Isolating JavaScript with Filters, Rewriting, and Wrappers

Abstract. We study methods that allow web sites to safely combine JavaScript from untrusted sources. If implemented properly, filters can prevent dangerous code from loading into the execution environment, while rewriting allows greater expressiveness by inserting run-time checks. Wrapping properties of the execution environment can prevent misuse without requiring changes to imported JavaScript. Using a formal semantics for the ECMA 262-3 standard language, we prove security properties of a subset of JavaScript, comparable in expressiveness to Facebook FBJS, obtained by combining three isolation mechanisms. The isolation guarantees of the three mechanisms are interdependent, with rewriting and wrapper functions relying on the absence of JavaScript constructs eliminated by language filters.

Refinement Types for Secure Implementations

We present the design and implementation of a typechecker for verifying security properties of the source code of cryptographic protocols and access control mechanisms. The underlying type theory is a λ-calculus equipped with refinement types for expressing pre- and post-conditions within first-order logic. We derive formal cryptographic primitives and represent active adversaries within the type theory. Well-typed programs enjoy assertion-based security properties, with respect to a realistic threat model including key compromise. The implementation amounts to an enhanced typechecker for the general purpose functional language F#; typechecking generates verification conditions that are passed to an SMT solver. We describe a series of checked examples. This is the first tool to verify authentication properties of cryptographic protocols by typechecking their source code. © 2008 IEEE

Exposure to particulate matter and risk of amyotrophic lateral sclerosis: A case-control study in Northern Italy

Background: Amyotrophic lateral sclerosis (ALS) is progressive neurodegenerative disease with still unknown etiology. Role of occupational and environmental risk factors has been investigated, including outdoor air pollutants, which have been recently associated to an excess disease risk. We carried out a case-control study in order to assess if environmental exposure to particulate matter ≤10 µm (PM10) may increase ALS risk. Methods: We recruited patients referred to the Modena Neurology Unit between 1994-2015 and controls from the Modena province population. Using a validated geographical information system-based dispersion model, we geocoded subjects’ addresses of residence at the time of diagnosis and we estimated outdoor air PM10 concentrations for each subjects. We computed odds ratio (OR) and 95% confidence interval (CI) of ALS according to increasing PM10 exposure, using an unconditional logistic regression model age- and sex-adjusted. Results: For the 132 study participants (52 cases/80 controls), mean of annual average and maximum PM10 concentrations were 5.2 and 38.6µg/m3, respectively. Using fixed cutpoints at 5, 10 and 20 of average annual PM10 concentrations, compared with subjects <5µg/m3, we did not find evidence for an excess ALS risk associated with PM10 exposure, since OR was 0.87 (95% CI 0.39-1.96), 0.94 (0.24-3.70), and 0.87 (0.05-15.01) at 5-10, 10-20 and ≥20µg/m3, respectively. Using maximum annual PM10 concentrations, we found an excess ALS risk for subjects exposed at 10-20µg/m3 (OR=4.27, 0.69-26.51) compared with exposure below 10µg/m3, although the risk tended to decrease at higher PM10 concentrations, with OR of 1.49 (0.39-5.75) at 20-50, and 1.16 (0.98-4.82) at ≥50µg/m3. Conclusions:Our findings do not suggest that PM10exposure is associated with ALS risk. However, some evidence of an increased risk associated with maximum annual exposure concentrations, although statistically imprecise, suggests the need of further investigations, also considering the high concentrations of particulate matter characterizing Northern Italy

Monitoring Neoadjuvant Chemotherapy Through Time Domain Diffuse Optical Spectroscopy in Breast Cancer Patients: Preliminary Clinical Results

The purpose of this clinical study is to monitor NeoAdjuvant Chemotherapy through time domain Diffuse Optical Spectroscopy, correlate the optical results with conventional imaging techniques and pathological response and eventually predict the efficacy of NAC in breast cancer patients. Our seven wavelength (635 -1060 nm) optical mammograph is used to perform non-invasive measurements on patients undergoing NAC in this study. The broad spectral range helps us to fully analyze tissue composition, that includes hemoglobin, water lipids and collagen concentration, to track the tumor response during the course of the therapy. In this paper, we present the preliminary results of five patients

Preliminary Evidence of the Efficacy of Time-Resolved Broad-Spectrum Optical Mammography in Monitoring Neoadjuvant Chemotherapy

We present initial results of a clinical trial involving breast cancer patients under neoadjuvant chemotherapy, monitored through our time-resolved optical mammograph. Besides hemoglobin, water and lipids, we assess collagen concentration systematically for the first time

Assessing the Economic Value of a Regional Air Quality Plan

When developing an air quality plan, environmental authorities usually devise a number of individual actions, constituted by the application of both technical (end-of-pipe) and energy efficiency measures. They may range from the incentives to buy less polluting vehicles, to the enforcement of stricter rules on domestic heating. The assessment of the economic effectiveness for the society as a whole of the individual measures and of the overall plan requires a flexible support system able to quickly perform air quality impact evaluations on the specific area. One such system is RIAT+, a software package developed and tested during a series of European research projects, which has been used to evaluate costs and benefits of the Lombardy Region Air Quality Plan (PRIA), constituted by about 90 different actions to be implemented within 2020. The adoption of each measure means a certain change in the emission, which is distributed over the regional territory in different way, depending on the type of measure. A shift of the car fleet to a different EURO class, for instance, means an emission reduction only on the road network, while a reduced use of electricity may imply a lower emission of power plants at specific sites. To evaluate the effects of these emission changes, RIAT+ adopts a surrogate model approach, namely using a neural network calibrated on few results of a full chemical transport model. It is thus possible to rapidly evaluate the improvements in the population exposure and health and the consequent reduction of external costs. The final economic assessment is obtained by comparing the sum of energy savings and external cost reductions with the implementation costs of the corresponding measures