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Se realizó un estudio con el objetivo de evaluar los intervalos de corte (30, 60 y 90 días) y el manejo de la nutrición en la morera: sin fertilizantes minerales ni canavalia intercalada e inoculada con HMA (F0); fertilización mineral a razón de 150 y 75 kg ha-1 de N y K2O por época del año (FM), respectivamente; y canavalia intercalada e inoculada con HMA (CeHMA). El diseño fue de bloques al azar con arreglo factorial, y el suelo se clasifica como Ferralítico Rojo lixiviado. En la época lluviosa, los mayores rendimientos se obtuvieron con CeHMA y corte cada 90 días (entre 10,99 y 6,85 kg ha-1 de MS), y en la época poco lluviosa este indicador fue mayor en FM (entre 3,56 y 2,52 kg ha-1 de MS). La producción de biomasa comestible por corte a los 90 días mostró diferencias entre tratamientos a favor de FM en el primer corte y de CeHMA en el segundo corte. CeHMA con el intervalo de 90 días alcanzó una proporción de hojas superior a la media poblacional en la época lluviosa, no así en la poco lluviosa. El rendimiento de PB en la época lluviosa fue mayor en FM con los intervalos de 60 y 90 días, y en CeHMA en el intervalo de 90 días. Se concluye que el intervalo de corte cada 90 días fue el mejor, y que resultó factible intercalar la canavalia inoculada con HMA en la época de lluvia. La época del año determinó la cuantía de la producción de forraje y de proteína bruta, la cual fue tres veces mayor en la época lluviosa.

Se realizó un estudio con el objetivo de determinar el efecto del ácido naftilacético (ANA) y el agua sobre la supervivencia y el desarrollo foliar de propágulos de Morus alba, y para ello se empleó un diseño de bloques completamente aleatorizados con arreglo factorial. Los tratamientos consistieron en tres variedades: tigreada, yu-62 y universidad mejorada, y dos sustancias estimuladoras del enraizamiento de los propágulos: ANA y agua, además del testigo (sin productos). Se midió la cantidad de plantas que sobrevivieron y el peso verde del área foliar. Los propágulos de la var. tigreada mostraron entre 91 y 100 % de sobrevivencia; en el caso de las var. yu-62 y universidad mejorada, este indicador fue favorecido por el uso del ANA y el agua. El menor peso del área foliar lo presentó la var. universidad mejorada (14,55 g), al no ser inoculada. Este estudio permite concluir que la variedad tigreada sobresalió en términos de supervivencia, por lo que se considera una de las de mayor potencialidad en cuanto establecimiento y eficiencia en la reproducción asexual. Con el uso del agua como vehículo enraizador se puede lograr la propagación de las variedades nuevas (universidad mejorada y yu- 62); además, el agua y el ANA permitieron que las plantas expresaran un desarrollo adecuado de su área foliar desde edades tempranas.

En un suelo Ferralítico Rojo lixiviado, en condiciones de secano, se determinó el efecto del intercalamiento de Canavaliaensiformis (L.) inoculada con HMA, complementada con fertilizante mineral, en la producción de forraje de morera y en el estado nutricional de las plantas. Los tratamientos se formaron por la combinación del intercalamiento de C. ensiformis (canavalia) inoculada con HMA (con CeHMA) o no (sinCeHMA) y las dosis de fertilizante mineral (F0: sin fertilizante; F1: 100-50-50 kg ha-1 de N, P2O5 y K2O en cada época; F2: 200-100-100 kg ha-1 de N, P2O5 y K2O en cada época). Se empleó un diseño de bloques al azar con arreglo factorial. Los mayores rendimientos se alcanzaron con CeHMA, complementada con F1 (12,15 y 16,65 t ha-1 para los años 1 y 2 respectivamente), sin diferencias de F2 sin canavalia en tres de las cuatro épocas evaluadas. En la época de lluvia se produjo el 76 % del rendimiento total del año. Existió una relación alta y significativa entre el rendimiento estacional y el acumulado de lluvia caída, con coeficiente de determinación de 0,97. La morera con CeHMA, complementada con fertilizante, logró mantene rrendimientos estables entre los cortes en cada época evaluada. El rendimiento en la época lluviosa varió en función de la concentración de N en las hojas, que alcanzó 32,6 g kg-1 de MS. Se concluye que el intercalamiento de canavalia inoculada con HMA, complementada con el tratamiento F1, produjo un mayor rendimiento de biomasa comestible de morera y un mejor estado nutricional de las plantas en términos de concentración de N en las hojas.

