Aspect-Oriented Risk Driven Development (AORDD) framework, combines Aspect-Oriented Modeling (AOM) and Risk Driven Development (RDD) techniques and consists of the seven components: (1) An iterative AORDD process. (2) Security solution aspect repository. (3) Estimation repository to store experience from estimation of security risks and security solution variables involved in security solution decisions. (4) RDD annotation rules for security risk and security solution variable estimation. (5) The AORDD security solution trade-off analysis and trade-o¤ tool BBN topology. (6) Rule set for how to transfer RDD information from the annotated UML diagrams into the trad-off tool BBN topology. (7) Trust-based information aggregation schema to aggregate disparate information in the trade-o¤ tool BBN topology. This work focuses on components 5 and 7, which are the two core components in the AORDD framework

Framework for Assessing Information System Security Posture Risks

In today’s data-driven world, Information Systems, particularly the ones operating in regulated industries, require comprehensive security frameworks to protect against loss of confidentiality, integrity, or availability of data, whether due to malice, accident or otherwise. Once such a security framework is in place, an organization must constantly monitor and assess the overall compliance of its systems to detect and rectify any issues found. This thesis presents a technique and a supporting toolkit to first model dependencies between security policies (referred to as controls) and, second, devise models that associate risk with policy violations. Third, devise algorithms that propagate risk when one or more policies are found to be non-compliant and fourth, propose a technique that evaluates the overall security posture risk of a system as a function of the non-compliant policies, the affected policies, and the time elapsed since these policy violations discovered but not have been mitigated yet. More specifically, the approach is based on modeling the dependencies between the different controls in the NIST 800.53 framework by compiling a dependency multi-graph, devising a fuzzy-reasoning-based risk assessment technique that traverses the dependency multi-graph and assigns an overall security exposure risk score when one or more controls fail, and finally a technique for identifying the strategies an attacker can use, given the failed controls, and for which an organization should defend itself. This approach allows organizations to obtain a bird’s-eye view of their Information Systems’ cyber security posture and help triage the security control checks by focusing on the most vulnerable parts of their Information System ecosystem

Run-time risk management in adaptive ICT systems

We will present results of the SERSCIS project related to risk management and mitigation strategies in adaptive multi-stakeholder ICT systems. The SERSCIS approach involves using semantic threat models to support automated design-time threat identification and mitigation analysis. The focus of this paper is the use of these models at run-time for automated threat detection and diagnosis. This is based on a combination of semantic reasoning and Bayesian inference applied to run-time system monitoring data. The resulting dynamic risk management approach is compared to a conventional ISO 27000 type approach, and validation test results presented from an Airport Collaborative Decision Making (A-CDM) scenario involving data exchange between multiple airport service providers

Defense against Insider Threat: a Framework for Gathering Goal-based Requirements

Insider threat is becoming comparable to outsider threat in frequency of security events. This is a worrying situation, since insider attacks have a high probability of success because insiders have authorized access and legitimate privileges. Despite their importance, insider threats are still not properly addressed by organizations. We contribute to reverse this situation by introducing a framework composed of a method for identification and assessment of insider threat risks and of two supporting deliverables for awareness of insider threat. The deliverables are: (i) attack strategies structured in four decomposition trees, and (ii) a matrix which correlates defense strategies, attack strategies and control principles. The method output consists of goal-based requirements for the defense against insiders

RISK ASSESSMENT OF MALICIOUS ATTACKS AGAINST POWER SYSTEMS

The new scenarios of malicious attack prompt for their deeper consideration and mainly when critical systems are at stake. In this framework, infrastructural systems, including power systems, represent a possible target due to the huge impact they can have on society. Malicious attacks are different in their nature from other more traditional cause of threats to power system, since they embed a strategic interaction between the attacker and the defender (characteristics that cannot be found in natural events or systemic failures). This difference has not been systematically analyzed by the existent literature. In this respect, new approaches and tools are needed. This paper presents a mixed-strategy game-theory model able to capture the strategic interactions between malicious agents that may be willing to attack power systems and the system operators, with its related bodies, that are in charge of defending them. At the game equilibrium, the different strategies of the two players, in terms of attacking/protecting the critical elements of the systems, can be obtained. The information about the attack probability to various elements can be used to assess the risk associated with each of them, and the efficiency of defense resource allocation is evidenced in terms of the corresponding risk. Reference defense plans related to the online defense action and the defense action with a time delay can be obtained according to their respective various time constraints. Moreover, risk sensitivity to the defense/attack-resource variation is also analyzed. The model is applied to a standard IEEE RTS-96 test system for illustrative purpose and, on the basis of that system, some peculiar aspects of the malicious attacks are pointed ou

Security, Privacy and Safety Risk Assessment for Virtual Reality Learning Environment Applications

Social Virtual Reality based Learning Environments (VRLEs) such as vSocial render instructional content in a three-dimensional immersive computer experience for training youth with learning impediments. There are limited prior works that explored attack vulnerability in VR technology, and hence there is a need for systematic frameworks to quantify risks corresponding to security, privacy, and safety (SPS) threats. The SPS threats can adversely impact the educational user experience and hinder delivery of VRLE content. In this paper, we propose a novel risk assessment framework that utilizes attack trees to calculate a risk score for varied VRLE threats with rate and duration of threats as inputs. We compare the impact of a well-constructed attack tree with an adhoc attack tree to study the trade-offs between overheads in managing attack trees, and the cost of risk mitigation when vulnerabilities are identified. We use a vSocial VRLE testbed in a case study to showcase the effectiveness of our framework and demonstrate how a suitable attack tree formalism can result in a more safer, privacy-preserving and secure VRLE system.Comment: Tp appear in the CCNC 2019 Conferenc