Explainability and transparency of computations, as well as compliance with data-privacy requirements, presuppose an understanding of whether some input plays a non-trivial role in computing an output. However, difficulty in distinguishing between correlation and actual usage in computation, along with possible correlations between inputs, makes determination of such accountability challenging. A flow definition is presented that can make this distinction. The definition enables the construction of accountability evidence to establish how an input is computed based on an output, in terms of the intermediate variables used. Intermediate variables can also serve as mediation points that fully block information flow from an input to an output. A connection between accountability and mediation is established by showing the role of mediation points for constructing accountability evidence.

Maintaining legacy software requires many software and systems engineering hours. Assembly code programs, which demand low-level control over the computer machine state and have no variable names, are particularly difficult for humans to analyze. Existing conventional program translators guarantee correctness, but are hand-engineered for the source and target programming languages in question. Learned transpilation, i.e. automatic translation of code, offers an alternative to manual re-writing and engineering efforts. Automated symbolic program translation approaches guarantee correctness but struggle to scale to longer programs due to the exponentially large search space. Their rigid rule-based systems also limit their expressivity, so they can only reason about a reduced space of programs. Probabilistic neural language models (LMs) produce plausible outputs for every input, but do so at the cost of guaranteed correctness. In this work, we leverage the strengths of LMs and symbolic solvers in a neurosymbolic approach to learned transpilation for assembly code. Assembly code is an appropriate setting for a neurosymbolic approach, since assembly code can be divided into shorter non-branching basic blocks amenable to the use of symbolic methods. Guess & Sketch extracts alignment and confidence information from features of the LM then passes it to a symbolic solver to resolve semantic equivalence of the transpilation input and output. We test Guess & Sketch on three different test sets of assembly transpilation tasks, varying in difficulty, and show that it successfully transpiles 57.6% more examples than GPT-4 and 39.6% more examples than an engineered transpiler. We also share a training and evaluation dataset for this task.

With its combination of Datalog, SMT solving, and functional programming, the language Formulog provides an appealing mix of features for implementing SMT-based static analyses (e.g., refinement type checking, symbolic execution) in a natural, declarative way. At the same time, the performance of its custom Datalog solver can be an impediment to using Formulog beyond prototyping—a common problem for Datalog variants that aspire to solve large problem instances. In this work we speed up Formulog evaluation, with some surprising results: while 2.2× speedups can be obtained by using the conventional techniques for high-performance Datalog (e.g., compilation, specialized data structures), the big wins come by abandoning the central assumption in modern performant Datalog engines, semi-naive Datalog evaluation. In the place of semi-naive evaluation, we develop eager evaluation, a concurrent Datalog evaluation algorithm that explores the logical inference space via a depth-first traversal order. In practice, eager evaluation leads to an advantageous distribution of Formulog’s SMT workload to external SMT solvers and improved SMT solving times: our eager evaluation extensions to the Formulog interpreter and Soufflé’s code generator achieve mean 5.2× and 7.6× speedups, respectively, over the optimized code generated by off-the-shelf Soufflé on SMT-heavy Formulog benchmarks. All in all, using compilation and eager evaluation (as appropriate), Formulog implementations of refinement type checking, bottom-up pointer analysis, and symbolic execution achieve speedups on 20 out of 23 benchmarks over previously published, hand-tuned analyses written in F♯, Java, and C++, providing strong evidence that Formulog can be the basis of a realistic platform for SMT-based static analysis. Moreover, our experience adds nuance to the conventional wisdom that traditional semi-naive evaluation is the one-size-fits-all best Datalog evaluation algorithm for static analysis workloads.

This paper contributes a formal framework for quantitative analysis of bounded sensor attacks on cyber-physical systems, using the formalism of differential dynamic logic. Given a precondition and postcondition of a system, we formalize two quantitative safety notions, quantitative forward and backward safety, which respectively express (1) how strong the strongest postcondition of the system is with respect to the specified postcondition, and (2) how strong the specified precondition is with respect to the weakest precondition of the system needed to ensure the specified postcondition holds. We introduce two notions, forward and backward robustness, to characterize the robustness of a system against sensor attacks as the loss of safety. Two simulation distances, which respectively characterize upper bounds of the degree of forward and backward safety loss caused by the sensor attacks, are developed to reason with robustness. We verify the two simulation distances by expressing them as formulas of differential dynamic logic. We showcase an example of an autonomous vehicle that needs to avoid a collision.

