Biblio

We propose Cupid, a language for specifying commitments that supports their information-centric aspects, and offers crucial benefits.  One, Cupid is first-order, enabling a systematic treatment of commitment instances.  Two, Cupid supports features needed for real-world scenarios such as deadlines, nested commitments, and complex event expressions for capturing the lifecycle of commitment instances.  Three, Cupid maps to relational database queries and thus provides a set-based semantics for retrieving commitment instances in states such as being violated,discharged, and so on.  We prove that Cupid queries are safe.  Four,to aid commitment modelers, we propose the notion of well-identified commitments, and finitely violable and finitely expirable commitments.  We give syntactic restrictions for obtaining such commitments.

Breaches of software security affect millions of people, and therefore it is crucial to strive for more secure software systems. However, the effect of programming language design on software security is not easily measured or studied. In the absence of scientific insight, opinions range from those that claim that programming language design has no effect on security of the system, to those that believe that programming language design is the only way to provide “high-assurance software.” In this paper, we discuss how programming language design can impact software security by looking at a specific example: the Wyvern programming language. We report on how the design of the Wyvern programming language leverages security principles, together with hypotheses about how usability impacts security, in order to prevent command injection attacks. Furthermore, we discuss what security principles we considered in Wyvern’s design.

Phishing is a social engineering tactic that targets internet users in an attempt to trick them into divulging personal information. When opening an email, users are faced with the decision of determining if an email is legitimate or an attempt at phishing. Although software has been developed to assist the user, studies have shown they are not foolproof, leaving the user vulnerable. Multiple training programs have been developed to educate users in their efforts to make informed decisions; however, training that conveys the real world consequences of phishing or training that increases a user’s fear level have not been developed. Conveying real world consequences of a situation and increasing a user’s fear level have been proven to enhance the effects of training in other fields. Ninety-six participants were recruited and randomly assigned to training programs with phishing consequences, training programs designed to increase fear, or a control group. Preliminary results indicate that training helped users identify phishing emails; however, little difference was seen among the three groups. Future analysis will include a factor analysis of personality and individual differences that influence training efficacy.

Static types may be used both by the language implementation and directly by the user as documentation. Though much existing work focuses primarily on the implications of static types on the semantics of programs, relatively little work considers the impact on usability that static types provide. Though the omission of static type information may decrease program length and thereby improve readability, it may also decrease readability because users must then frequently derive type information manually while reading programs. As type inference becomes more popular in languages that are in widespread use, it is important to consider whether the adoption of type inference may impact productivity of developers.

Web applications must ultimately command systems like web browsers and database engines using strings. Strings derived from improperly sanitized user input can as a result be a vector for command injection attacks. In this paper, we introduce regular string types, which classify strings constrained statically to be in a regular language specified by a regular expression. Regular strings support standard string operations like concatenation and substitution, as well as safe coercions, so they can be used to implement, in an essentially conventional manner, the pieces of a web application or framework that handle strings arising from user input. Simple type annotations at function interfaces can be used to statically verify that sanitization has been performed correctly without introducing redundant run-time checks. We specify this type system first as a minimal typed lambda calculus, lambdaRS. To be practical, adopting a specialized type system like this should not require the adoption of a new programming language. Instead, we advocate for extensible type systems: new type system fragments like this should be implemented as libraries atop a mechanism that guarantees that they can be safely composed. We support this with two contributions. First, we specify a translation from lambdaRS to a calculus with only standard strings and regular expressions. Then, taking Python as a language with these constructs, we implement the type system together with the translation as a library using typy, an extensible static type system for Python.

Breaches of software security affect millions of people, and therefore it is crucial to strive for more secure software systems. However, the effect of programming language design on software security is not easily measured or studied. In the absence of scientific insight, opinions range from those that claim that programming language design has no effect on security of the system, to those that believe that programming language design is the only way to provide “high-assurance software.” In this paper, we discuss how programming language design can impact software security by looking at a specific example: the Wyvern programming language. We report on how the design of the Wyvern programming language leverages security principles, together with hypotheses about how usability impacts security, in order to prevent command injection attacks. Furthermore, we discuss what security principles we considered in Wyvern’s design. 

