CHURNs : freshness assurance for humans

We present CHURNs, a method for providing freshness and authentication assurances to human users. In computer-to-computer protocols, it has long been accepted that assurances of freshness such as random nonces are required to prevent replay attacks. Typically, no such assurance of freshness is presented to a human in a human-and-computer protocol. A Computer–HUman Recognisable Nonce (CHURN) is a computer-aided random sequence that the human has a measure of control over and input into. Our approach overcomes limitations such as ‘humans cannot do random’ and that humans will follow the easiest path. Our findings show that CHURNs are significantly more random than values produced by unaided humans; that humans may be used as a second source of randomness, and we give measurements as to how much randomness can be gained from humans using our approach; and that our CHURN-generator makes the user feel more in control, thus removing the need for complete trust in devices and underlying protocols. We give an example of how a CHURN may be used to provide assurances of freshness and authentication for humans in a widely used protocol.

Security ceremonies : including humans in cryptographic protocols

Whether by using electronic banking, by using credit cards, or by synchronising a mobile telephone via Bluetooth to an in-car system, humans are a critical part in many cryptographic protocols daily. We reduced the gap that exists between the theory and the reality of the security of these cryptographic protocols involving humans, by creating tools and techniques for proofs and implementations of human-followable security. After three human research studies, we present a model for capturing human recognition; we provide a tool for generating values called Computer-HUman Recognisable Nonces (CHURNs); and we provide a model for capturing human perceptible freshness.

Indicadores de qualidade do leite de vacas criadas no sistema silvipastoril

Pós-graduação em Cirurgia Veterinária - FCAV

Qualidade do leite de vacas criadas no sistema silvipastoril no Vale do Cauca, Colômbia

The silvopastoral system is characterized by increasing the production of milk with a greater number of cows per hectare due to the higher amount of protein in the diet. In silvopastoral system cows are fed in addition to pasture, small trees and shrubs. The aim of this study was determinate the main indicators of milk quality and mastitis causal agents in cows bred on silvopastoral system. We evaluated the composition (fat, total protein, lactose, solids, dry extract, nonfat dry and urea nitrogen), somatic cell count (SCC), total bacterial count (TBC), occurrence of clinical and subclinical mastitis, microbiological isolation, in vitro antimicrobial sensitivity profile and detection of antimicrobial residues in milk produced by 100 cows raised in silvopastoral systems, as well as the bulk tank and churns in farms of Cauca Valley, Colombia. The concentration of the major constituents of milk were 3.24% fat, 3.27% total protein, 4.40% lactose, 10.62% dry extract, 8.57% nonfat dry and 15.82mg/dL urea nitrogen, while the bulk tank and churns was 3.51% fat, 3.20% total protein, 4.34% lactose, 11.72% dry extract, 8.47% nonfat dry and 14.57mg/dL urea nitrogen. The cell count of the cows and the bulk tank was 141,252.75 CS/mL and 363,078.05 CS/mL respectively. The TBC mean in cows and the bulk tank was 4,466.84 CFU/mL and 24,547.01 CFU/mL respectively. The main microorganisms isolated from the udder cows were Corynebacterium bovis, Staphylococcus aureus, Staphylococcus hyicus, Staphylococcus spp., Streptococcus dysgalatiae, while the bulk tank were identified more often Streptococcus spp., Enterobacter cloacae, Hafnia alveii, hemolytic Streptococcus and Streptococcus spp. Antimicrobial residues in cow milk and bulk or churn were detected in 30% and 86% respectively. The silvopastoral system showed to be good alternative to milk production in cow. However is important the care with antimicrobial residues in milk and the analysis of all quality parameters to ensure a differentiated product.