In authorization logics, it is natural to treat computations as principals, since systems need to decide how much authority to give computations when they execute. But unlike other kinds of principals, the authority that we want to give to computations might be based on properties of the computation itself, such as whether the computation is differentially private, or whether the computation is memory safe. Existing authorization logics do not treat computation principals specially. Instead, they identify computation principals using a brittle hash-based naming scheme: minor changes to the code produce a distinct principal, even if the new computation is equivalent to the original one. Moreover, existing authorization logics typically treat computation principals as "black boxes," leaving any reasoning about the structure, semantics, or other properties of the computation out of the logic. We introduce Coal, a novel programming-language calculus that embeds an authorization logic in its type system via the Curry- Howard isomorphism. A key innovation of Coal is computation principals: computations that can be treated like other principals but also allow reasoning about the computation itself. Critically, Coal allows equivalent computations to be treated as equivalent principals, avoiding the brittleness of identity-based approaches to computation principals. Coal enables us to cleanly express fine-grained access control policies that are dependent on the structure and semantics of computations, such as expressing trust in all computations that are analyzed to be differentially private by any program analyzer that has been verified correct.

Given a set of candidate Datalog rules, the Datalog synthesis-as-rule-selection problem chooses a subset of these rules that satisfies a specification (such as an input-output example). Building off prior work using counterexample-guided inductive synthesis, we present a progression of three solver-based approaches for solving Datalog synthesis-as-rule-selection problems. Two of our approaches offer some advantages over existing approaches, and can be used more generally to solve arbitrary SMT formulas containing Datalog predicates; the third—an encoding into standard, off-the-shelf answer set programming (ASP)—leads to significant speedups (∼ 9× geomean) over the state of the art while synthesizing higher quality programs. Our progression of solutions explores the space of interactions between SAT/SMT and Datalog, identifying ASP as a promising tool for working with and reasoning about Datalog. Along the way, we identify Datalog programs as monotonic SMT theories, which enjoy particularly efficient interactions in SMT; our plugins for popular SMT solvers make it easy to load an arbitrary Datalog program into the SMT solver as a custom monotonic theory. Finally, we evaluate our approaches using multiple underlying solvers to provide a more thorough and nuanced comparison against the current state of the art.

The end of Moore’s Law has ushered in a diversity of hardware not seen in decades. Operating system (OS) (and system software) portability is accordingly becoming increasingly critical. Simultaneously, there has been tremendous progress in program synthesis. We set out to explore the feasibility of using modern program synthesis to generate the machine-dependent parts of an operating system. Our ultimate goal is to generate new ports automatically from descriptions of new machines. One of the issues involved is writing specifications, both for machine-dependent operating system functionality and for instruction set architectures. We designed two domain-specific languages: Alewife for machine-independent specifications of machine-dependent operating system functionality and Cassiopea for describing instruction set architecture semantics. Automated porting also requires an implementation. We developed a toolchain that, given an Alewife specification and a Cassiopea machine description, specializes the machine-independent specification to the target instruction set architecture and synthesizes an implementation in assembly language with a customized symbolic execution engine. Using this approach, we demonstrate the successful synthesis of a total of 140 OS components from two pre-existing OSes for four real hardware platforms. We also developed several optimization methods for OS-related assembly synthesis to improve scalability. The effectiveness of our languages and ability to synthesize code for all 140 specifications is evidence of the feasibility of program synthesis for machine-dependent OS code. However, many research challenges remain; we also discuss the benefits and limitations of our synthesis-based approach to automated OS porting.

Cyber-physical systems, such as self-driving cars or autonomous aircraft, must defend against attacks that target sensor hardware. Analyzing system design can help engineers understand how a compromised sensor could impact the system's behavior; however, designing security analyses for cyber-physical systems is difficult due to their combination of discrete dynamics, continuous dynamics, and nondeterminism. This paper contributes a framework for modeling and analyzing sensor attacks on cyber-physical systems, using the formalism of hybrid programs. We formalize and analyze two relational properties of a system's robustness. These relational properties respectively express (1) whether a system's safety property can be influenced by sensor attacks, and (2) whether a system's high-integrity state can be affected by sensor attacks. We characterize these relational properties by defining an equivalence relation between a system under attack and the original unattacked system. That is, the system satisfies the robustness properties if executions of the attacked system are appropriately related to executions of the unattacked system. We present two techniques for reasoning about the equivalence relation and thus proving the relational properties for a system. One proof technique decomposes large proof obligations to smaller proof obligations. The other proof technique adapts the self-composition technique from the literature on secure information-flow, allowing us to reduce reasoning about the equivalence of two systems to reasoning about properties of a single system. This technique allows us to reuse existing tools for reasoning about properties of hybrid programs, but is challenging due to the combination of discrete dynamics, continuous dynamics, and nondeterminism. To validate the usefulness of our relational properties and proof techniques, we present three case studies motivated by real design flaws in existing cyber-physical systems.

