Biblio

Contemporary enterprise systems focus primarily on performance and development/maintenance costs. Dealing with cyber-threats and system compromise is relegated to good coding (i.e., defensive programming) and secure environment (e.g., patched OS, firewalls, etc.). This approach, while a necessary start, is not sufficient. Such security relies on no missteps, and compromise only need a single flaw; consequently, we must design for compromise and mitigate its impact. One approach is to utilize fine-grained modularization and isolation. In such a system, decomposition ensures that compromise of a single module presents limited and known risk to data/resource theft and denial. We propose mechanisms for automating such modular composition and consider its system performance impact.

Quantum Key Distribution (QKD) is a revolutionary technology which leverages the laws of quantum mechanics to distribute cryptographic keying material between two parties with theoretically unconditional security. Terrestrial QKD systems are limited to distances of \textbackslashtextless;200 km in both optical fiber and line-of-sight free-space configurations due to severe losses during single photon propagation and the curvature of the Earth. Thus, the feasibility of fielding a low Earth orbit (LEO) QKD satellite to overcome this limitation is being explored. Moreover, in August 2016, the Chinese Academy of Sciences successfully launched the world's first QKD satellite. However, many of the practical engineering performance and security tradeoffs associated with space-based QKD are not well understood for global secure key distribution. This paper presents several system-level considerations for modeling and studying space-based QKD architectures and systems. More specifically, this paper explores the behaviors and requirements that researchers must examine to develop a model for studying the effectiveness of QKD between LEO satellites and ground stations.

Modern industrial control systems (ICSes) are increasingly adopting Internet technology to boost control efficiency, which unfortunately opens up a new frontier for cyber-security. People have typically applied existing Internet security techniques, such as firewalls, or anti-virus or anti-spyware software. However, those security solutions can only provide fine-grained protection at single devices. To address this, we design a novel software-defined networking (SDN) architecture that offers the global visibility of a control network infrastructure, and we investigate innovative SDN-based applications with the focus of ICS security, such as network verification and self-healing phasor measurement unit (PMU) networks. We are also conducting rigorous evaluation using the IIT campus microgrid as well as a high-fidelity testbed combining network emulation and power system simulation.

SDN’s logically centralized control provides an insertion point for programming the network. While it is generally agreed that higherlevel abstractions are needed to make that programming easy, there is little consensus on what are the “right” abstractions. Indeed, as SDN moves beyond its initial specialized deployments to broader use cases, it is likely that network control applications will require diverse abstractions that evolve over time. To this end, we champion a perspective that SDN control fundamentally revolves around data representation. We discard any application-specific structure that might be outgrown by new demands. Instead, we adopt a plain data representation of the entire network — network topology, forwarding, and control applications — and seek a universal data language that allows application programmers to transform the primitive representation into any high-level representations presented to applications or network operators. Driven by this insight, we present a system, Ravel, that implements an entire SDN network control infrastructure within a standard SQL database. In Ravel, network abstractions take the form of user-defined SQL views expressed by SQL queries that can be added on the fly. A key challenge in realizing this approach is to orchestrate multiple simultaneous abstractions that collectively affect the same underlying data. To achieve this, Ravel enhances the database with novel data integration mechanisms that merge the multiple views into a coherent forwarding behavior. Moreover, Ravel is exposed to applications through the one simple, familiar and highly interoperable SQL interface. While this is an ambitious long-term goal, our prototype built on the PostgreSQL database exhibits promising performance even for large scale networks.

We present an architecture for the Security Behavior Observatory (SBO), a client-server infrastructure designed to collect a wide array of data on user and computer behavior from hundreds of participants over several years. The SBO infrastructure had to be carefully designed to fulfill several requirements. First, the SBO must scale with the desired length, breadth, and depth of data collection. Second, we must take extraordinary care to ensure the security of the collected data, which will inevitably include intimate participant behavioral data. Third, the SBO must serve our research interests, which will inevitably change as collected data is analyzed and interpreted. This short paper summarizes some of our design and implementation benefits and discusses a few hurdles and trade-offs to consider when designing such a data collection system.

Security features are often hardwired into software applications, making it difficult to adapt security responses to reflect changes in runtime context and new attacks. In prior work, we proposed the idea of architecture-based self-protection as a way of separating adaptation logic from application logic and providing a global perspective for reasoning about security adaptations in the context of other business goals. In this paper, we present an approach, based on this idea, for combating denial-of-service (DoS) attacks. Our approach allows DoS-related tactics to be composed into more sophisticated mitigation strategies that encapsulate possible responses to a security problem. Then, utility-based reasoning can be used to consider different business contexts and qualities. We describe how this approach forms the underpinnings of a scientific approach to self-protection, allowing us to reason about how to make the best choice of mitigation at runtime. Moreover, we also show how formal analysis can be used to determine whether the mitigations cover the range of conditions the system is likely to encounter, and the effect of mitigations on other quality attributes of the system. We evaluate the approach using the Rainbow self-adaptive framework and show how Rainbow chooses DoS mitigation tactics that are sensitive to different business contexts.

The Symposium and Bootcamp on the Science of Security (HotSoS), is a research event centered on the Science of Security (SoS). Following a successful invitational SoS Community Meeting in December 2012, HotSoS 2014 was the first open research event in what we expect will be a continuing series of such events. The key motivation behind developing a Science of Security is to address the fundamental problems of cybersecurity in a principled manner. Security has been intensively studied, but a lot of previous research emphasizes the engineering of specific solutions without first developing the scientific understanding of the problem domain. All too often, security research conveys the flavor of identifying specific threats and removing them in an apparently ad hoc manner. The motivation behind the nascent Science of Security is to understand how computing systems are architected, built, used, and maintained with a view to understanding and addressing security challenges systematically across their life cycle. In particular, two features distinguish the Science of Security from previous research programs on cybersecurity. Scope. The Science of Security considers not just computational artifacts but also incorporates the human, social, and organizational aspects of computing within its purview. Approach. The Science of Security takes a decidedly scientific approach, based on the understanding of empirical evaluation and theoretical foundations as developed in the natural and social sciences, but adapted as appropriate for the "artificial science" (paraphrasing Herb Simon's term) that is computing.