Biblio

We present überSpark (üSpark), an innovative architecture for compositional verification of security properties of extensible hypervisors written in C and Assembly. üSpark comprises two key ideas: (i) endowing low-level system software with abstractions found in higher-level languages (e.g., objects, interfaces, function-call semantics for implementations of interfaces, access control on interfaces, concurrency and serialization), enforced using a combination of commodity hardware mechanisms and lightweight static analysis; and (ii) interfacing with platform hardware by programming in Assembly using an idiomatic style (called CASM) that is verifiable via tools aimed at C, while retaining its performance and low-level access to hardware. After verification, the C code is compiled using a certified compiler while the CASM code is translated into its corresponding Assembly instructions. Collectively, these innovations enable compositional verification of security invariants without sacrificing performance. We validate üSpark by building and verifying security invariants of an existing open-source commodity x86 micro-hypervisor and several of its extensions, and demonstrating only minor performance overhead with low verification costs.

Security-sensitive applications that execute untrusted code often check the code’s integrity by comparing its syntax to a known good value or sandbox the code to contain its effects. System M is a new program logic for reasoning about such security-sensitive applications. System M extends Hoare Type Theory (HTT) to trace safety properties and, additionally, contains two new reasoning principles. First, its type system internalizes logical equality, facilitating reasoning about applications that check code integrity. Second, a con- finement rule assigns an effect type to a computation based solely on knowledge of the computation’s sandbox. We prove the soundness of System M relative to a step-indexed trace-based semantic model. We illustrate both new reasoning principles of System M by verifying the main integrity property of the design of Memoir, a previously proposed trusted computing system for ensuring state continuity of isolated security-sensitive applications. 

Interface-confinement is a common mechanism that secures untrusted code by executing it inside a sandbox. The sandbox limits (confines) the code's interaction with key system resources to a restricted set of interfaces. This practice is seen in web browsers, hypervisors, and other security-critical systems. Motivated by these systems, we present a program logic, called System M, for modeling and proving safety properties of systems that execute adversary-supplied code via interface-confinement. In addition to using computation types to specify effects of computations, System M includes a novel invariant type to specify the properties of interface-confined code. The interpretation of invariant type includes terms whose effects satisfy an invariant. We construct a step-indexed model built over traces and prove the soundness of System M relative to the model. System M is the first program logic that allows proofs of safety for programs that execute adversary-supplied code without forcing the adversarial code to be available for deep static analysis. System M can be used to model and verify protocols as well as system designs. We demonstrate the reasoning principles of System M by verifying the state integrity property of the design of Memoir, a previously proposed trusted computing system.

With the urban traffic planning and management development, it is a highly considerable issue to analyze and estimate the original-destination data in the city. Traditional method to acquire the OD information usually uses household survey, which is inefficient and expensive. In this paper, the new methodology proposed that using mobile phone data to analyze the mechanism of trip generation, trip attraction and the OD information. The mobile phone data acquisition is introduced. A pilot study is implemented on Beijing by using the new method. And, much important traffic information can be extracted from the mobile phone data. We use the K-means clustering algorithm to divide the traffic zone. The attribution of traffic zone is identified using the mobile phone data. Then the OD distribution and the commuting travel are analyzed. At last, an experiment is done to verify availability of the mobile phone data, that analyzing the "Traffic tide phenomenon" in Beijing. The results of the experiments in this paper show a great correspondence to the actual situation. The validated results reveal the mobile phone data has tremendous potential on OD analysis.