Abstract Differential privacy is a de facto standard in data privacy with applications in the private and public sectors. Most of the techniques that achieve differential privacy are based on a judicious use of randomness. However, reasoning about randomized programs is difficult and error prone. For this reason, several techniques have been recently proposed to support designer in proving programs differentially private or in finding violations to it. In this work we propose a technique based on symbolic execution for reasoning about differential privacy. Symbolic execution is a classic technique used for testing, counterexample generation and to prove absence of bugs. Here we use symbolic execution to support these tasks specifically for differential privacy. To achieve this goal, we design a relational symbolic execution technique which supports reasoning about probabilistic coupling, a formal notion that has been shown useful to structure proofs of differential privacy. We show how our technique can be used to both verify and find violations to differential privacy.

Incremental parsing is an integral part of code analysis performed by text editors and integrated development environments. This paper presents new methods to significantly improve the efficiency of incremental parsing for Parsing Expression Grammars (PEGs). We build on Incremental Packrat Parsing, an algorithm that adapts packrat parsing to an incremental setting, by implementing the memoization table as an interval tree with special support for shifting intervals, and modifying the memoization strategy to create tree structures in the table. Our approach enables reparsing in time logarithmic in the size of the input for typical edits, compared with linear-time reparsing for Incremental Packrat Parsing. We implement our methods in a prototype called GPeg, a parsing machine for PEGs with support for dynamic parsers (an important feature for extensibility in editors). Experiments show that GPeg has strong performance (sub-5ms reparse times) across a variety of input sizes (tens to hundreds of megabytes) and grammar types (from full language grammars to minimal grammars), and compares well with existing incremental parsers. As a complete example, we implement a syntax highlighting library and prototype editor using GPeg, with optimizations for these applications.

Coarse-grained dynamic information-flow control (IFC) is a good match for imperative object-oriented programming languages such as Java. Java language abstractions align well with coarse-grained IFC concepts, and so Java can be cleanly extended with coarse-grained dynamic IFC without requiring significantly different design patterns or excessive security annotations, and without excessive performance overhead.We present Co-Inflow: an extension of Java with coarse-grained dynamic IFC. By careful design choices and defaults, a programmer typically needs to add very few annotations to a Java program to convert it to a Co-Inflow program with relatively good precision. Additional annotations can improve precision. We achieve this tradeoff between precision and annotation burden by instantiating and specializing recent advances in coarse-grained IFC for a Java-like setting, and by using opaque labeled values: a restriction of labeled values that the Co-Inflow runtime automatically and securely creates and uses.We have captured the essence of Co-Inflow in a middle-weight imperative calculus, and proven that it provides a termination- insensitive non-interference security guarantee. We have a prototype implementation of Co-Inflow and use it to evaluate the precision, usability, and potential performance of Co-Inflow.

Assembly programming is challenging, even for experts. Program synthesis, as an alternative to manual implementation, has the potential to enable both expert and non-expert users to generate programs in an automated fashion. However, current tools and techniques are unable to synthesize assembly programs larger than a few instructions. We present Assuage : ASsembly Synthesis Using A Guided Exploration, which is a parallel interactive assembly synthesizer that engages the user as an active collaborator, enabling synthesis to scale beyond current limits. Using Assuage, users can provide two types of semantically meaningful hints that expedite synthesis and allow for exploration of multiple possibilities simultaneously. Assuage exposes information about the underlying synthesis process using multiple representations to help users guide synthesis. We conducted a within-subjects study with twenty-one participants working on assembly programming tasks. With Assuage, participants with a wide range of expertise were able to achieve significantly higher success rates, perceived less subjective workload, and preferred the usefulness and usability of Assuage over a state of the art synthesis tool.

Satisfiability modulo theories (SMT) solving has become a critical part of many static analyses, including symbolic execution, refinement type checking, and model checking. We propose Formulog, a domain-specific language that makes it possible to write a range of SMT-based static analyses in a way that is both close to their formal specifications and amenable to high-level optimizations and efficient evaluation. Formulog extends the logic programming language Datalog with a first-order functional language and mechanisms for representing and reasoning about SMT formulas; a novel type system supports the construction of expressive formulas, while ensuring that neither normal evaluation nor SMT solving goes wrong. Our case studies demonstrate that a range of SMT-based analyses can naturally and concisely be encoded in Formulog, and that — thanks to this encoding — high-level Datalog-style optimizations can be automatically and advantageously applied to these analyses.