Industrial Control Systems (ICS) collect information from a variety of sensors throughout the process, and then use that information to control some physical components. Control engineers usually have to pick which measurements they are going to use and then they purchase sensors to take these measurements. However, in most cases they only need a small subset of all possible measurements that can be used. Economic and efficiency reasons motivate engineers to use only a small number of sensors for controlling a system; however, as attacks against industrial systems continue to increase, we need to study a systematic way to add sensors to the system to identify potentially malicious attacks. We propose the addition of hidden sensor measurements to a system to improve its security. Hidden sensor measurements are by our definition measurements that were not considered in the original design of the system, and are not used for any operational reason. We only add them to improve the security of the system and using them in anomaly detection and mitigation. We show the addition of these new, independent, but correlated measurements to the system makes it harder for adversaries to launch false-data injection stealthy attacks and, even if they do, it is possible to limit the impact caused by those attacks. When an attack is detected, we replace the compromised sensor measurements with estimated ones from the new sensors improving the risky open-loop simulations proposed by previous work.

In the past decade we have seen an active research community proposing attacks and defenses to Cyber-Physical Systems (CPS). Most of these attacks and defenses have been heuristic in nature, limiting the attacker to a set of predefined operations, and proposing defenses with unclear security guarantees. In this paper, we propose a generic adversary model that can capture any type of attack (our attacker is not constrained to follow specific attacks such as replay, delay, or bias) and use it to design security mechanisms with provable security guarantees. In particular, we propose a new secure design paradigm we call DARIA: Designing Actuators to Resist arbItrary Attacks. The main idea behind DARIA is the design of physical limits to actuators in order to prevent attackers from arbitrarily manipulating the system, irrespective of their point of attack (sensors or actuators) or the specific attack algorithm (bias, replay, delays, etc.). As far as we are aware, we are the first research team to propose the design of physical limits to actuators in a control loop in order to keep the system secure against attacks. We demonstrate the generality of our proposal on simulations of vehicular platooning and industrial processes.

Unmanned Vehicles (UVs), including aerial, sea, and ground vehicles, include remotely operated vehicles and autonomous vehicles. The use of these vehicles is increasing rapidly, from military operations to the consumer space. UVs assess their environment (or relay it to the remote operator) with a variety of sensors and actuators that allow them to perform specific tasks such as navigating a route, hovering, or avoiding collisions. So far, UVs tend to trust the information provided by their sensors to make navigation decisions without data validation or verification. Therefore, attackers can exploit these limitations by feeding erroneous sensor data to disrupt or take control of the system. In this paper, we leverage the Dynamic Data Driven Application Systems (DDDAS) paradigm to design and implement an architecture for securing unmanned vehicles. We argue that DDDAS principles are a perfect fit to secure feedback-control systems with protections that classical security mechanisms cannot provide. In particular, by using exact models of the vehicle dynamics, we can compare and correlate their expected behavior (given by the models) with the values from data acquisition. If there is a persistent anomaly, we can replace sensor values with models, or fuse other sensors to replace the missing ones, enabling the vehicle to maintain safety in the immediate future.

