Privacy by design requires that developers address privacy concerns from the early stage of software development life cycle. It encourages them to take a proactive approach to privacy engineering by identifying personal data, creating conceptual data flow diagrams, and identifying privacy threats. We argue that by providing a tool that automates some of the steps can reduce the burden on development teams. We develop a tool called PrivacyStory, including an end-to-end privacy requirement generation from a set of user stories. The tool provides some automation, utilizing a current state-of-the art natural language processing model. The core aim of our tool is to assist development teams in becoming more agile in their approach to privacy requirements engineering.

Attack graph-based methods are a promising approach towards discovering attacks and various techniques have been proposed recently. A key limitation, however, is that approaches developed so far are monolithic in their architecture and heterogeneous in their internal models. The inflexible custom data models of existing prototypes and the implementation of rules in code rather than declarative languages on the one hand make it difficult to combine, extend, and reuse techniques, and on the other hand hinder reuse of security knowledge – including detection rules and threat intelligence. KRYSTAL tackles these challenges by providing a knowledge graph-based, modular framework for threat detection, attack graph and scenario reconstruction, and analysis based on RDF as a standard model for knowledge representation. This approach provides query options that facilitate contextualization over internal and external background knowledge, as well as the integration of multiple detection techniques, including tag propagation, attack signatures, and graph queries. We implemented our framework in an openly available prototype and demonstrate its applicability on multiple scenarios of the DARPA Transparent Computing dataset. Our evaluation shows that the combination of different threat detection techniques within our framework improved detection capabilities. Furthermore, we find that RDF provenance graphs are scalable and can efficiently support a variety of threat detection techniques.

Security professionals rely extensively on log data to monitor IT infrastructures and investigate potentially malicious activities. Existing systems support these tasks by collecting log messages in a database, from where log events can be queried and correlated. Such centralized approaches are typically based on a relational model and store log messages as plain text, which offers limited flexibility for the representation of heterogeneous log events and the connections between them. A knowledge graph representation can overcome such limitations and enable graph pattern-based log analysis, leveraging semantic relationships between objects that appear in heterogeneous log streams. In this paper, we present a method to dynamically construct such log knowledge graphs at query time, i.e., without a priori parsing, aggregation, processing, and materialization of log data. Specifically, we propose a method that – for a given query formulated in SPARQL – dynamically constructs a virtual log knowledge graph directly from heterogeneous raw log files across multiple hosts and contextualizes the result with internal and external background knowledge. We evaluate the approach across multiple heterogeneous log sources and machines and see encouraging results that indicate that the approach is viable and facilitates ad-hoc graph-analytic queries in federated settings.

Traditional forms of cyber security education mainly focus on knowledge transmission, which means that knowledge is perceived as a tangible object being transferred from an expert (i.e., the teacher) to a beginner. When practiced well, the learner may acquire such knowledge, but not the resilience to apply it in various contexts [1], [2]. This is especially troubling for the cyber security domain, given the dynamic and constantly changing nature of the field and the environments in which it is required. We therefore need forms of education that aim at understanding the interdisciplinary nature of the field of cyber security as well as at the development of joint action in context: being able to quickly analyse and understand evolving and possibly previously unseen situations and take collaborative action to prevent, detect and recover from incidents.

Digital forensics are becoming increasingly important for the investigation of computer-related crimes, white-collar crimes and massive hacker attacks. After an incident has been detected an appropriate incident response is usually initiated with the aim to mitigate the attack and ensure the recovery of the IT systems. Digital Forensics pursues the goal of acquiring evidence that will stand up in court for sentencing and sometimes opposes contradicting objectives of incident response approaches. The concept presented here provides a solution to strengthen the credibility of digital evidence during actions related to incident response. It adapts an approach for data provenance to accurately track the transformation of digital evidence. For this purpose, the affected system and the incident response systems are equipped with a whole system data provenance capturing mechanism and then data provenance is captured simultaneously during an incident response. Context information about the incident response is also documented. An adapted algorithm for sub-graph detection is used to identify similarities between two provenance graphs. By applying the proposed concept to a use case, the advantages are demonstrated and possibilities for further development are presented.