Distributed applications cannot assume that their security policies will be enforced on untrusted hosts. Trusted execution environments (TEEs) combined with cryptographic mechanisms enable execution of known code on an untrusted host and the exchange of confidential and authenticated messages with it. TEEs do not, however, establish the trustworthiness of code executing in a TEE. Thus, developing secure applications using TEEs requires specialized expertise and careful auditing. This paper presents DFLATE, a core security calculus for distributed applications with TEEs. DFLATE offers high-level abstractions that reflect both the guarantees and limitations of the underlying security mechanisms they are based on. The accuracy of these abstractions is exhibited by asymmetry between confidentiality and integrity in our formal results: DFLATE enforces a strong form of noninterference for confidentiality, but only a weak form for integrity. This reflects the asymmetry of the security guarantees of a TEE: a malicious host cannot access secrets in the TEE or modify its contents, but they can suppress or manipulate the sequence of its inputs and outputs. Therefore DFLATE cannot protect against the suppression of high-integrity messages, but when these messages are delivered, their contents cannot have been influenced by an attacker.

Applications that handle sensitive information need to express and reason about the trust relationships between security principals. Such reasoning is difficult because the trust relationships are dynamic, and must thus be reasoned about at runtime when discovering and reasoning about trust relationships might inadvertently reveal confidential information and be subject to manipulation by untrusted principals. The Flow-Limited Authorization Model (FLAM) by Arden et al. exactly meets these needs. However, previous attempts to use FLAM in a programming language have not reaped the full benefits of the model. We present Flamio, an instantiation of FLAM in a language with coarse-grained dynamic information-flow control (IFC) which naturally lends itself to dynamic enforcement techniques. In our implementation of Flamio, the FLAM proof search rules for deriving trust relationships are implemented as regular Flamio computations: the IFC requirements for FLAM proof rules are a natural fit with coarse-grained information-flow mechanisms. Flamio even supports remote procedure calls, and thus seamlessly supports FLAM's distributed proof search. We have implemented Flamio as a Haskell library, and proved that a calculus based on Flamio enforces a noninterference-based security guarantee. We have implemented several case studies, demonstrating the expressiveness and usefulness of Flamio in distributed settings, as well as our novel approach to control label creep during proof search.

Symbolic execution is a classical program analysis technique used to show that programs satisfy or violate given specifications. In this work we generalize symbolic execution to support program analysis for relational specifications in the form of relational properties - these are properties about two runs of two programs on related inputs, or about two executions of a single program on related inputs. Relational properties are useful to formalize notions in security and privacy, and to reason about program optimizations. We design a relational symbolic execution engine, named RelSym which supports interactive refutation, as well as proving of relational properties for programs written in a language with arrays and for-like loops.

Recent advances in program synthesis convinced us that it was the right time to transform the process of porting an operating system into a program synthesis problem. We set out to synthesize the needed machine dependent code for an existing operating system. This undertaking proved far more challenging than we anticipated. We summarize our experience and lessons learned and propose next steps in realizing such an undertaking.

We present Clio, an information flow control (IFC) system that transparently incorporates cryptography to enforce confidentiality and integrity policies on untrusted storage. Clio insulates developers from explicitly manipulating keys and cryptographic primitives by leveraging the policy language of the IFC system to automatically use the appropriate keys and correct cryptographic operations. We prove that Clio is secure with a novel proof technique that is based on a proof style from cryptography together with standard programming languages results. We present a prototype Clio implementation and a case study that demonstrates Clio's practicality.

Modern service-oriented applications forgo semantically rich protocols and middleware when composing services. Instead, they embrace the loosely-coupled development and deployment of services that communicate via simple network protocols. Even though these applications do expose interfaces that are higher-order in spirit, the simplicity of the network protocols forces them to rely on brittle low-level encodings. To bridge the apparent semantic gap, programmers introduce ad-hoc and error-prone defensive code. Inspired by Design by Contract, we choose a different route to bridge this gap. We introduce Whip, a contract system for modern services. Whip (i) provides programmers with a higher-order contract language tailored to the needs of modern services; and (ii) monitors services at run time to detect services that do not live up to their advertised interfaces. Contract monitoring is local to a service. Services are treated as black boxes, allowing heterogeneous implementation languages without modification to services' code. Thus, Whip does not disturb the loosely coupled nature of modern services.

