Embedded System Security: A Software-based Approach

We present a body of work aimed at understanding and improving the security posture of embedded devices. We present results from several large-scale studies that measured the quantity and distribution of exploitable vulnerabilities within embedded devices in the world. We propose two host-based software defense techniques, Symbiote and Autotomic Binary Structure Randomization, that can be practically deployed to a wide spectrum of embedded devices in use today. These defenses are designed to overcome major challenges of securing legacy embedded devices. To be specific, our proposed algorithms are software- based solutions that operate at the firmware binary level. They do not require source-code, are agnostic to the operating-system environment of the devices they protect, and can work on all major ISAs like MIPS, ARM, PowerPC and X86. More importantly, our proposed defenses are capable of augmenting the functionality of embedded devices with a plethora of host-based defenses like dynamic firmware integrity attestation, binary structure randomization of code and data, and anomaly-based malcode detection. Furthermore, we demonstrate the safety and efficacy of the proposed defenses by applying them to a wide range of real- time embedded devices like enterprise networking equipment, telecommunication appliances and other commercial devices like network-based printers and IP phones. Lastly, we present a survey of promising directions for future research in the area of embedded security

Cluster-based Vulnerability Assessment of Operating Systems and Web Browsers

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) and web browsers they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs (Windows, Mac, IOS, and Linux) and four web browsers (Internet Explorer, Safari, Firefox, and Chrome). Out of the total eight OSs and web browsers we analyzed using a power-law model issued from a family of SRMs, the model was statistically adequate for modeling in six cases. For these cases, in terms of estimation and forecasting capability, our results, compared to a power-law model without clustering, are more accurate in all cases but one

Cluster-based Vulnerability Assessment Applied to Operating Systems

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed

Cluster-based Vulnerability Assessment Applied to Operating Systems

Organizations face the issue of how to best allocate their security resources. Thus, they need an accurate method for assessing how many new vulnerabilities will be reported for the operating systems (OSs) they use in a given time period. Our approach consists of clustering vulnerabilities by leveraging the text information within vulnerability records, and then simulating the mean value function of vulnerabilities by relaxing the monotonic intensity function assumption, which is prevalent among the studies that use software reliability models (SRMs) and nonhomogeneous Poisson process (NHPP) in modeling. We applied our approach to the vulnerabilities of four OSs: Windows, Mac, IOS, and Linux. For the OSs analyzed in terms of curve fitting and prediction capability, our results, compared to a power-law model without clustering issued from a family of SRMs, are more accurate in all cases we analyzed

Secure Configuration and Management of Linux Systems using a Network Service Orchestrator.

Manual management of the configuration of network devices and computing devices (hosts) is an error-prone task. Centralized automation of these tasks can lower the costs of management, but can also introduce unknown or unanticipated security risks. Misconfiguration (deliberate (by outsiders) or inadvertent (by insiders)) can expose a system to significant risks. Centralized network management has seen significant progress in recent years, resulting in model-driven approaches that are clearly superior to previous "craft" methods. Host management has seen less development. The tools available have developed in separate task-specific ways. This thesis explores two aspects of the configuration management problem for hosts: (1) implementing host management using the model-driven (network) management tools; (2) establishing the relative security of traditional methods and the above proposal for model driven host management. It is shown that the model-driven approach is feasible, and the security of the model driven approach is significantly higher than that of existing approaches

Security-Policy Analysis with eXtended Unix Tools

During our fieldwork with real-world organizations---including those in Public Key Infrastructure (PKI), network configuration management, and the electrical power grid---we repeatedly noticed that security policies and related security artifacts are hard to manage. We observed three core limitations of security policy analysis that contribute to this difficulty. First, there is a gap between policy languages and the tools available to practitioners. Traditional Unix text-processing tools are useful, but practitioners cannot use these tools to operate on the high-level languages in which security policies are expressed and implemented. Second, practitioners cannot process policy at multiple levels of abstraction but they need this capability because many high-level languages encode hierarchical object models. Finally, practitioners need feedback to be able to measure how security policies and policy artifacts that implement those policies change over time. We designed and built our eXtended Unix tools (XUTools) to address these limitations of security policy analysis. First, our XUTools operate upon context-free languages so that they can operate upon the hierarchical object models of high-level policy languages. Second, our XUTools operate on parse trees so that practitioners can process and analyze texts at multiple levels of abstraction. Finally, our XUTools enable new computational experiments on multi-versioned structured texts and our tools allow practitioners to measure security policies and how they change over time. Just as programmers use high-level languages to program more efficiently, so can practitioners use these tools to analyze texts relative to a high-level language. Throughout the historical transmission of text, people have identified meaningful substrings of text and categorized them into groups such as sentences, pages, lines, function blocks, and books to name a few. Our research interprets these useful structures as different context-free languages by which we can analyze text. XUTools are already in demand by practitioners in a variety of domains and articles on our research have been featured in various news outlets that include ComputerWorld, CIO Magazine, Communications of the ACM, and Slashdot

Instructional eLearning technologies for the vision impaired

The principal sensory modality employed in learning is vision, and that not only increases the difficulty for vision impaired students from accessing existing educational media but also the new and mostly visiocentric learning materials being offered through on-line delivery mechanisms. Using as a reference Certified Cisco Network Associate (CCNA) and IT Essentials courses, a study has been made of tools that can access such on-line systems and transcribe the materials into a form suitable for vision impaired learning. Modalities employed included haptic, tactile, audio and descriptive text. How such a multi-modal approach can achieve equivalent success for the vision impaired is demonstrated. However, the study also shows the limits of the current understanding of human perception, especially with respect to comprehending two and three dimensional objects and spaces when there is no recourse to vision