Cyber-Physical Systems (CPS) have traditionally been considered more static, with regular communication patterns when compared to classical information technology networks. Because the structure of most CPS remains unchanged during long periods of time, they become vulnerable to adversaries who can tailor their attacks based on their precise knowledge of the system dynamics, communications, and control. Moving Target Defense (MTD) has emerged as a strategy to add uncertainty about the state and execution of a system in order to prevent adversaries from having predictable effects with their attacks. In this work we propose a novel type of MTD strategy that randomly changes the availability of the sensor data, so that it is harder for adversaries to tailor stealthy attacks and at the same time it can minimize the impact of false-data injection attacks. Using tools from switched control systems we formulate an optimization problem to find the probability of the switching signals that increase the visibility of stealthy attacks while decreasing the deviation caused by false data injection attacks.

The performance of different anomaly detection algorithms is typically compared using metrics that depend on the true positive rate (TPR) and the false positive rate (FPR). However, to obtain the TPR it is necessary to generate attacks that will be detected, which is useless to evaluate detection strategies against more realistic adversaries that can adapt their attacks to remain undetected. On the other hand, the FPR can be misleading and hard to interpret in practical applications since the amount of time a process is observed is not fixed. In this poster, we present a novel metric that is based on the maximum impact an adversary can cause while remaining stealthy, and on the expected time between false alarms. Our metric is useful for the evaluation and comparison of anomaly detection strategies in CPS.

In the past years we have seen an emerging field of research focusing on using the “physics” of a Cyber-Physical System to detect attacks. In its basic form, a security monitor is deployed somewhere in the industrial control network, observes a time-series of the operation of the system, and identifies anomalies in those measurements in order to detect potentially manipulated control commands or manipulated sensor readings. While there is a growing literature on detection mechanisms in that research direction, the problem of where to monitor the physical behavior of the system has received less attention. In this paper, we analyze the problem of where should we monitor these systems, and what attacks can and cannot be detected depending on the location of this network monitor. The location of the monitor is particularly important, because an attacker can bypass attack-detection by lying in some network interfaces while reporting that everything is normal in the others. Our paper is the first detailed study of what can and cannot be detected based on the devices an attacker has compromised and where we monitor our network. We show that there are locations that maximize our visibility against such attacks. Based on our analysis, we design a low-level security monitor that is able to directly observe the field communication between sensors, actuators, and Programmable Logic Controllers (PLCs). We implement that security monitor in a realistic testbed, and demonstrate that it can detect attacks that would otherwise be undetected at the supervisory network.

A 10‐year monitoring program was developed to quantify the population dynamics of the long‐snouted seahorse population in the Mar Menor coastal lagoon. Based on 985 underwater visual censuses, we estimated the long‐snouted seahorse (Hippocampus guttulatus Cuvier, 1829) population size in the Mar Menor lagoon and its reduction in size in the last decades, as well as the effect of eutrophication crises in 2016 and 2019 on the species. The annual recruitment for the 2013–2020 period was estimated by comparing the relative abundance of early seahorse life stages in the ichthyoplankton. The density ranged from 0.0458 specimens/m3 at the beginning of the sampling period to 0.0004 at the end, showing a statistically significant difference between the three analyzed periods (Hgl=2 = 14.0, p = 0.001). The long‐snouted seahorse population from the Mar Menor lagoon exemplifies the impact of fishing activities and human pressure, especially euxinic episodes and habitat destruction. As a result of this, the Mar Menor population has decreased from several million specimens to a few thousand, in only three decades. This species showed considerable resilience, the seahorse population began to recover once fishing activity stopped. In contrast, the long‐snouted seahorse showed high vulnerability to habitat loss and an episodic flooding event. Adult seahorses showed preferences for highly complex habitats, especially Caulerpa prolifera–Cymodocea nodosa mixed meadows and habitats of high complexity and anthropogenic origin, such as harbors, jetties, or breakwaters. In contrast, juvenile seahorses preferred monotonous seabeds with low complexity, such as the sandy beds that are characteristic of the Mar Menor lagoon littoral. [ABSTRACT FROM AUTHOR]