Threat intelligence sharing has become a cornerstone of cooperative and collaborative cybersecurity. Sources providing such data have become more widespread in recent years, ranging from public entities (driven by legislatorial changes) to commercial companies and open communities that provide threat intelligence in order to help organisations and individuals to better understand and assess the cyber threat landscape putting their systems at risk. Tool support to automatically process this information is emerging concurrently. It has been observed that the quality of information received by the sources varies significantly and that in order to assess the quality of a threat intelligence source it is not sufficient to only consider qualitative indications of the source itself, but it is necessary to monitor the data provided by the source continuously to be able to draw conclusions about the quality of information provided by a source. In this paper, we propose a methodology for evaluating cyber threat information sources based on quantitative parameters. The methodology aims to facilitate trust establishment to threat intelligence sources, based on a weighted evaluation method that allows each entity to adapt it to its own needs and priorities. The approach facilitates automated tools utilising threat intelligence, since information to be considered can be prioritised based on which source is trusted the most at the time the intelligence arrives.

Modern automobiles are considered semi-autonomous vehicles regarding new adaptive technologies. New cars consist of a vast number of electronic units for managing and controlling the functional safety in a vehicle. In the vehicular industry, safety and security are considered two sides for the same coin. Therefore, improving functional safety in the vehicular industry is essential to protect the vehicle from different attack scenarios. This work introduces an ontology-based model for security verification and validation in the vehicular domain. The model performs a series of logical quires and inference rules to ensure that the security requirements are fulfilled. It endeavors to enhance the current security state of a vehicle by selecting additional security requirements that can handle existence security weaknesses and meet the actual security goal.

Computation Intelligence has inspired many researchers to develop the capability of computers to learn and solve a complex task in real-world problems. In this work, we propose an Artificial Bee Colony (ABC) to deal with the Stock Selection problem. We apply a Sigmoid-based Discrete-Continuous model with ABC to select appropriate features for stock scoring. The empirical study tests the performance of ABC compared with Genetic Algorithm (GA) and Differential Evolution (DE) algorithm by using data from the Stock Exchange Thailand. The empirical results show that the novel model stock selection significantly outperforms in terms of both investment return, diversity and model robustness.

The goal of the project described in this paper is to describe a GDPR compliance checking model and tool for supporting the information exchange between CERTs. The paper first motivates the project, and then briefly discusses major aspects of GDPR, before presenting the developed model and the implemented prototype. A discussion and an outlook conclude the paper.

Internet technology has changed how people work, live, communicate, learn and entertain. The internet adoption is rising rapidly, thus creating a new industrial revolution named "Industry 4.0". Industry 4.0 is the use of automation and data transfer in manufacturing technologies. It fosters several technological concepts, one of these is the Internet of Things (IoT). IoT technology is based on a big network of machines, objects, or people called "things" interacting together to achieve a common goal. These things are continuously generating vast amounts of data. Data understanding, processing, securing and storing are significant challenges in the IoT technology which restricts its development. This paper presents a new reference IoT model for future smart IoT solutions called Cloud Web of Things (CloudWoT). CloudWoT aims to overcome these limitations by combining IoT with edge computing, semantic web, and cloud computing. Additionally, this work is concerned with the security issues which threatens data in IoT application domains.

The semantic web aims to describe information in terms of well-defined vocabularies and comprehends both data and knowledge to cope with meaning of data. Advanced search engines are used to retrieve precise information out of these knowledge resources. The main challenge is not only retrieving data but also how to keep data safe and protected against any form of attacks.