Hardware-based enclave protection mechanisms, such as Intel's SGX, ARM's TrustZone, and Apple's Secure Enclave, can protect code and data from powerful low-level attackers. In this work, we use enclaves to enforce strong application-specific information security policies.

Existing programming language access control frameworks do not meet the needs of all software components. We propose an expressive framework for implementing access control monitors for components. The basis of the framework is a novel concept: the authority environment. An authority environment associates rights with an execution context. The building blocks of access control monitors in our framework are authorization contracts: software contracts that manage authority environments. We demonstrate the expressiveness of our framework by implementing a diverse set of existing access control mechanisms and writing custom access control monitors for three realistic case studies.

We present an approach for dynamic information flow control across the application and database. Our approach reduces the amount of policy code required, yields formal guarantees across the application and database, works with existing relational database implementations, and scales for realistic applications. In this paper, we present a programming model that factors out information flow policies from application code and database queries, a dynamic semantics for the underlying $^JDB$ core language, and proofs of termination-insensitive non-interference and policy compliance for the semantics. We implement these ideas in Jacqueline, a Python web framework, and demonstrate feasibility through three application case studies: a course manager, a health record system, and a conference management system used to run an academic workshop. We show that in comparison to traditional applications with hand-coded policy checks, Jacqueline applications have 1) a smaller trusted computing base, 2) fewer lines of policy code, and 2) reasonable, often negligible, additional overheads.

Controlling confidential information in concurrent systems is difficult, due to covert channels resulting from interaction between threads. This problem is exacerbated if threads share resources at fine granularity. In this work, we propose a novel monitoring framework to enforce strong information security in concurrent programs. Our monitors are hybrid, combining dynamic and static program analysis to enforce security in a sound and rather precise fashion. In our framework, each thread is guarded by its own local monitor, and there is a single global monitor. We instantiate our monitoring framework to support rely-guarantee style reasoning about the use of shared resources, at the granularity of individual memory locations, and then specialize local monitors further to enforce flow-sensitive progress-sensitive information-flow control. Our local monitors exploit rely-guarantee-style reasoning about shared memory to achieve high precision. Soundness of rely-guarantee-style reasoning is guaranteed by all monitors cooperatively. The global monitor is invoked only when threads synchronize, and so does not needlessly restrict concurrency. We prove that our hybrid monitoring approach enforces a knowledge-based progress-sensitive non-interference security condition.

Information erasure is a formal security requirement that stipulates when sensitive data must be removed from computer systems. In a system that correctly enforces erasure requirements, an attacker who observes the system after sensitive data is required to have been erased cannot deduce anything about the data. Practical obstacles to enforcing information erasure include: (1) correctly determining which data requires erasure, and (2) reliably deleting potentially large volumes of data, despite untrustworthy storage services. In this paper, we present a novel formalization of language-based information erasure that supports cryptographic enforcement of erasure requirements: sensitive data is encrypted before storage, and upon erasure, only a relatively small set of decryption keys needs to be deleted. This cryptographic technique has been used by a number of systems that implement data deletion to allow the use of untrustworthy storage services. However, these systems provide no support to correctly determine which data requires erasure, nor have the formal semantic properties of these systems been explained or proven to hold. We address these shortcomings. Specifically, we study a programming language extended with primitives for public-key cryptography, and demonstrate how information-flow control mechanisms can automatically track data that requires erasure and provably enforce erasure requirements even when programs employ cryptographic techniques for erasure.

We present PIDGIN, a program analysis and understanding tool that enables the specification and enforcement of precise application-specific information security guarantees. PIDGIN also allows developers to interactively explore the information flows in their applications to develop policies and investigate counter-examples. PIDGIN combines program dependence graphs (PDGs), which precisely capture the information flows in a whole application, with a custom PDG query language. Queries express properties about the paths in the PDG; because paths in the PDG correspond to information flows in the application, queries can be used to specify global security policies. PIDGIN is scalable. Generating a PDG for a 330k line Java application takes 90 seconds, and checking a policy on that PDG takes under 14 seconds. The query language is expressive, supporting a large class of precise, application-specific security guarantees. Policies are separate from the code and do not interfere with testing or development, and can be used for security regression testing. We describe the design and implementation of PIDGIN and report on using it: (1) to explore information security guarantees in legacy programs; (2) to develop and modify security policies concurrently with application development; and (3) to develop policies based on known vulnerabilities.

