Cyber-Physical System Intrusion: A Case Study of Automobile Identification Vulnerabilities and Automated Approaches for Intrusion Detection

Today\u27s vehicle manufacturers do not tend to publish proprietary packet formats for the controller area network (CAN), a network protocol regularly used in automobiles and manufacturing. This is a form of security through obscurity -it makes reverse engineering efforts more difficult for would-be intruders -but obfuscating the CAN data in this way does not adequately hide the vehicle\u27s unique signature, even if these data are unprocessed or limited in scope. To prove this, we train two distinct deep learning models on data from 11 different vehicles. Our results clearly indicate that one can determine which vehicle generated a given sample of CAN data. This erodes consumer safety: a sophisticated attacker who establishes a presence on an unknown vehicle can use similar techniques to identify the vehicle and better format attacks. To protect critical cyber-physical systems (CPSs) against attacks like those enabled by this CAN vulnerability, system administrators often develop and employ intrusion detection systems (IDSs). Before developing an IDS, one requires an understanding of the behavior of the CPS and of the causality of its constituent parts. Such an understanding allows one to characterize normal behavior and, in turn, identify and report anomalous behavior. This research explores two different time series analysis techniques, Granger causality and empirical dynamic modeling (EDM), which may contribute to this understanding of a system. Our findings indicate that Granger causality is not a suitable approach to IDS development but that EDM may enable the understanding of a system required of an IDS architect. We thus encourage further research into EDM applications to IDSs for CPSs

Role of appetitive phenotype trajectory groups on child body weight during a family-based treatment for children with overweight or obesity.

ObjectiveEmerging evidence suggests that individual appetitive traits may usefully explain patterns of weight loss in behavioral weight loss treatments for children. The objective of this study was to identify trajectories of child appetitive traits and the impact on child weight changes over time.MethodsSecondary data analyses of a randomized noninferiority trial conducted between 2011 and 2015 evaluated children's appetitive traits and weight loss. Children with overweight and obesity (mean age = 10.4; mean BMI z = 2.0; 67% girls; 32% Hispanic) and their parent (mean age = 42.9; mean BMI = 31.9; 87% women; 31% Hispanic) participated in weight loss programs and completed assessments at baseline, 3, 6,12, and 24 months. Repeated assessments of child appetitive traits, including satiety responsiveness, food responsiveness and emotional eating, were used to identify parsimonious grouping of change trajectories. Linear mixed-effects models were used to identify the impact of group trajectory on child BMIz change over time.ResultsOne hundred fifty children and their parent enrolled in the study. The three-group trajectory model was the most parsimonious and included a high satiety responsive group (HighSR; 47.4%), a high food responsive group (HighFR; 34.6%), and a high emotional eating group (HighEE; 18.0%). Children in all trajectories lost weight at approximately the same rate during treatment, however, only the HighSR group maintained their weight loss during follow-ups, while the HighFR and HighEE groups regained weight (adjusted p-value < 0.05).ConclusionsDistinct trajectories of child appetitive traits were associated with differential weight loss maintenance. Identified high-risk subgroups may suggest opportunities for targeted intervention and maintenance programs

Engaging Empirical Dynamic Modeling to Detect Intrusions in Cyber-Physical Systems

Modern cyber-physical systems require effective intrusion detection systems to ensure adequate critical infrastructure protection. Developing an intrusion detection capability requires an understanding of the behavior of a cyber-physical system and causality of its components. Such an understanding enables the characterization of normal behavior and the identification and reporting of anomalous behavior. This chapter explores a relatively new time series analysis technique, empirical dynamic modeling, that can contribute to system understanding. Specifically, it examines if the technique can adequately describe causality in cyber-physical systems and provides insights into it serving as a foundation for intrusion detection

