Computing homomorphic program invariants

Program invariants are properties that are true at a particular program point or points. Program invariants are often undocumented assertions made by a programmer that hold the key to reasoning correctly about a software verification task. Unlike the contemporary research in which program invariants are defined to hold for all control flow paths, we propose \textit{homomorphic program invariants}, which hold with respect to a relevant equivalence class of control flow paths. For a problem-specific task, homomorphic program invariants can form stricter assertions. This work demonstrates that the novelty of computing homomorphic program invariants is both useful and practical. Towards our goal of computing homomorphic program invariants, we deal with the challenge of the astronomical number of paths in programs. Since reasoning about a class of program paths must be efficient in order to scale to real-world programs, we extend prior work to efficiently divide program paths into equivalence classes with respect to control flow events of interest. Our technique reasons about inter-procedural paths, which we then use to determine how to modify a program binary to abort execution at the start of an irrelevant program path. With off-the-shelf components, we employ the state-of-the-art in fuzzing and dynamic invariant detection tools to mine homomorphic program invariants. To aid in the task of identifying likely software anomalies, we develop human-in-the-loop analysis methodologies and a toolbox of human-centric static analysis tools. We present work to perform a statically-informed dynamic analysis to efficiently transition from static analysis to dynamic analysis and leverage the strengths of each approach. To evaluate our approach, we apply our techniques to three case study audits of challenge applications from DARPA\u27s Space/Time Analysis for Cybersecurity (STAC) program. In the final case study, we discover an unintentional vulnerability that causes a denial of service (DoS) in space and time, despite the challenge application having been hardened against static and dynamic analysis techniques

Model-Based Pricing in Hurricane Insurance: A Case Study for Judicial Reform of the McCarran-Freguson Act

The McCarran-Ferguson Act (MFA) exempts various aspects of state insurance operations from federal antitrust enforcement. This exemption is a source of longstanding controversy, due in part to its potentially harmful effect on consumers in product pricing. In hurricane insurance, there is a burgeoning debate concerning insurers\u27 use of predictive computer models rather than shared loss data to set premiums for the industry. By using these models in hurricane-prone states, insurers have increased the price of hurricane insurance dramatically. Where these new prediction methods are used, MFA exemption may facilitate supracompetitive pricing in ways its architects could not have foreseen. This Note analyzes MFA\u27s economic effects on model-based pricing in hurricane insurance to argue for judicial revision of the Act. Through an effects test, it proposes conditioning eligibility for antitrust exemption on the economic benefits of a challenged activity exceeding its costs

Model-Based Pricing in Hurricane Insurance: A Case Study for Judicial Reform of the McCarran-Freguson Act

The McCarran-Ferguson Act (MFA) exempts various aspects of state insurance operations from federal antitrust enforcement. This exemption is a source of longstanding controversy, due in part to its potentially harmful effect on consumers in product pricing. In hurricane insurance, there is a burgeoning debate concerning insurers\u27 use of predictive computer models rather than shared loss data to set premiums for the industry. By using these models in hurricane-prone states, insurers have increased the price of hurricane insurance dramatically. Where these new prediction methods are used, MFA exemption may facilitate supracompetitive pricing in ways its architects could not have foreseen. This Note analyzes MFA\u27s economic effects on model-based pricing in hurricane insurance to argue for judicial revision of the Act. Through an effects test, it proposes conditioning eligibility for antitrust exemption on the economic benefits of a challenged activity exceeding its costs

The Stark Physician Self-Referral Law and Accountable Care Organizations: Collision Course or Opportunity to Reconcile Federal Anti-Abuse and Cost-Saving Legislation?

Scholars and legal practitioners have long debated the virtues and vices of integrated models of health care delivery and financing. Few such models have been as promising or as rapidly adopted as Accountable Care Organizations (“ACOs”), the latest concept in delivering cost-effective, high-quality health care. Implementation of pre-ACO models, however, never required extensive grants of immunity to providers and suppliers from the federal Stark physician self-referral law (“Stark”) and other fraud and abuse laws. The broad waivers issued by the Centers for Medicare & Medicaid Services (“CMS”) for implementing ACOs raise unprecedented legal questions concerning Stark’s application to these hospital/physician arrangements designed to decrease costs. Furthermore, the waivers represent new opportunities to reconcile, through rulemaking, the cost savings of ACOs with their attendant risks of physician abuse or patient harm accomplished through Stark-proscribed self-referral

Security Toolbox for Detecting Novel and Sophisticated Android Malware

This paper presents a demo of our Security Toolbox to detect novel malware in Android apps. This Toolbox is developed through our recent research project funded by the DARPA Automated Program Analysis for Cybersecurity (APAC) project. The adversarial challenge ("Red") teams in the DARPA APAC program are tasked with designing sophisticated malware to test the bounds of malware detection technology being developed by the research and development ("Blue") teams. Our research group, a Blue team in the DARPA APAC program, proposed a "human-in-the-loop program analysis" approach to detect malware given the source or Java bytecode for an Android app. Our malware detection apparatus consists of two components: a general-purpose program analysis platform called Atlas, and a Security Toolbox built on the Atlas platform. This paper describes the major design goals, the Toolbox components to achieve the goals, and the workflow for auditing Android apps. The accompanying video (http://youtu.be/WhcoAX3HiNU) illustrates features of the Toolbox through a live audit.Comment: 4 pages, 1 listing, 2 figure

C3TM: CEI CCD charge transfer model for radiation damage analysis and testing

Radiation induced defects in the silicon lattice of Charge Couple Devices (CCDs) are able to trap electrons during read out and thus create a smearing effect that is detrimental to the scientific data. To further our understanding of the positions and properties of individual radiation-induced traps and how they affect space- borne CCD performance, we have created the Centre for Electronic Imaging (CEI) CCD Charge Transfer Model (C3TM). This model simulates the physical processes taking place when transferring signal through a radiation damaged CCD. C3TM is a Monte Carlo model based on Shockley-Read-Hall theory, and it mimics the physical properties in the CCD as closely as possible. It runs on a sub-electrode level taking device specific charge density simulations made with professional TCAD software as direct input. Each trap can be specified with 3D positional information, emission time constant and other physical properties. The model is therefore also able to simulate multi-level clocking and other complex clocking schemes, such as trap pumping

A model for simulating dynamic problems of economic development

At head of title: Economic dynamics"July 1960."Includes bibliographic references (p. 198-203

A Persistent Simulation Environment for Autonomous Systems

The age of Autonomous Unmanned Aircraft Systems (AUAS) is creating new challenges for the accreditation and certification requiring new standards, policies and procedures that sanction whether a UAS is safe to fly. Establishing a basis for certification of autonomous systems via research into trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautics Solution (CAS) project. Simulation Environments to test and evaluate AUAS decision making may be a low-cost solution to help certify that various AUAS systems are trustworthy enough to be allowed to fly in current general and commercial aviation airspace. NASA is working to build a peer-to-peer persistent simulation (P3 Sim) environment. The P3 Sim will be a Massively Multiplayer Online (MMO) environment were AUAS avatars can interact with a complex dynamic environment and each other. The focus of the effort is to provide AUAS researchers a low-cost intuitive testing environment that will aid training for and assessment of decisions made by autonomous systems such as AUAS. This presentation focuses on the design approach and challenges faced in development of the P3 Sim Environment is support of investigating trustworthiness of autonomous systems