We demonstrate, by a number of examples, that information flow security properties can be proved from abstract architectural descriptions, which describe only the causal structure of a system and local properties of trusted components. We specify these architectural descriptions of systems by generalizing intransitive noninterference policies to admit the ability to filter information passed between communicating domains. A notion of refinement of such system architectures is developed that supports top-down development of architectural specifications and proofs by abstraction of information security properties. We also show that, in a concrete setting where the causal structure is enforced by access control, a static check of the access control setting plus local verification of the trusted components is sufficient to prove that a generalized intransitive noninterference policy is satisfied.

In capability-safe languages, components can access a resource only if they possess a capability for that resource. As a result, a programmer can prevent an untrusted component from accessing a sensitive resource by ensuring that the component never acquires the corresponding capability. In order to reason about which components may use a sensitive resource it is necessary to reason about how capabilities propagate through a system. This may be difficult, or, in the case of dynamically composed code, impossible to do before running the system. To counter this situation, we propose extensions to capability-safe languages that restrict the use of capabilities according to declarative policies. We introduce two independently useful semantic security policies to regulate capabilities and describe language-based mechanisms that enforce them. Access control policies restrict which components may use a capability and are enforced using higher-order contracts. Integrity policies restrict which components may influence (directly or indirectly) the use of a capability and are enforced using an information-flow type system. Finally, we describe how programmers can dynamically and soundly combine components that enforce access control or integrity policies with components that enforce different policies or even no policy at all.

Graphical user interfaces (GUIs) mediate many of our interactions with computers. Functional Reactive Programming (FRP) is a promising approach to GUI design, providing high-level, declarative, compositional abstractions to describe user interactions and time-dependent computations. We present Elm, a practical FRP language focused on easy creation of responsive GUIs. Elm has two major features: simple declarative support for Asynchronous FRP; and purely functional graphical layout.

A great deal of research on sanitizer placement, sanitizer correctness, checking path validity, and policy inference, has been done in the last five to ten years, involving type systems, static analysis and runtime monitoring and enforcement. However, in pretty much all work thus far, the burden of sanitizer placement has fallen on the developer. However, sanitizer placement in large-scale applications is difficult, and developers are likely to make errors, and thus create security vulnerabilities.

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from the truthfulness; it is not incorporated in players' utility functions (and doing so has been shown to lead to non-truthfulness in some cases). In this work, we propose a new, general way of modelling privacy in players' utility functions. Specifically, we only assume that if an outcome o has the property that any report of player i would have led to o with approximately the same probability, then o has small privacy cost to player i. We give three mechanisms that are truthful with respect to our modelling of privacy: for an election between two candidates, for a discrete version of the facility location problem, and for a general social choice problem with discrete utilities (via a VCG-like mechanism). As the number n of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of n).

Program progress (or termination) is a covert channel that may leak sensitive information. To control information leakage on this channel, semantic definitions of security should be progress sensitive and enforcement mechanisms should restrict the channel's capacity. However, most state-of-the-art language-based information-flow mechanisms are progress insensitive---allowing arbitrary information leakage through this channel---and current progress-sensitive enforcement techniques are overly restrictive.

In systems that handle confidential information, the security policy to enforce on information frequently changes: new users join the system, old users leave, and sensitivity of data changes over time. It is challenging, yet important, to specify what it means for such systems to be secure, and to gain assurance that a system is secure. We present a language-based model for specifying, reasoning about, and enforcing information security in systems that dynamically change the security policy. We specify security for such systems as a simple and intuitive extensional knowledge-based semantic condition: an attacker can only learn information in accordance with the current security policy. Importantly, the semantic condition is parameterized by the ability of the attacker. Learning is about change in knowledge, and an observation that allows one attacker to learn confidential information may provide a different attacker with no new information. A program that is secure against an attacker with perfect recall may not be secure against a more realistic, weaker, attacker. We introduce a compositional model of attackers that simplifies enforcement of security, and demonstrate that standard information-flow control mechanisms, such as security-type systems and information-flow monitors, can be easily adapted to enforce security for a broad and useful class of attackers.

We demonstrate that a practical concurrent language can be extended in a natural way with information security mechanisms that provably enforce strong information security guarantees. We extend the X10 concurrent programming language with coarse-grained information-flow control. Central to X10 concurrency abstractions is the notion of a place: a container for data and computation. We associate a security level with each place, and restrict each place to store only data appropriate for that security level. When places interact only with other places at the same security level, then our security mechanisms impose no restrictions. When places of differing security levels interact, our information security analysis prevents potentially dangerous information flows, including information flow through covert scheduling channels. The X10 concurrency mechanisms simplify reasoning about information flow in concurrent programs. We present a static analysis that enforces a noninterference-based extensional information security condition in a calculus that captures the key aspects of X10's place abstraction and async-finish parallelism. We extend this security analysis to support many of X10's language features, and have implemented a prototype compiler for the resulting language.

