measuring the cost of a pediatric vaccine administration in the uk

Abstract The administration of a vaccine dose involves a series of activities prior to and on the day of vaccine delivery. Total vaccination cost should include the cost of each activity, which is often not done or poorly reported. To calculate those costs a field study was performed in 6 United Kingdom (UK) sites (General Practitioner (GP) practices) during a 4-month period (April–June 2015). First, a workflow map of all the relevant vaccine-related activities per site was obtained through interviews. Second, time estimates for activities happening prior to the vaccination day were obtained through interviews and associated costs were calculated. A prospective, non-interventional study using Time & Motion (T&M) methodology was used to measure time for activities happening on the day of vaccination. Consumables, wastage, and guardian time were also collected. Third, the time for each task and for all tasks combined during the T&M study was analyzed using a random intercept model to account for site effect. Hundred and twenty-three T&M observations with approximately 20 per site were collected and were equally stratified by vaccination visit during the first year of a baby's life. Total cost per visit was £11.9 (site range: £8.6–£17.0) when supply cost and time for activities prior to the vaccination day were included. Time per dose administrated was 7.1 min (site range: 5.7–9.2) and the associated cost was £4.3 (site range: £3.1–£6.2). The study demonstrates an accurate reflection of the time and cost involved in a vaccine dose administration in a pediatric setting in the UK. The amount measured is consistent with the current National Health Services fee schedule

Practical Improvements of Profiled Side-Channel Attacks on a Hardware Crypto-Accelerator

Abstract. This article investigates the relevance of the theoretical frame-work on profiled side-channel attacks presented by F.-X. Standaert et al. at Eurocrypt 2009. The analyses consist in a case-study based on side-channel measurements acquired experimentally from a hardwired crypto-graphic accelerator. Therefore, with respect to previous formal analyses carried out on software measurements or on simulated data, the inves-tigations we describe are more complex, due to the underlying chip’s architecture and to the large amount of algorithmic noise. In this dif-ficult context, we show however that with an engineer’s mindset, two techniques can greatly improve both the off-line profiling and the on-line attack. First, we explore the appropriateness of different choices for the sensitive variables. We show that a skilled attacker aware of the regis-ter transfers occurring during the cryptographic operations can select the most adequate distinguisher, thus increasing its success rate. Sec-ond, we introduce a method based on the thresholding of leakage data to accelerate the profiling or the matching stages. Indeed, leveraging on an engineer’s common sense, it is possible to visually foresee the shape of some eigenvectors thereby anticipating their estimation towards their asymptotic value by authoritatively zeroing weak components containing mainly non-informational noise. This method empowers an attacker, in that it saves traces when converging towards correct values of the secret. Concretely, we demonstrate a 5 times speed-up in the on-line phase of the attack.

Asymptotic information leakage under one-try attacks

We study the asymptotic behaviour of (a) information leakage and (b) adversary’s error probability in information hiding systems modelled as noisy channels. Specifically, we assume the attacker can make a single guess after observing n independent executions of the system, throughout which the secret information is kept fixed. We show that the asymptotic behaviour of quantities (a) and (b) can be determined in a simple way from the channel matrix. Moreover, simple and tight bounds on them as functions of n show that the convergence is exponential. We also discuss feasible methods to evaluate the rate of convergence. Our results cover both the Bayesian case, where a prior probability distribution on the secrets is assumed known to the attacker, and the maximum-likelihood case, where the attacker does not know such distribution. In the Bayesian case, we identify the distributions that maximize the leakage. We consider both the min-entropy setting studied by Smith and the additive form recently proposed by Braun et al., and show the two forms do agree asymptotically. Next, we extend these results to a more sophisticated eavesdropping scenario, where the attacker can perform a (noisy) observation at each state of the computation and the systems are modelled as hidden Markov models

Efficient template attacks

This is the accepted manuscript version. The final published version is available from http://link.springer.com/chapter/10.1007/978-3-319-08302-5_17.Template attacks remain a powerful side-channel technique to eavesdrop on tamper-resistant hardware. They model the probability distribution of leaking signals and noise to guide a search for secret data values. In practice, several numerical obstacles can arise when implementing such attacks with multivariate normal distributions. We propose efficient methods to avoid these. We also demonstrate how to achieve significant performance improvements, both in terms of information extracted and computational cost, by pooling covariance estimates across all data values. We provide a detailed and systematic overview of many different options for implementing such attacks. Our experimental evaluation of all these methods based on measuring the supply current of a byte-load instruction executed in an unprotected 8-bit microcontroller leads to practical guidance for choosing an attack algorithm.Omar Choudary is a recipient of the Google Europe Fellowship in Mobile Security, and this research is supported in part by this Google Fellowship