Population genetics in compressible flows

We study competition between two biological species advected by a compressible velocity field. Individuals are treated as discrete Lagrangian particles that reproduce or die in a density-dependent fashion. In the absence of a velocity field and fitness advantage, number fluctuations lead to a coarsening dynamics typical of the stochastic Fisher equation. We then study three examples of compressible advecting fields: a shell model of turbulence, a sinusoidal velocity field and a linear velocity sink. In all cases, advection leads to a striking drop in the fixation time, as well as a large reduction in the global carrying capacity. Despite localization on convergence zones, one species goes extinct much more rapidly than in well-mixed populations. For a weak harmonic potential, one finds a bimodal distribution of fixation times. The long-lived states in this case are demixed configurations with a single boundary, whose location depends on the fitness advantage.Comment: 10 pages, 5 figures, submitte

The shear-driven Rayleigh problem for generalised Newtonian fluids

We consider a variant of the classical ‘Rayleigh problem’ (‘Stokes’s first problem’) in which a semi-infinite region of initially quiescent fluid is mobilised by a shear stress applied suddenly to its boundary. We show that self-similar solutions for the fluid velocity are available for any generalised Newtonian fluid, regardless of its constitutive law. We demonstrate how these solutions may be used to provide insight into some generic questions about the behaviour of unsteady, non-Newtonian boundary layers, and in particular the effect of shear thinning or thickening on the thickness of a boundary layer

Ownership and ecosystem as sources of spatial heterogeneity in a forested landscape, Wisconsin, USA

The interaction between physical environment and land ownership in creating spatial heterogeneity was studied in largely forested landscapes of northern Wisconsin, USA. A stratified random approach was used in which 2500-ha plots representing two ownerships (National Forest and private non-industrial) were located within two regional ecosystems (extremely well-drained outwash sands and moderately well-drained moraines). Sixteen plots were established, four within each combination of ownership and ecosystem, and the land cover on the plots was classified from aerial photographs using a modified form of the Anderson (U.S. Geological Survey) land use and land cover classification system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43156/1/10980_2004_Article_206157.pd

Robust estimates of soil moisture and latent heat flux coupling strength obtained from triple collocation

Land surface models (LSMs) are often applied to predict the one-way coupling strength between surface soil moisture (SM) and latent heat (LH) flux. However, the ability of LSMs to accurately represent such coupling has not been adequately established. Likewise, the estimation of SM/LH coupling strength using ground-based observational data is potentially compromised by the impact of independent SM and LH measurements errors. Here we apply a new statistical technique to acquire estimates of one-way SM/LH coupling strength which are nonbiased in the presence of random error using a triple collocation approach based on leveraging the simultaneous availability of independent SM and LH estimates acquired from (1) LSMs, (2) satellite remote sensing, and (3) ground-based observations. Results suggest that LSMs do not generally overestimate the strength of one-way surface SM/LH coupling

Intraseasonal periodicity in the Southern Hemisphere circulation on regional spatial scales

Wave activity in the Southern Hemisphere extratropical atmosphere exhibits robust periodicity on time scales of ~20–25 days. Previous studies have demonstrated the robustness of the periodicity in hemispheric averages of various eddy quantities. Here the authors explore the signature of the periodicity on regional spatial scales. Intraseasonal periodicity in the Southern Hemisphere circulation derives from out-of-phase anomalies in wave activity that form in association with extratropical wave packets as they propagate to the east. In the upper troposphere, the out-of-phase anomalies in wave activity form not along the path of extratropical wave packets, but in their wake. The out-of-phase anomalies in wave activity give rise to periodicity not only on hemispheric scales, but also on synoptic scales when the circulation is sampled along an eastward path between ~5 and 15 m s−1. It is argued that 1) periodicity in extratropical wave activity derives from two-way interactions between the heat fluxes and baroclinicity in the lower troposphere and 2) the unique longitude–time structure of the periodicity in upper-tropospheric wave activity derives from the contrasting eastward speeds of the source of the periodicity in the lower troposphere (~10 m s−1) and wave packets in the upper troposphere (~25 m s−1)