Many computer systems have a functional requirement to release information. Such requirements are an important part of a system's information security requirements. Current information-flow control techniques are able to reason about permitted information flows, but not required information flows. In this paper, we introduce and explore the specification and enforcement of required information release in a language-based setting. We define semantic security conditions that express both what information a program is required to release, and how an observer is able to learn this information. We also consider the relationship between permitted and required information release, and define bounded release, which provides upper- and lower-bounds on the information a program releases. We show that both required information release and bounded release can be enforced using a security-type system.

Hybrid information-flow monitors use a combination of static analysis and dynamic mechanisms to provide precise strong information security guarantees. However, unlike purely static mechanisms for information security, hybrid information-flow monitors incur run-time overhead. We show how static analyses can be used to make hybrid information-flow monitors more efficient, in two ways. First, a simple static analysis can determine when it is sound for a monitor to stop tracking the security level of certain variables. This potentially reduces run-time overhead of the monitor, particularly in applications where sensitive (i.e., confidential or untrusted) data is infrequently introduced to the system. Second, we derive sufficient conditions for soundly incorporating a wide range of memory abstractions into information-flow monitors. This allows the selection of a memory abstraction that gives an appropriate tradeoff between efficiency and precision. It also facilitates the development of innovative and sound memory abstractions that use run-time security information maintained by the monitor. We present and prove our results by extending the information-flow monitor of Russo and Sabelfeld (2010). These results bring us closer to efficient, sound, and precise enforcement of information security.

We explore the inference of expressive human-readable declassification policies as a step towards providing practical tools and techniques for strong language-based information security. Security-type systems can enforce expressive information-security policies, but can require enormous programmer effort before any security benefit is realized. To reduce the burden on the programmer, we focus on inference of expressive yet intuitive information-security policies from programs with few programmer annotations. We define a novel security policy language that can express what information a program may release, under what conditions (or, when) such release may occur, and which procedures are involved with the release (or, where in the code the release occur). We describe a dataflow analysis for precisely inferring these policies, and build a tool that instantiates this analysis for the Java programming language. We validate the policies, analysis, and our implementation by applying the tool to a collection of simple Java programs.

Many computer systems have a functional requirement to release information. Such requirements are an important part of a system's information security requirements. Current information-flow control techniques are able to reason about permitted information flows, but not required information flows. In this paper, we introduce and explore the specification and enforcement of required information release in a language-based setting. We define semantic security conditions that express both what information a program is required to release, and how an observer is able to learn this information. We also consider the relationship between permitted and required information release, and define bounded release, which provides upper- and lower-bounds on the information a program releases. We show that both required information release and bounded release can be enforced using a security-type system.

Public-use sensor datasets are a useful scientific resource with the unfortunate feature that their provenance is easily disconnected from their content. To address this we introduce a technique to directly associate provenance information with sensor datasets. Our technique is similar to traditional watermarking but is intended for application to unstructured datasets. Our approach is potentially imperceptible given sufficient margins of error in datasets, and is robust to a number of benign but likely transformations including truncation, rounding, bit-flipping, sampling, and reordering. We provide algorithms for both one-bit and blind mark checking. Our algorithms are probabilistic in nature and are characterized by a combinatorial analysis.

One of our most resilient intuitions is that causality is a precondition for information flow: where there are no causal connections, we expect there to be no flow of information. In this paper, we study this idea as it arises in the computer science notion of systems architectures, which are high level designs that describe the coarse structure of a system in terms of its high-level components and their permitted causal interactions.

Declassification occurs when the confidentiality of information is weakened; erasure occurs when the confidentiality of information is strengthened, perhaps to the point of completely removing the information from the system. This paper shows how to enforce erasure and declassification policies. A combination of a type system that controls information flow and a simple runtime mechanism to overwrite data ensures end-to-end enforcement of policies. We prove that well-typed programs satisfy the semantic security condition noninterference according to policy. We extend the Jif programming language with erasure and declassification enforcement mechanisms and use the resulting language in a large case study of a voting system.

Civitas is the first electronic voting system that is coercion-resistant, universally and voter verifiable, and suitable for remote voting. This paper describes the design and implementation of Civitas. Assurance is established in the design through security proofs, and in the implementation through information-flow security analysis. Experimental results give a quantitative evaluation of the tradeoffs between time, cost, and security.

