IoT Device Identification Using Deep Learning

The growing use of IoT devices in organizations has increased the number of attack vectors available to attackers due to the less secure nature of the devices. The widely adopted bring your own device (BYOD) policy which allows an employee to bring any IoT device into the workplace and attach it to an organization's network also increases the risk of attacks. In order to address this threat, organizations often implement security policies in which only the connection of white-listed IoT devices is permitted. To monitor adherence to such policies and protect their networks, organizations must be able to identify the IoT devices connected to their networks and, more specifically, to identify connected IoT devices that are not on the white-list (unknown devices). In this study, we applied deep learning on network traffic to automatically identify IoT devices connected to the network. In contrast to previous work, our approach does not require that complex feature engineering be applied on the network traffic, since we represent the communication behavior of IoT devices using small images built from the IoT devices network traffic payloads. In our experiments, we trained a multiclass classifier on a publicly available dataset, successfully identifying 10 different IoT devices and the traffic of smartphones and computers, with over 99% accuracy. We also trained multiclass classifiers to detect unauthorized IoT devices connected to the network, achieving over 99% overall average detection accuracy

Privatization and State Capacity in Postcommunist Society

Economists have used cross-national regression analysis to argue that postcommunist economic failure is the result of inadequate adherence liberal economic policies. Sociologists have relied on case study data to show that postcommunist economic failure is the outcome of too close adherence to liberal policy recommendations, which has led to an erosion of state effectiveness, and thus produced poor economic performance. The present paper advances a version of this statist theory based on a quantitative analysis of mass privatization programs in the postcommunist world. We argue that rapid large-scale privatization creates severe supply and demand shocks for enterprises, thereby inducing firm failure. The resulting erosion of tax revenues leads to a fiscal crisis for the state, and severely weakens its capacity and bureaucratic character. This, in turn, reacts back on the enterprise sector, as the state can no longer support the institutions necessary for the effective functioning of a modern economy, thus resulting in deindustrialization. Using cross-national regression techniques we find that the implementation of mass privatization programs negatively impacts measures of economic growth, state capacity and the security of property rights.http://deepblue.lib.umich.edu/bitstream/2027.42/40192/3/wp806.pd

T-MoCA: A valid phone screen for cognitive impairment in diverse community samples

Introduction: There is an urgent need to validate telephone versions of widely used general cognitive measures, such as the Montreal Cognitive Assessment (T-MoCA), for remote assessments. Methods: In the Einstein Aging Study, a diverse community cohort (n = 428; mean age = 78.1; 66% female; 54% non-White), equivalence testing was used to examine concordance between the T-MoCA and the corresponding in-person MoCA assess- ment. Receiver operating characteristic analyses examined the diagnostic ability to dis- criminate between mild cognitive impairment and normal cognition. Conversion meth- ods from T-MoCA to the MoCA are presented. Results: Education, race/ethnicity, gender, age, self-reported cognitive concerns, and telephone administration difficulties were associated with both modes of administra- tion; however, when examining the difference between modalities, these factors were not significant. Sensitivity and specificity for the T-MoCA (using Youden’s index opti- mal cut) were 72% and 59%, respectively. Discussion: The T-MoCA demonstrated sufficient psychometric properties to be use- ful for screening of MCI, especially when clinic visits are not feasible

The differential diagnosis of chronic daily headaches: an algorithm-based approach

Chronic daily headaches (CDHs) refers to primary headaches that happen on at least 15 days per month, for 4 or more hours per day, for at least three consecutive months. The differential diagnosis of CDHs is challenging and should proceed in an orderly fashion. The approach begins with a search for “red flags” that suggest the possibility of a secondary headache. If secondary headaches that mimic CDHs are excluded, either on clinical grounds or through investigation, the next step is to classify the headaches based on the duration of attacks. If the attacks last less than 4 hours per day, a trigeminal autonomic cephalalgia (TAC) is likely. TACs include episodic and chronic cluster headache, episodic and chronic paroxysmal hemicrania, SUNCT, and hypnic headache. If the duration is ≥4 h, a CDH is likely and the differential diagnosis encompasses chronic migraine, chronic tension-type headache, new daily persistent headache and hemicrania continua. The clinical approach to diagnosing CDH is the scope of this review

A measurement of the W boson mass using large rapidity electrons

We present a measurement of the W boson mass using data collected by the D0 experiment at the Fermilab Tevatron during 1994--1995. We identify W bosons by their decays to e-nu final states where the electron is detected in a forward calorimeter. We extract the W boson mass, Mw, by fitting the transverse mass and transverse electron and neutrino momentum spectra from a sample of 11,089 W -> e nu decay candidates. We use a sample of 1,687 dielectron events, mostly due to Z -> ee decays, to constrain our model of the detector response. Using the forward calorimeter data, we measure Mw = 80.691 +- 0.227 GeV. Combining the forward calorimeter measurements with our previously published central calorimeter results, we obtain Mw = 80.482 +- 0.091 GeV

Measurement of the WW Boson Mass

A measurement of the mass of the $W$ boson is presented based on a sample of 5982 $W \rightarrow e \nu$ decays observed in $p\overline{p}$ collisions at $\sqrt{s}$ = 1.8~TeV with the D\O\ detector during the 1992--1993 run. From a fit to the transverse mass spectrum, combined with measurements of the $Z$ boson mass, the $W$ boson mass is measured to be $M_W = 80.350 \pm 0.140 (stat.) \pm 0.165 (syst.) \pm 0.160 (scale) GeV/c^2$.Comment: 12 pages, LaTex, style Revtex, including 3 postscript figures (submitted to PRL

Direct Measurement of the Top Quark Mass at D0

We determine the top quark mass m_t using t-tbar pairs produced in the D0 detector by \sqrt{s} = 1.8 TeV p-pbar collisions in a 125 pb^-1 exposure at the Fermilab Tevatron. We make a two constraint fit to m_t in t-tbar -> b W^+bbar W^- final states with one W boson decaying to q-qbar and the other to e-nu or mu-nu. Likelihood fits to the data yield m_t(l+jets) = 173.3 +- 5.6 (stat) +- 5.5 (syst) GeV/c^2. When this result is combined with an analysis of events in which both W bosons decay into leptons, we obtain m_t = 172.1 +- 5.2 (stat) +- 4.9 (syst) GeV/c^2. An alternate analysis, using three constraint fits to fixed top quark masses, gives m_t(l+jets) = 176.0 +- 7.9 (stat) +- 4.8 (syst) GeV/C^2, consistent with the above result. Studies of kinematic distributions of the top quark candidates are also presented.Comment: 43 pages, 53 figures, 33 tables. RevTeX. Submitted to Phys. Rev.

The Azimuthal Decorrelation of Jets Widely Separated in Rapidity

This study reports the first measurement of the azimuthal decorrelation between jets with pseudorapidity separation up to five units. The data were accumulated using the D{\O}detector during the 1992--1993 collider run of the Fermilab Tevatron at $\sqrt{s}=$ 1.8 TeV. These results are compared to next--to--leading order (NLO) QCD predictions and to two leading--log approximations (LLA) where the leading--log terms are resummed to all orders in $\alpha_{\scriptscriptstyle S}$. The final state jets as predicted by NLO QCD show less azimuthal decorrelation than the data. The parton showering LLA Monte Carlo {\small HERWIG} describes the data well; an analytical LLA prediction based on BFKL resummation shows more decorrelation than the data.Comment: 6 pages with 4 figures, all uuencoded and gzippe

Probing BFKL Dynamics in the Dijet Cross Section at Large Rapidity Intervals in ppbar Collisions at sqrt{s}=1800 and 630 GeV

Inclusive dijet production at large pseudorapidity intervals (delta_eta) between the two jets has been suggested as a regime for observing BFKL dynamics. We have measured the dijet cross section for large delta_eta in ppbar collisions at sqrt{s}=1800 and 630 GeV using the DO detector. The partonic cross section increases strongly with the size of delta_eta. The observed growth is even stronger than expected on the basis of BFKL resummation in the leading logarithmic approximation. The growth of the partonic cross section can be accommodated with an effective BFKL intercept of a_{BFKL}(20GeV)=1.65+/-0.07.Comment: Published in Physical Review Letter

Search for Top Squark Pair Production in the Dielectron Channel

This report describes the first search for top squark pair production in the channel stop_1 stopbar_1 -> b bbar chargino_1 chargino_1 -> ee+jets+MEt using 74.9 +- 8.9 pb^-1 of data collected using the D0 detector. A 95% confidence level upper limit on sigma*B is presented. The limit is above the theoretical expectation for sigma*B for this process, but does show the sensitivity of the current D0 data set to a particular topology for new physics.Comment: Five pages, including three figures, submitted to PRD Brief Report