This paper describes an approach to the definition of requirements for CERT-Communication in a changing environment. CERTs play an outstanding role for the detection, analysis and mitigation of vulnerabilities, threats and cyber-attacks in a multistakeholder cyberspace on which society relies more and more. Furthermore CERTs are a very valuable backbone for national and regional (e.g. European Union) cyber strategies and their role is partly defined in national and European legislation. It can be difficult to bring these obligations in line with the current primarily informal communication channels of CERTs that rely on person to person trust. This paper is devoted to the question of which kind of communication requirements have to be fulfilled to best use and support the work of CERTs in this complex environment.

Information security has become interdependent, global and critical - it has become cybersecurity. In this complex environment, legal consideration and economic incentives are as integral to ensuring the security of information systems as the technological realization. In this paper, we argue that comprehensive cybersecurity requires that these three disciplines are considered together. To this end, we propose a legal analysis framework, which can can be used to study legal and economic requirements for cybersecurity in relation to technological realities. The framework yields concrete recommendations, which complex system and critical infrastructure stakeholders can utilize to improve security within their networks. The analysis framework aims to offer key stakeholders a better understanding of the legal and economic requirements for cybersecurity and provide them with recommendations that are in line with modern cybersecurity strategies, including the enhancement of cooperation and collaboration capabilities and the implementation of other state-of-the-art security mechanisms.

This paper describes an approach towards modelling the communication in and between CERTs, of CERTs with their constituents, and of CERTs with other stakeholders and partners. As achieving their sometimes diverging goals is essential for CERTs, an extended goal-scenario model is suggested.

Agile software development methods are often applied in volatile software development environments typically perceived as being difficult to tackle by traditional methods. Yet, only a minority of organizations is able to transfer to agile development effectively. This paper proposes a knowledge transfer framework supporting the transition to agile development with guidance on how to put knowledge transfer into action. In this framework, a knowledge transfer process consists of six components (i.e., problems, antecedents, knowledge, mechanisms, knowledge application, and outcomes) and flows through four distinct stages (i.e., Initiation, Implementation, Ramp-up, and Integration). In each stage, components interact with each other multi-directionally and play an important role depending on the stage's functionality. A set of knowledge transfer activities in each stage is also specified which aligns with agile ways, especially Scrum. The description of the application of the developed framework and lessons learned conclude the paper.

Attacks on Voice-over-IP calls happen frequently. A specific type of these attacks are toll-fraud attacks. The prevention of these attacks depends on understanding the attack patterns. These can be derived from communication records. However, these records contain privacy relevant information of the call participants. These records are also protected by a number of laws and regulations. To make an analysis privacy compliant, relevant laws and regulations need to be considered. We propose a method for changing communication records in such a way that the forensic analysis in VoIP attacks is possible and the privacy of the call participants is preserved. We define privacy requirements for communication records from laws, regulations and concerns of call participants. We also present patterns of communication records based upon real world examples. We further show a framework for privacy attack identification and privacy data minimisation for a structured analysis of communication records. Moreover, an analysis pattern for toll-fraud attacks states which relations in the communication records have to survive the data minimisation.

Voice-over-IP systems are quite frequently attacked with the intent of service theft. While VoIP security has been intensively researched in the past, devised solutions often demand significant changes to the VoIP systems. In addition, several solutions propose the filtering of telephone calls, but these solutions only have a limited focus on the privacy rights of the call participants. We propose a method for analyzing communication records with the primary purpose to prevent VoIP attacks. Moreover, our approach integrates with little effort into common VoIP usage scenarios. As an example we use the prevention of toll-fraud attacks as a running example. The analysis of the communication records, however, requires investigating personal information in the communication records, e.g., call habits and phone numbers. Consequently we give an overview of major US and EU laws and regulations to elicit privacy requirements. We also demonstrate how these requirements can be implemented using Comercial-Off-The-Shelf VoIP systems.

This paper describes the CDRAS (Call Detail Records Analysis System) system, the motivation behind it, its approach and its background. The system aims at dealing with the notorious Man-in-the-Middle attack in the context of VoIP. As the use of such a system constitutes leads to an interference with the privacy of users, the most relevant legal aspects related to this work are also briefly discussed.

