Towards Automating the Construction & Maintenance of Attack Trees: a Feasibility Study

Security risk management can be applied on well-defined or existing systems; in this case, the objective is to identify existing vulnerabilities, assess the risks and provide for the adequate countermeasures. Security risk management can also be applied very early in the system's development life-cycle, when its architecture is still poorly defined; in this case, the objective is to positively influence the design work so as to produce a secure architecture from the start. The latter work is made difficult by the uncertainties on the architecture and the multiple round-trips required to keep the risk assessment study and the system architecture aligned. This is particularly true for very large projects running over many years. This paper addresses the issues raised by those risk assessment studies performed early in the system's development life-cycle. Based on industrial experience, it asserts that attack trees can help solve the human cognitive scalability issue related to securing those large, continuously-changing system-designs. However, big attack trees are difficult to build, and even more difficult to maintain. This paper therefore proposes a systematic approach to automate the construction and maintenance of such big attack trees, based on the system's operational and logical architectures, the system's traditional risk assessment study and a security knowledge database.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

Digital Preservation Services : State of the Art Analysis

Research report funded by the DC-NET project.An overview of the state of the art in service provision for digital preservation and curation. Its focus is on the areas where bridging the gaps is needed between e-Infrastructures and efficient and forward-looking digital preservation services. Based on a desktop study and a rapid analysis of some 190 currently available tools and services for digital preservation, the deliverable provides a high-level view on the range of instruments currently on offer to support various functions within a preservation system.European Commission, FP7peer-reviewe

Design reuse research : a computational perspective

This paper gives an overview of some computer based systems that focus on supporting engineering design reuse. Design reuse is considered here to reflect the utilisation of any knowledge gained from a design activity and not just past designs of artefacts. A design reuse process model, containing three main processes and six knowledge components, is used as a basis to identify the main areas of contribution from the systems. From this it can be concluded that while reuse libraries and design by reuse has received most attention, design for reuse, domain exploration and five of the other knowledge components lack research effort

Towards Efficiency and Quality Assurance in Threat Analysis of Software Systems

Context: Security threats have been a growing concern in many organizations. Organizations developing software products strive to plan for security as soon as possible to mitigate such potential threats. In the design phase of the software development life-cycle, teams of experts routinely analyze the system architecture and design to nd potential security threats.Objective: The goal of this research is to improve on the performance of existing threat analysis techniques and support practitioners with automation and tool support. To understand the inner-workings of existing threat analysis methodologies we also conduct a systematic literature review examining 26 methodologies in detail. Our industrial partners conrm that existing techniques are labor intensive and do not provide quality guarantees about their outcomes.Method: We conducted empirical studies for building an in-depth understanding of existing techniques (Systematic Literature Review (SLR), controlled experiments). Further we rely on empirical case studies for ongoing validation of an attempted technique performance improvement.Findings: We have found that using a novel risk-rst approach can help reduce the labor while producing the same level of outcome quality in a shorter period of time. Further, we suggest that the key for a successful application of this approach is two fold. First, widening the analysis scope to end-to-end scenarios guides the analyst to focus on important assets. Second, appropriate model abstractions are required to manage the cognitive load of the human analysts. We have also found that reasoning about security in a formal setting requires extending the existing notations with security semantics. Further, minimal model extensions for doing so include security contracts for system nodes handling sensitive information. In such a setting, the analysis can be automated and can to some extent provide completeness guarantees.Future work: In the future, we plan to further study the analysis completeness guarantees. In particular, we plan to improve on the analysis automation and investigate complementary techniques for analysis completeness (namely informal pattern based techniques). We also plan to work on the disconnect between the planned and implemented security

Ontology learning for semantic web services

Semantic Web Services promise automatic service discovery and composition, relying heavily on domain ontology as a core component. With large Web Service repository, manual ontology development is proving a bottleneck (with associated expense and likely errors) to the realisation of a semantic Web of services. Providing the appropriate tools that assist in and automate ontology development is essential for a dynamic service vision to be realised. As a statement of research-in-progress, this paper proposes combining different ontology learning paradigms in Web Services domain, highlighting the need for further research that accommodates the variation in Web Service descriptive and operational sources. A research agenda is proposed that recognises this variation in artefacts as they are selected, pre-processed and analyzed by ontology learning techniques

Efficiency and Automation in Threat Analysis of Software Systems

Context: Security is a growing concern in many organizations. Industries developing software systems plan for security early-on to minimize expensive code refactorings after deployment. In the design phase, teams of experts routinely analyze the system architecture and design to find potential security threats and flaws. After the system is implemented, the source code is often inspected to determine its compliance with the intended functionalities. Objective: The goal of this thesis is to improve on the performance of security design analysis techniques (in the design and implementation phases) and support practitioners with automation and tool support.Method: We conducted empirical studies for building an in-depth understanding of existing threat analysis techniques (Systematic Literature Review, controlled experiments). We also conducted empirical case studies with industrial participants to validate our attempt at improving the performance of one technique. Further, we validated our proposal for automating the inspection of security design flaws by organizing workshops with participants (under controlled conditions) and subsequent performance analysis. Finally, we relied on a series of experimental evaluations for assessing the quality of the proposed approach for automating security compliance checks. Findings: We found that the eSTRIDE approach can help focus the analysis and produce twice as many high-priority threats in the same time frame. We also found that reasoning about security in an automated fashion requires extending the existing notations with more precise security information. In a formal setting, minimal model extensions for doing so include security contracts for system nodes handling sensitive information. The formally-based analysis can to some extent provide completeness guarantees. For a graph-based detection of flaws, minimal required model extensions include data types and security solutions. In such a setting, the automated analysis can help in reducing the number of overlooked security flaws. Finally, we suggested to define a correspondence mapping between the design model elements and implemented constructs. We found that such a mapping is a key enabler for automatically checking the security compliance of the implemented system with the intended design. The key for achieving this is two-fold. First, a heuristics-based search is paramount to limit the manual effort that is required to define the mapping. Second, it is important to analyze implemented data flows and compare them to the data flows stipulated by the design

A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft