Helping forensic analysts to attribute cyber-attacks: an argumentation-based reasoner

Discovering who performed a cyber-attack or from where it originated is essential in order to determine an appropriate response and future risk mitigation measures. In this work, we propose a novel argumentation-based reasoner for analyzing and attributing cyber-attacks that combines both technical and social evidence. Our reasoner helps the digital forensics analyst during the analysis of the forensic evidence by providing to the analyst the possible culprits of the attack, new derived evidence, hints about missing evidence, and insights about other paths of investigation. The proposed reasoner is flexible, deals with conflicting and incomplete evidence, and was tested on real cyber-attacks cases

A hybrid threat model for smart systems

Cyber-physical systems and their smart components have a pervasive presence in all our daily activities. Unfortunately, identifying the potential threats and issues in these systems and selecting enough protection is challenging given that such environments combine human, physical and cyber aspects to the system design and implementation. Current threat models and analysis do not take into consideration all three aspects of the analyzed system, how they can introduce new vulnerabilities or protection measures to each other. In this work, we introduce a novel threat model for cyber-physical systems that combines the cyber, physical, and human aspects. Our model represents the system's components relations and security properties by taking into consideration these three aspects. Together with the threat model we also propose a threat analysis method that allows understanding the security state of the system's components. The threat model and the threat analysis have been implemented into an automatic tool, called TAMELESS, that automatically analyzes threats to the system, verifies its security properties, and generates a graphical representation, useful for security architects to identify the proper prevention/mitigation solutions. We show and prove the use of our threat model and analysis with three cases studies from different sectors

Decision-making in policy governed human-autonomous systems teams

Policies govern choices in the behavior of systems. They are applied to human behavior as well as to the behavior of autonomous systems but are defined differently in each case. Generally humans have the ability to interpret the intent behind the policies, to bring about their desired effects, even occasionally violating them when the need arises. In contrast, policies for automated systems fully define the prescribed behavior without ambiguity, conflicts or omissions. The increasing use of AI techniques and machine learning in autonomous systems such as drones promises to blur these boundaries and allows us to conceive in a similar way more flexible policies for the spectrum of human-autonomous systems collaborations. In coalition environments this spectrum extends across the boundaries of authority in pursuit of a common coalition goal and covers collaborations between human and autonomous systems alike. In social sciences, social exchange theory has been applied successfully to explain human behavior in a variety of contexts. It provides a framework linking the expected rewards, costs, satisfaction and commitment to explain and anticipate the choices that individuals make when confronted with various options. We discuss here how it can be used within coalition environments to explain joint decision making and to help formulate policies re-framing the concepts where appropriate. Social exchange theory is particularly attractive within this context as it provides a theory with “measurable” components that can be readily integrated in machine reasoning processes

Time-stamped claim logic

The main objective of this paper is to define a logic for reasoning about distributed time-stamped claims. Such a logic is interesting for theoretical reasons, i.e., as a logic per se, but also because it has a number of practical applications, in particular when one needs to reason about a huge amount of pieces of evidence collected from different sources, where some of the pieces of evidence may be contradictory and some sources are considered to be more trustworthy than others. We introduce the Time-Stamped Claim Logic including a sound and complete sequent calculus. In order to show how Time-Stamped Claim Logic can be used in practice, we consider a concrete cyber-attribution case study

A hybrid threat model for smart systems

Cyber-physical systems and their smart components have a pervasive presence in all our daily activities. Unfortunately, identifying the potential threats and issues in these systems and selecting enough protection is challenging given that such environments combine human, physical and cyber aspects to the system design and implementation. Current threat models and analysis do not take into consideration all three aspects of the analyzed system, how they can introduce new vulnerabilities or protection measures to each other. In this work, we introduce a novel threat model for cyber-physical systems that combines the cyber, physical, and human aspects. Our model represents the system’s components relations and security properties by taking into consideration these three aspects. Together with the threat model we also propose a threat analysis method that allows understanding the security state of the system’s components. The threat model and the threat analysis have been implemented into an automatic tool, called TAMELESS, that automatically analyzes threats to the system, verifies its security properties, and generates a graphical representation, useful for security architects to identify the proper prevention/mitigation solutions. We show and prove the use of our threat model and analysis with three cases studies from different sector

Towards a Framework for Automatic Firewalls Configuration via Argumentation Reasoning

Firewalls have been widely used to protect not only small and local networks but also large enterprise networks. The configuration of firewalls is mainly done by network administrators, thus, it suffers from human errors. This paper aims to solve the network administrators' problem by introducing a formal approach that helps to configure centralized and distributed firewalls and automatically generate conflict-free firewall rules. We propose a novel framework, called ArgoFiCo, which is based on argumentation reasoning. Our framework automatically populates the firewalls of a network, given the network topology and the high-level requirements that represent how the network should behave. ArgoFiCo provides two strategies for firewall rules distribution

Access control and quality attributes of open data: Applications and techniques

Open Datasets provide one of the most popular ways to acquire insight and information about individuals, organizations and multiple streams of knowledge. Exploring Open Datasets by applying comprehensive and rigorous techniques for data processing can provide the ground for innovation and value for everyone if the data are handled in a legal and controlled way. In our study, we propose an argumentation and abductive reasoning approach for data processing which is based on the data quality background. Explicitly, we draw on the literature of data management and quality for the attributes of the data, and we extend this background through the development of our techniques. Our aim is to provide herein a brief overview of the data quality aspects, as well as indicative applications and examples of our approach. Our overall objective is to bring serious intent and propose a structured way for access control and processing of open data with a focus on the data quality aspects

Access control and quality attributes of open data: Applications and techniques

Open Datasets provide one of the most popular ways to acquire insight and information about individuals, organizations and multiple streams of knowledge. Exploring Open Datasets by applying comprehensive and rigorous techniques for data processing can provide the ground for innovation and value for everyone if the data are handled in a legal and controlled way. In our study, we propose an argumentation and abductive reasoning approach for data processing which is based on the data quality background. Explicitly, we draw on the literature of data management and quality for the attributes of the data, and we extend this background through the development of our techniques. Our aim is to provide herein a brief overview of the data quality aspects, as well as indicative applications and examples of our approach. Our overall objective is to bring serious intent and propose a structured way for access control and processing of open data with a focus on the data quality aspects

Next generation firewalls for dynamic coalitions

Firewalls represent a critical security building block for networks as they monitor and control incoming and outgoing network traffic based on the enforcement of predetermined secu- rity rules, referred to as firewall rules. Firewalls are constantly being improved to enhance network security. From being a simple filtering device, firewall has been evolved to operate in conjunc- tion in intrusion detection and prevention systems. This paper reviews the existing firewall policies and assesses their application in highly dynamic networks such as coalitions networks. The paper also describe the need for the next-generation firewall policies and how the generative policy model can be leveraged

Policy support for autonomous swarms of drones

In recent years drones have become more widely used in military and non-military applications. Automation of these drones will become more important as their use increases. Individual drones acting autonomously will be able to achieve some tasks, but swarms of autonomous drones working together will be able to achieve much more complex tasks and be able to better adapt to changing environments. In this paper we describe an example scenario involving a swarm of drones from a military coalition and civil/humanitarian organisations that are working collaboratively to monitor areas at risk of flooding. We provide a definition of a swarm and how they can operate by exchanging messages. We define a flexible set of policies that are applicable to our scenario that can be easily extended to other scenarios or policy paradigms. These policies ensure that the swarms of drones behave as expected (e.g., for safety and security). Finally we discuss the challenges and limitations around policies for autonomous swarms and how new research, such as generative policies, can aid in solving these limitations