Swift is a new, principled approach to building web applications that are secure by construction. In modern web applications, some application functionality is usually implemented as client-side code written in JavaScript. Moving code and data to the client can create security vulnerabilities, but currently there are no good methods for deciding when it is secure to do so. Swift automatically partitions application code while providing assurance that the resulting placement is secure and efficient. Application code is written as Java-like code annotated with information flow policies that specify the confidentiality and integrity of web application information. The compiler uses these policies to automatically partition the program into JavaScript code running in the browser, and Java code running on the server. To improve interactive performance, code and data are placed on the client side. However, security-critical code and data are always placed on the server. Code and data can also be replicated across the client and server, to obtain both security and performance. A max-flow algorithm is used to place code and data in a way that minimizes client-server communication.

Robustness links confidentiality and integrity properties of a computing system and has been identified as a useful property for characterizing and enforcing security. Previous characterizations of robustness have been with respect to a single idealized attacker; this paper shows how to define robustness for systems with mutual distrust. Further, we demonstrate that the decentralized label model (DLM) can be extended to support fine-grained reasoning about robustness in such systems. The DLM is a natural choice for capturing robustness requirements because decentralized labels are explicitly expressed in terms of principals that can be used to characterize the power of attackers across both the confidentiality and integrity axes. New rules are proposed for statically checking robustness and qualified robustness using an extended DLM; the resulting type system is shown to soundly enforce robustness. Finally, sound approximations are developed for checking programs with bounded but unknown label parameters, which is useful for security-typed languages. In sum, the paper shows how to use robustness to gain assurance about secure information flow and information release in systems with complex security requirements

Interactive programs allow users to engage in input and output throughout execution. The ubiquity of such programs motivates the development of models for reasoning about their information-flow security, yet no such models seem to exist for imperative programming languages. Further, existing language-based security conditions founded on noninteractive models permit insecure information flows in interactive imperative programs. This paper formulates new strategy-based information-flow security conditions for a simple imperative programming language that includes input and output operators. The semantics of the language enables a fine-grained approach to the resolution of nondeterministic choices. The security conditions leverage this approach to prohibit refinement attacks while still permitting observable nondeterminism. Extending the language with probabilistic choice yields a corresponding definition of probabilistic noninterference. A soundness theorem demonstrates the feasibility of statically enforcing the security conditions via a simple type system. These results constitute a step toward understanding and enforcing information-flow security in real-world programming languages, which include similar input and output operators

Real computing systems sometimes need to forget sensitive information. This paper explores the specification and semantics of information erasure policies, which impose a strong, end-to-end requirement that information be either erased or made less accessible. Simple lattice-based information flow policies, corresponding to a noninterference requirement, are augmented with the ability to express explicit erasure and declassification policies. Examples are given of applying this expressive policy language to real systems. The paper gives tools for reasoning about policy enforcement either statically or dynamically. Further, the significance of these policies to security is formally explained in terms of trace-based semantic security properties: generalizations of noninterference that accommodate erasure and declassification.

A long-standing problem in information security is how to specify and enforce expressive security policies that control information flow while also permitting information release (i.e., declassification) where appropriate. This paper presents security policies for downgrading and a security type system that incorporates them, allowing secure downgrading of information through an explicit declassification operation. Examples are given showing that the downgrading policy language captures useful aspects of designer intent. These policies are connected to a semantic security condition that generalizes noninterference, and the type system is shown to enforce this security condition.

Inheritance is a useful mechanism for factoring and reusing code. However, it has limitations for building extensible systems. We describe nested inheritance, a mechanism that addresses some of the limitations of ordinary inheritance and other code reuse mechanisms. Using our experience with an extensible compiler framework, we show how nested inheritance can be used to construct highly extensible software frameworks. The essential aspects of nested inheritance are formalized in a simple object-oriented language with an operational semantics and type system. The type system of this language is sound, so no run-time type checking is required to implement it and no run-time type errors can occur. We describe our implementation of nested inheritance as an unobtrusive extension of the Java language, called Jx. Our prototype implementation translates Jx code to ordinary Java code, without duplicating inherited code.

A challenging unsolved security problem is how to specify and enforce system-wide security policies; this problem is even more acute in distributed systems with mutual distrust. This paper describes a way to enforce policies for data confidentiality and integrity in such an environment. Programs annotated with security specifications are statically checked and then transformed by the compiler to run securely on a distributed system with untrusted hosts. The code and data of the computation are partitioned across the available hosts in accordance with the security specification. The key contribution is automatic replication of code and data to increase assurance of integrity, without harming confidentiality, and without placing undue trust in any host. The compiler automatically generates secure run-time protocols for communication among the replicated code partitions. Results are given from a prototype implementation applied to various distributed programs.