Hybrid Information Flow Analysis for Programs with Arrays

Information flow analysis checks whether certain pieces of (confidential) data may affect the results of computations in unwanted ways and thus leak information. Dynamic information flow analysis adds instrumentation code to the target software to track flows at run time and raise alarms if a flow policy is violated; hybrid analyses combine this with preliminary static analysis. Using a subset of C as the target language, we extend previous work on hybrid information flow analysis that handled pointers to scalars. Our extended formulation handles arrays, pointers to array elements, and pointer arithmetic. Information flow through arrays of pointers is tracked precisely while arrays of non-pointer types are summarized efficiently. A prototype of our approach is implemented using the Frama-C program analysis and transformation framework. Work on a full machine-checked proof of the correctness of our approach using Isabelle/HOL is well underway; we present the existing parts and sketch the rest of the correctness argument.Comment: In Proceedings VPT 2016, arXiv:1607.0183

Imaging of solid flow in a gravity flow rig using infra-red tomography

Information on flow regimes is vital in the analysis and measurement of industrial process flow. Almost all currently available method of measuring the flow of two-component mixtures in industrial pipelines endeavors to average a property of the flow over the pipe cross-section. They do not give information on the nature of the flow regime and they are unsuitable for accurate measurement where the component distribution is spatially or time varying. The overall aim of this project is to investigate the use of an optical tomography method based on infra-red sensors for real-time monitoring of solid particles conveyed by a rotary valve in a pneumatic pipeline. The infra-red tomography system can be divided into two distinct portions of hardware and software development process. The hardware development process covers the infra-red sensor selection, fixtures and signals conditioning circuits, and control circuits. The software development involves data acquisition system, sensor modeling, image algorithms, and programming for a tomographic display to provide solids flow information in pipeline such as concentration and velocity profiles. Collimating the radiated beam from a light source and passing it via a flow regime ensures that the intensity of radiation detected on the opposite side is linked to the distribution and the absorption coefficients of the different phases in the path of the beam. The information is obtained from the combination of two orthogonal and two diagonal light projection system and 30 cycles of real-time measurements. Those information on the flow captured using upstream and downstream infra-red sensors are digitized by the DAS system before it was passed into a computer for analysis such as image reconstructions and cross-correlation process that provide velocity profiles represented by 16 × 16 pixels mapped onto the pipe cross-section. This project successfully developed and tested an infra-red tomography system to display two-dimensional images of concentration and velocity

Delayed information flow effect in economy systems. An ACP model study

Applying any strategy requires some knowledge about the past state of the system. Unfortunately in the case of economy collecting information is a difficult, expensive and time consuming process. Therefore the information about the system is known at the end of some well defined intervals, e. g. company reports, inflation data, GDP etc. They describe a (market) situation in the past. The time delay is specific to the market branch. It can be very short (e.g. stock market offer is updated every minute or so and this information is immediately available) or long, like months in the case of agricultural market, when the decisions are taken based on the results from the previous harvest. The analysis of the information flow delay can be based on the ACP model of spatial evolution of economic systems. The entities can move on a square lattice and when meeting take one of the two following decisions: merge or create a new entity. The decision is based on the system state, which is known with some time delay. The effect of system's feedback is investigated. We consider the case of company distribution evolution in a heterogenous field. The information flow time delay implies different final states, including cycles.Comment: Presented at APFA

LPMLE3 : a novel 1-D approach to study water flow in streambeds using heat as a tracer

We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods

The price impact of economic news, private information and trading intensity

In this paper we use three years high-frequency data to investigate the role played by public and private information in the process of price formation in two secondary government bond markets. As public information we examine the impact of regularly scheduled macroeconomic news announcements. We identify those announcements with the greatest impact on these markets. As private information we estimate the price impact of order flow. In fact, according to the microstructure models, private information in this context is related to the subjective evaluation of information and order flow can reflect difference of opinions among market participants. Thus, market participant may infer information about the subjective beliefs of other market participants looking at the aggregate order flow. We then use a vector autoregressive model for prices and trades to empirically test the role played by intraday trading intensity and by the waiting time between consecutive transactions in the process of price formations