Biblio

One hundred-sixty four participants from the United States, India and China completed a survey designed to assess past phishing experiences and whether they engaged in certain online safety practices (e.g., reading a privacy policy). The study investigated participants' reported agreement regarding the characteristics of phishing attacks, types of media where phishing occurs and the consequences of phishing. A multivariate analysis of covariance indicated that there were significant differences in agreement regarding phishing characteristics, phishing consequences and types of media where phishing occurs for these three nationalities. Chronological age and education did not influence the agreement ratings; therefore, the samples were demographically equivalent with regards to these variables. A logistic regression analysis was conducted to analyze the categorical variables and nationality data. Results based on self-report data indicated that (1) Indians were more likely to be phished than Americans, (2) Americans took protective actions more frequently than Indians by destroying old documents, and (3) Americans were more likely to notice the "padlock" security icon than either Indian or Chinese respondents. The potential implications of these results are discussed in terms of designing culturally sensitive anti-phishing solutions.

Information system developers and administrators often overlook critical security requirements and best practices. This may be due to lack of tools and techniques that allow practitioners to tailor security knowledge to their particular context. In order to explore the impact of new security methods, we must improve our ability to study the impact of security tools and methods on software and system development. In this paper, we present early findings of an experiment to assess the extent to which the number and type of examples used in security training stimuli can impact security problem solving. To motivate this research, we formulate hypotheses from analogical transfer theory in psychology. The independent variables include number of problem surfaces and schemas, and the dependent variable is the answer accuracy. Our study results do not show a statistically significant difference in performance when the number and types of examples are varied. We discuss the limitations, threats to validity and opportunities for future studies in this area.

Modeling and analyzing security of networked systems is an important problem in the emerging Science of Security and has been under active investigation. In this paper, we propose a new approach towards tackling the problem. Our approach is inspired by the shock model and random environment techniques in the Theory of Reliability, while accommodating security ingredients. To the best of our knowledge, our model is the first that can accommodate a certain degree of adaptiveness of attacks, which substantially weakens the often-made independence and exponential attack inter-arrival time assumptions. The approach leads to a stochastic process model with two security metrics, and we attain some analytic results in terms of the security metrics.

According to a 2011 survey in healthcare, the most commonly reported breaches of protected health information involved employees snooping into medical records of friends and relatives. Logging mechanisms can provide a means for forensic analysis of user activity in software systems by proving that a user performed certain actions in the system. However, logging mechanisms often inconsistently capture user interactions with sensitive data, creating gaps in traces of user activity. Explicit design principles and systematic testing of logging mechanisms within the software development lifecycle may help strengthen the overall security of software. The objective of this research is to observe the current state of logging mechanisms by performing an exploratory case study in which we systematically evaluate logging mechanisms by supplementing the expected results of existing functional black-box test cases to include log output. We perform an exploratory case study of four open-source electronic health record (EHR) logging mechanisms: OpenEMR, OSCAR, Tolven eCHR, and WorldVistA. We supplement the expected results of 30 United States government-sanctioned test cases to include log output to track access of sensitive data. We then execute the test cases on each EHR system. Six of the 30 (20%) test cases failed on all four EHR systems because user interactions with sensitive data are not logged. We find that viewing protected data is often not logged by default, allowing unauthorized views of data to go undetected. Based on our results, we propose a set of principles that developers should consider when developing logging mechanisms to ensure the ability to capture adequate traces of user activity.

The relationship between accountability and identity in online life presents many interesting questions. Here, we first systematically survey the various (directed) relationships among principals, system identities (nyms) used by principals, and actions carried out by principals using those nyms. We also map these relationships to corresponding accountability-related properties from the literature. Because punishment is fundamental to accountability, we then focus on the relationship between punishment and the strength of the connection between principals and nyms. To study this particular relationship, we formulate a utility-theoretic framework that distinguishes between principals and the identities they may use to commit violations. In doing so, we argue that the analogue applicable to our setting of the well known concept of quasilinear utility is insufficiently rich to capture important properties such as reputation. We propose more general utilities with linear transfer that do seem suitable for this model. In our use of this framework, we define notions of "open" and "closed" systems. This distinction captures the degree to which system participants are required to be bound to their system identities as a condition of participating in the system. This allows us to study the relationship between the strength of identity binding and the accountability properties of a system.

The Maude-NRL Protocol Analyzer (Maude-NPA) is a tool for reasoning about the security of cryptographic protocols in which the cryptosystems satisfy different equational properties. It tries to find secrecy or authentication attacks by searching backwards from an insecure attack state pattern that may contain logical variables, in such a way that logical variables become properly instantiated in order to find an initial state. The execution mechanism for this logical reachability is narrowing modulo an equational theory. Although Maude-NPA also possesses a forwards semantics naturally derivable from the backwards semantics, it is not suitable for state space exploration or protocol simulation. In this paper we define an executable forwards semantics for Maude-NPA, instead of its usual backwards one, and restrict it to the case of concrete states, that is, to terms without logical variables. This case corresponds to standard rewriting modulo an equational theory. We prove soundness and completeness of the backwards narrowing-based semantics with respect to the rewriting-based forwards semantics. We show its effectiveness as an analysis method that complements the backwards analysis with new prototyping, simulation, and explicit-state model checking features by providing some experimental results.

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.

Sandboxes impose a security policy, isolating applications and their components from the rest of a system. While many sandboxing techniques exist, state of the art sandboxes generally perform their functions within the system that is being defended. As a result, when the sandbox fails or is bypassed, the security of the surrounding system can no longer be assured. We experiment with the idea of in-nimbo sandboxing, encapsulating untrusted computations away from the system we are trying to protect. The idea is to delegate computations that may be vulnerable or malicious to virtual machine instances in a cloud computing environment. This may not reduce the possibility of an in-situ sandbox compromise, but it could significantly reduce the consequences should that possibility be realized. To achieve this advantage, there are additional requirements, including: (1) A regulated channel between the local and cloud environments that supports interaction with the encapsulated application, (2) Performance design that acceptably minimizes latencies in excess of the in-situ baseline. To test the feasibility of the idea, we built an in-nimbo sandbox for Adobe Reader, an application that historically has been subject to significant attacks. We undertook a prototype deployment with PDF users in a large aerospace firm. In addition to thwarting several examples of existing PDF-based malware, we found that the added increment of latency, perhaps surprisingly, does not overly impair the user experience with respect to performance or usability.