Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation

Owing to a growing number of attacks, the assessment of Industrial Control Systems (ICSs) has gained in importance. An integral part of an assessment is the creation of a detailed inventory of all connected devices, enabling vulnerability evaluations. For this purpose, scans of networks are crucial. Active scanning, which generates irregular traffic, is a method to get an overview of connected and active devices. Since such additional traffic may lead to an unexpected behavior of devices, active scanning methods should be avoided in critical infrastructure networks. In such cases, passive network monitoring offers an alternative, which is often used in conjunction with complex deep-packet inspection techniques. There are very few publications on lightweight passive scanning methodologies for industrial networks. In this paper, we propose a lightweight passive network monitoring technique using an efficient Media Access Control (MAC) address-based identification of industrial devices. Based on an incomplete set of known MAC address to device associations, the presented method can guess correct device and vendor information. Proving the feasibility of the method, an implementation is also introduced and evaluated regarding its efficiency. The feasibility of predicting a specific device/vendor combination is demonstrated by having similar devices in the database. In our ICS testbed, we reached a host discovery rate of 100% at an identification rate of more than 66%, outperforming the results of existing tools.Comment: http://dx.doi.org/10.14236/ewic/ICS2018.

LICSTER -- A Low-cost ICS Security Testbed for Education and Research

Unnoticed by most people, Industrial Control Systems (ICSs) control entire productions and critical infrastructures such as water distribution, smart grid and automotive manufacturing. Due to the ongoing digitalization, these systems are becoming more and more connected in order to enable remote control and monitoring. However, this shift bears significant risks, namely a larger attack surface, which can be exploited by attackers. In order to make these systems more secure, it takes research, which is, however, difficult to conduct on productive systems, since these often have to operate twenty-four-seven. Testbeds are mostly very expensive or based on simulation with no real-world physical process. In this paper, we introduce LICSTER, an open-source low-cost ICS testbed, which enables researchers and students to get hands-on experience with industrial security for about 500 Euro. We provide all necessary material to quickly start ICS hacking, with the focus on low-cost and open-source for education and research

Efeitos genéticos e de ambiente em um rebanho do ecótipo mantiqueira: II. Características produtivas Genetics and environment effects in mantiqueira type breed: II. Productive traits

Por meio de análises uni e bicaracterísticas entre a produção total de leite (PL), produção de gordura (PROG), porcentagem de gordura (PERG), duração da lactação (DL) e período seco (PSECO), objetivou-se, com este trabalho, estimar parâmetros genéticos utilizando-se registros provenientes das cinco primeiras lactações de 1.406 vacas do ecótipo Mantiqueira, filhas de 113 reprodutores, com partos entre os anos de 1977 e 1997, pertencentes ao programa de melhoramento do Pólo Regional do Vale do Paraíba da Agência Paulista de Tecnologia dos Agronegócios da Secretaria de Agricultura e Abastecimento do Estado de São Paulo (APTA/SAA-SP), no município de Pindamonhangaba. Os modelos usados para obtenção das médias dos quadrados mínimos incluíram os efeitos fixos de ano e estação de parto e idade ao parto, além dos efeitos aleatórios de reprodutor e do erro. Para a obtenção dos parâmetros genéticos pela metodologia REML foram utilizados os modelos que ajustavam os efeitos fixos de ano-estação e idade da vaca ao parto, além dos efeitos aleatórios de animal e do erro. As médias ajustadas ± erros-padrão foram: 1863,31 ± 1047,19 kg para a PL; 76,59 ± 31,92 kg para a PROG; 3,43 ± 0,64 % para PERG; 231,72 ± 91,30 dias para DL; e 256,40 ± 180,29 dias para o PSECO. As herdabilidades foram: 0,25; 0,09; 0,00; 0,16 e 0,06, respectivamente, para PL, PROG, PERG, DL e PSECO. As correlações genéticas entre PL e PROG ou PERG foram, respectivamente, de 0,36 e -0,02. De acordo com os resultados obtidos, pode-se inferir que há variação genética aditiva entre vacas para produção de leite.<br>Mantiqueira ecotype breed cows were analyzed to estimate genetic parameters for productive traits using single and multiple traits analysis of total milk production (PL), fat production (PROG), fat percentage (PERG), lactation length (DL) and days dry (PSECO). Records of the first five lactations of 1,406 cows from 113 sires with calving between 1977 and 1997 from the Paraiba Valley Regional Center of Research from São Paulo State (APTA/SAA-SP) breeding program were used. Models to obtain least square means included fixed effects for year and season of calving and age of calving, in addition to random effect of sire and error. The models to obtain the genetic parameters by REML methodology included fixed effects for year-season and age, in addition to random effects of animal and error. Least square means ± standard error were 1863,31 ± 1047,19 kg (PL); 76,59 ± 31,92 kg (PROG); 3,43 ± 0,64 % (PERG); 231,72 ± 91,30 days (DL); and 256,40 ± 180,29 days (PSECO). Estimated values of heritabilities were: 0.25 (PL); 0.09 (PROG); 0.00 (PERG); 0.16 (DL) and 0.06 (PSECO). Genetic correlations of PL with PROG and PERG were 0.36 and 0.02, respectively. These results suggest an additive genetic variation among cows to milk yield