The Android framework utilizes a permission-based security model, which is essentially a variation of the ACL-based access control mechanism. This security model provides controlled access to various system resources. Access control systems are known to be vulnerable to anomalies in security policies, such as inconsistency. In this work, we focus on inconsistent security enforcement within the Android framework, motivated by the recent work which discovered such vulnerabilities. They include stealthily taking pictures in the background and recording keystrokes without any permissions, posing security and privacy risks to Android users. Identifying such inconsistencies is generally difficult, especially in complicated and large codebases such as the Android framework. Our work is the first to propose a methodology to systematically uncover the inconsistency in security policy enforcement in Android. We do not assume Android's security policies are known and focus only on inconsistent enforcement. We propose Kratos, a tool that leverages static analysis to build a precise call graph for identifying paths that allow third-party applications with insufficient privilege to access sensitive resources, violating security policies. Kratos is designed to analyze any Android system, including vendor-customized versions. Using Kratos, we have conservatively discovered at least fourteen inconsistent security enforcement cases that can lead to security check circumvention vulnerabilities across important and popular services such as the SMS service and the Wi-Fi service, incurring impact such as privilege escalation, denial of service, and soft reboot. Our findings also provide useful insights on how to proactively prevent such security enforcement inconsistency within Android. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform. CCS Concepts: • Software and its engineering → Domain specific languages; General programming languages; • Theory of computation → Logic; Type theory; • Social and professional topics → History of programming languages;

In this work, we conduct the first systematic study in understanding the security properties of the usage of Unix domain sockets by both Android apps and system daemons as an IPC (Inter-process Communication) mechanism, especially for cross-layer communications between the Java and native layers. We propose a tool called SInspector to expose potential security vulnerabilities in using Unix domain sockets through the process of identifying socket addresses, detecting authentication checks, and performing data flow analysis. Our in-depth analysis revealed some serious vulnerabilities in popular apps and system daemons, such as root privilege escalation and arbitrary file access. Based on our findings, we propose countermeasures and improved practices for utilizing Unix domain sockets on Android.

BackgroundMoving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test–driven development and automated regression testing promotes reliability. Test–driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a “safety net” for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and “living” design documentation. Rapid-cycle development or “agile” methods are being successfully applied to CDS development. The agile practice of automated test–driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as “executable requirements.”ObjectiveWe aimed to establish feasibility of acceptance test–driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse).MethodsAcceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory’s expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite.ResultsWe used test–driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the “executable requirements” are shown prior to building the CDS alert, during build, and after successful build.ConclusionsAutomated acceptance test–driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test–driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization.

This paper introduces a compiler optimization strategy for Software-Programmable Laboratories-on-a-Chip (SP-LoCs), which miniaturize and automate a wide variety of benchtop laboratory experiments. The compiler targets a specific class of SP-LoCs that manipulate discrete liquid droplets on a 2D grid, with cyber-physical feedback provided by integrated sensors and/or video monitoring equipment. The optimization strategy employed here aims to reduce the overhead of transporting fluids between operations, and explores tradeoffs between the latency and resource requirements of mixing operations: allocating more space for mixing shortens mixing time, but reduces the amount of spatial parallelism available to other operations. The compiler is empirically evaluated using a cycle-accurate simulator that mimics the behavior of the target SP-LoC. Our results show that a coalescing strategy, inspired by graph coloring register allocation, effectively reduces droplet transport latencies while speeding up the compiler and reducing its memory footprint. For biochemical reactions that are dominated by mixing operations, we observe a linear correlation between a preliminary result using a default mixing operation resource allocation and the percentage decrease in execution time that is achieved via resizing. CCS Concepts • Computer systems organization → Embedded and cyber-physical systems; Parallel architectures; Reconfigurable computing; • Software and its engineering → Compilers; • Hardware → Emerging languages and compilers; Microelectromechanical systems.

While safe chemical storage and disposal are simple in principle-users should read safety specifications and place chemicals in appropriate cabinets or collection pointshigh-profile incidents involving improper storage and disposal of chemicals continue to occur. This paper introduces ChemStor , an open-source, automated computational system that can guarantee (mathematically verify a system is correct with respect to its specification), with regard to prescribed constraints, safe storage and disposal of chemicals used in academic, industrial, and domestic settings. ChemStor borrows concepts from formal methods-a branch of computer science capable of mathematically proving a specification or software is correct-to safely store or dispose of chemicals. If two or more chemicals can be combined in the same cabinet without forming possibly dangerous combinations of chemicals (while observing cabinet/shelf space constraints), then ChemStor determines that the storage configuration is safe. Likewise, if chemicals can be added to an existing disposal container without forming possibly dangerous combinations of chemicals (or exceeding the volume of the container), then ChemStor determines that the disposal configuration is safe. ChemStor accomplishes this by first building a chemical interaction graph, a graph that describes which chemicals may interact with each other based on their Reactivity Groups as determined by the United States Environmental Protection Agency. Next, ChemStor computes the chromatic number of the graph, the smallest number of colors used to color the graph such that no two vertices (chemicals) that share an edge (an interaction) share the same color. ChemStor then assigns all the chemicals of each color to a storage or disposal container after confirming that there is enough space in the container. These steps are encoded into a series of Satisfiability Modulo Theory equations, and ChemStor uses an industry-standard tool to try to find a valid solution to these equations. The result is either a solution which dictates exactly where to store or dispose of each chemical, or an indication that no safe storage or disposal configuration could be found. To demonstrate the feasibility of ChemStor , we used the tool to analyze ten real-world chemical 2 storage and disposal incidents that led to injuries or destruction of property. In each case, ChemStor quickly and successfully identified a proper chemical disposal or storage configuration that would have prevented the incident. In the future, ChemStor may be integrated with electronic laboratory notebooks, voice assistants, and other emerging technology to protect users of chemicals in labs, workplaces, and homes. Container 1

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