State estimation plays a critically important role in ensuring the secure and reliable operation of the electric grid. Recent works have shown that the state estimation process is vulnerable to stealthy attacks where an adversary can alter certain measurements to corrupt the solution of the process, but evade the existing bad data detection algorithms and remain invisible to the system operator. Since the state estimation result is used to compute optimal power flow and perform contingency analysis, incorrect estimation can undermine economic and secure system operation. However, an adversary needs sufficient resources as well as necessary knowledge to achieve a desired attack outcome. The knowledge that is required to launch an attack mainly includes the measurements considered in state estimation, the connectivity among the buses, and the power line admittances. Uncertainty in information limits the potential attack space for an attacker. This advantage of uncertainty enables us to apply moving target defense (MTD) strategies for developing a proactive defense mechanism for state estimation.

In this paper, we propose an MTD mechanism for securing state estimation, which has several characteristics: (i) increase the knowledge uncertainty for attackers, (ii) reduce the window of attack opportunity, and (iii) increase the attack cost. In this mechanism, we apply controlled randomization on the power grid system properties, mainly on the set of measurements that are considered in state estimation, and the topology, especially the line admittances. We thoroughly analyze the performance of the proposed mechanism on the standard IEEE 14- and 30-bus test systems.

We investigate strong normalization, confluence, and behavioral equality in the realm of session-based concurrency. These interrelated issues underpin advanced correctness analysis in models of structured communications. The starting point for our study is an interpretation of linear logic propositions as session types for communicating processes, proposed in prior work. Strong normalization and confluence are established by developing a theory of logical relations. Defined upon a linear type structure, our logical relations remain remarkably similar to those for functional languages. We also introduce a natural notion of observational equivalence for session-typed processes. Strong normalization and confluence come in handy in the associated coinductive reasoning: as applications, we prove that all proof conversions induced by the logic interpretation actually express observational equivalences, and explain how type isomorphismsresulting from linear logic equivalences are realized by coercions between interface types of session-based concurrent systems.

Growing traffic volumes and the increasing complexity of attacks pose a constant scaling challenge for network intrusion prevention systems (NIPS). In this respect, offloading NIPS processing to compute clusters offers an immediately deployable alternative to expensive hardware upgrades. In practice, however, NIPS offloading is challenging on three fronts in contrast to passive network security functions: (1) NIPS offloading can impact other traffic engineering objectives; (2) NIPS offloading impacts user perceived latency; and (3) NIPS actively change traffic volumes by dropping unwanted traffic. To address these challenges, we present the SNIPS system. We design a formal optimization framework that captures tradeoffs across scalability, network load, and latency. We provide a practical implementation using recent advances in software-defined networking without requiring modifications to NIPS hardware. Our evaluations on realistic topologies show that SNIPS can reduce the maximum load by up to 10× while only increasing the latency by 2%.

Central to the secure operation of a public key infrastructure (PKI) is the ability to revoke certificates. While much of users' security rests on this process taking place quickly, in practice, revocation typically requires a human to decide to reissue a new certificate and revoke the old one. Thus, having a proper understanding of how often systems administrators reissue and revoke certificates is crucial to understanding the integrity of a PKI. Unfortunately, this is typically difficult to measure: while it is relatively easy to determine when a certificate is revoked, it is difficult to determine whether and when an administrator should have revoked.

In this paper, we use a recent widespread security vulnerability as a natural experiment. Publicly announced in April 2014, the Heartbleed OpenSSL bug, potentially (and undetectably) revealed servers' private keys. Administrators of servers that were susceptible to Heartbleed should have revoked their certificates and reissued new ones, ideally as soon as the vulnerability was publicly announced.

Using a set of all certificates advertised by the Alexa Top 1 Million domains over a period of six months, we explore the patterns of reissuing and revoking certificates in the wake of Heartbleed. We find that over 73% of vulnerable certificates had yet to be reissued and over 87% had yet to be revoked three weeks after Heartbleed was disclosed. Moreover, our results show a drastic decline in revocations on the weekends, even immediately following the Heartbleed announcement. These results are an important step in understanding the manual processes on which users rely for secure, authenticated communication.

We have been studying extension of the classical Software Reliability Engineering (SRE) methodology into the security space. We combine “classical” reliability modeling, when applied to reported vulnerabilities found under “normal” operational profile conditions, with safety oriented fault management processes. We illustrate with open source Fedora software.

Our initial results appear to indicate that generation of a repeatable automated test-strategy that would explicitly cover the “top 25” security problems may help considerably – eliminating perhaps as much as 50% of the field observable problems. However, genuine aleatoric and more process oriented incomplete analysis and design flaws remain. While we have made some progress in identifying focus areas, a number of questions remain, and we continue working on them.