The effective, efficient and continuous execution of business processes is crucial for meeting entrepreneurial goals. Business process modeling and simulation are used to enable desired business process optimizations. However, current approaches mainly focus on economic aspects while security aspects are dealt with in separate initiatives. This missing interconnection may lead to significant differences in improvement suggestions, such as the differing valuation of security investments (e.g., redundancy of systems). The major contribution of this paper is the introduction of a formal model that is capable of expressing the relations between threats, detection mechanisms, safeguards, recovery measures and their effects on business processes. This novel business process simulation capability paves the way for the evaluation of security investments at process design stage by allowing the consideration of stochastic influences of the occurrence of threats on process activities and resources in a unified way. A stylized business case outlines how our method can be applied to real world scenarios.

This paper describes a novel approach to combine the strengths of an automated presentation and argumentation support system with a classification of cybercriminals similar to the ones used in law enforcement work. The discussed concept is still in an early stage of development with no substantiated scientific results. The beginning of the paper is dedicated to the description of a prototype based on an automated forensic support system called ¿CFAA¿ (¿Computer Forensic Analyzer and Advisor¿). This description is followed by a short classification of current cybercriminals and their knowledge levels. This classification is a slight modification of the one described in "Scene of the Cybercrime" by Debra Littlejohn Shinder. The paper then continues with the presentation of an envisaged approach towards combining the software tool with the determined classification to increase the efficiency of the forensic analysis. The core aim of this paper is to demonstrate the possible increase of efficiency with adjusting the appropriate cybercriminal levels according to the forensic investigation.

So far, Computer-Assisted Language Learning (CALL) comes in many different flavors. Our research work focuses on developing an integrated e-learning environment that allows improving language skills in specific contexts. Integrated e-learning environment means that it is a Web-based solution that performs language learning tasks using common working environments like, for instance, Web browsers or Email clients. It should be accessible on different platforms, even on mobile devices. Natural Language Processing (NLP) forms the technological basis for developing such a learning framework. The paper gives an overview of the state-of-the-art in this area. Therefore, on the one hand, it explains creation processes for NLP resources and gives an overview of corpora. On the other hand, it describes existing NLP standards. Based on our requirements, the paper gives special attention to the evaluation and comparison of toolkits that can suitably support the planned implementation. An outlook at the end points out necessary developments in e-learning to keep in mind.

Driven by the steadily growing number of natural disasters, the threat of terrorist and other criminal attacks as well as changed legislation and regulations, companies are increasingly forced to prepare against threats that endanger the survivability of crucial business activities. As a consequence, management has to pay more attention to business continuity issues including serious management commitment and more appropriate funding. Business impact analysis and risk assessment concepts enable adequate business continuity planning as they deliver essential information about the impact of resources' disruption on business. In this paper we present how these concepts can be enhanced through the application of the ROPE (Risk-Oriented Process Evaluation) methodology enabling risk-aware business process management and simulation. Moreover, we present essential extensions of the ROPE simulation capabilities leading to a more efficient and effective business continuity planning.

Increasingly, companies face the challenges to perform their business processes effectively as well as efficiently and to simultaneously assure the continuity of these processes. As the majority of companies rely on IT, it is essential to establish effective incident handling. In this paper, we introduce new extensions of the risk-aware business process management framework ROPE (risk-oriented process evaluation) in order to support the improvement of the management and execution of business processes. We further discuss the advantages of those extensions and how they can support the implementation of standards and best-practices such as the NIST SP800-61 (Computer Security Incident Handling Guide).

Network operators gradually open their interfaces to formerly hidden services. This fosters the development of a new class of mobile applications that take into account context information such as the location of users. However, the development of location-based services also raises the issue of users location-privacy.

Network operators gradually open their interfaces to formerly hidden services. This fosters the development of a new class of mobile applications that take into account user's location and presence information. However, this development also raises problems especially the lack of protection of privacy in location-based services. This paper proposes a service architecture that is aimed at overcoming some of the shortages of currently existing context-aware applications that make use of network providers services as well as existing mobile payment systems. We therefore introduce the combination of tickets together with a novel privacy enhancing mechanism that is based on the notion of pseudonyms. Compared to other privacy enhancing solutions our pseudonym mechanism can also be implemented on mobile devices that have some restrictions regarding resources like memory or processing power. Due to their flexibility tickets can be used for many different kinds of applications. One important aspect in this respect is the highly postulated pay-as-you-go model. We give an example of a transport ticket application and explain the message interaction patterns for the basic functionalities of the systems, regarding aspects like data and privacy protection. This example further shows how 3rd party application providers can build meaningful mobile applications that are accepted by users

In this paper the author describes the approaches to blending learning he has pursued at the University of Vienna's Institute of Distributed and Multimedia Systems and at the University of South Australia's School of Computer and Information Science in an attempt to supply online students and on campus students with enhanced teaching and learning materials in an Information Security Management course

Purpose This paper seeks to provide an overview of the major technical, organizational and legal issues pertaining to the outsourcing of IS/IT security services. Design/methodology/approach The paper uses a combined socio‐technical approach to explore the different aspects of IS/IT security outsourcing and suggests a framework for accommodating security and privacy requirements that arise in outsourcing arrangements. Findings Data protection requirements are a decisive factor for IS/IT security outsourcing, not only because they pose restrictions to management, but also because security and privacy concerns are commonly cited among the most important concerns prohibiting organizations from IS/IT outsourcing. New emerging trends such as outsourcing in third countries, pose significant new issues, with regard to meeting data protection requirements. Originality/value The paper illustrates the reasons for which the outsourcing of IS/IT security needs to be examined under a different perspective from traditional IS/IT outsourcing. It focuses on the specific issue of personal data protection requirements that must be accommodated, according to the European Union directive.

The authors present a model for bringing the coordination power of workflow management systems to outdoor wearable augmented reality (AR) systems. They portray how mobile equipment may be integrated with adaptive, context-aware work environments. A scenario of a medical emergency task is described to illustrate the functionality of this form of collaboration system. Appropriate information stickers are introduced to support data collection in medical emergency scenarios in a sophisticated form through a hands-free user interface for medical personnel. They propose the use of new user interface technology, including multimedia, AR information stickers, and the allocation of patient medical records to identified locations of the human body. A key feature is the access to relevant information for users in the mobile environment as well as for those in the advanced control room. An additional advantage is the automatic recording of on-site data, which helps to build the medical record of a patient without interfering with the work of the emergency team.

Software development often suffers from well-known problems such as wrong schedules and cost estimations, low productivity, and low product quality. In order to overcome these problems we suggest adapting the concepts of "organizational memory" and "organizational learning" and we argue in favor of establishing a reuse culture of software process models. We introduce an approach based on the process definition/instantiation/enaction paradigm and on the reuse of explicit software process descriptions (process models). The key features of our approach are the division of process descriptions into a goal-oriented process definition document and a formal implementation-oriented process model on the one hand and the use of an artificial neural network, more precisely a self-organizing map, for classification and retrieval purposes on the other. We present an exposition of our approach and discuss the promising results of an experiment in structuring a software process library and retrieving reuse candidates for upcoming projects.

The conceptual and logical design of multilevel secure (MLS) database applications are treated in an integrated way. For the conceptual design, a powerful semantic data model is suggested in order to represent the data and security semantics of the application domain. For the logical design, a two-phase approach is developed. Phase one consists of the transformation of the database conceptualization into multilevel relational concepts, while phase two is concerned with integrity management. Enforcing the integrity in MLS databases is known to be a difficult task. Careful data modelling is a necessary prerequisite in order to arrive at consistent and secure MLS applications.>