Benefits of Location-Based Access Control:A Literature Study

Location-based access control (LBAC) has been suggested as a means to improve IT security. By 'grounding' users and systems to a particular location, \ud attackers supposedly have more difficulty in compromising a system. However, the motivation behind LBAC and its potential benefits have not been investigated thoroughly. To this end, we perform a structured literature review, and examine the goals that LBAC can potentially fulfill, \ud the specific LBAC systems that realize these goals and the context on which LBAC depends. Our paper has four main contributions:\ud first we propose a theoretical framework for LBAC evaluation, based on goals, systems and context. Second, we formulate and apply criteria for evaluating the usefulness of an LBAC system. Third, we identify four usage scenarios for LBAC: open areas and systems, hospitals, enterprises, and finally data centers and military facilities. Fourth, we propose directions for future research:\ud (i) assessing the tradeoffs between location-based, physical and logical access control, (ii) improving the transparency of LBAC decision making, and \ud (iii) formulating design criteria for facilities and working environments for optimal LBAC usage

ANWB-enquête niet democratisch

Terwijl de stemcomputers zijn afgeschaft laat minister Eurlings zich nu toch door een internetpoll adviseren, stelt André van Cleeff c.s

Current established risk assessment methodologies and tools

The technology behind information systems evolves at an exponential rate, while at the same time becoming more and more ubiquitous. This brings with it an implicit rise in the average complexity of systems as well as the number of external interactions. In order to allow a proper assessment of the security of such (sub)systems, a whole arsenal of methodologies, methods and tools have been developed in recent years. However, most security auditors commonly use a very small subset of this collection, that best suits their needs. This thesis aims at uncovering the differences and limitations of the most common Risk Assessment frameworks, the conceptual models that support them, as well as the tools that implement them. This is done in order to gain a better understanding of the applicability of each method and/or tool and suggest guidelines to picking the most suitable one

Squeeze-in Functionality for a Soft Parallel Robot Gripper

Grasping parts of inconsistent shapes, sizes and weights securely requires accurate part models and custom gripper fingers. Compliant grippers are a potential solution; however, each design approach requires the solution of unique problems. In this case, the durability and reliability of half lips (at least 1400 cycles) to perform consistently as springs of a specified stiffness (0.5N/mm) and displacement (5mm). Moreover, the challenge of low and small (3mm, 0.01kg bolt or Allen key) objects is addressed through vertical squeeze-in, implemented using an incline, lip and flex limiter as part of a 3D printed TPC spring. The squeeze-in phenomena are verified on large objects through a 30mm, 1.66kg common rail. Experimental results demonstrate the reliability when given a human-specified location for gripping, without the need for jigs or fixtures. Finally, the tested design is assessed for potential fulfillment of 7 of the United Nations sustainable development goals

Balancing Exploration and Exploitation : A Neurally Inspired Mechanism to Learn Sensorimotor Contingencies

The learning of sensorimotor contingencies is essential for the development of early cognition. Here, we investigate how such process takes place on a neural level. We propose a theoretical concept for learning sensorimotor contingencies based on motor babbling with a robotic arm and dynamic neural fields. The robot learns to perform sequences of motor commands in order to perceive visual activation from a baby mobile toy. First, the robot explores the different sensorimotor outcomes, then autonomously decides to utilize (or not) the experience already gathered. Moreover, we introduce a neural mechanism inspired by recent neuroscience research that supports the switch between exploration and exploitation. The complete model relies on dynamic field theory, which consists of a set of interconnected dynamical systems. In time, the robot demonstrates a behavior toward the exploitation of previously learned sensorimotor contingencies and thus selecting actions that induce high visual activation.acceptedVersionPeer reviewe

SingleDemoGrasp : Learning to Grasp From a Single Image Demonstration

Learning-based grasping models typically require a large amount of training data and training time to generate an effective grasping model. Alternatively, small non-generic grasp models have been proposed that are tailored to specific objects by, for example, directly predicting the object's location in 2/3D space, and determining suitable grasp poses by post processing. In both cases, data generation is a bottleneck, as this needs to be separately collected and annotated for each individual object and image. In this work, we tackle these issues and propose a grasping model that is developed in four main steps: 1. Visual object grasp demonstration, 2. Data augmentation, 3. Grasp detection model training and 4. Robot grasping action. Four different vision-based grasp models are evaluated with industrial and 3D printed objects, robot and standard gripper, in both simulation and real environments. The grasping model is implemented in the OpenDR toolkit at: https://github.com/opendr-eu/opendr/tree/master/projects/control/single_demo_grasp.acceptedVersionPeer reviewe

Mobile and adaptive User interface for human robot collaboration in assembly tasks

The manufacturing sector is constantly looking for more efficient ways of production. The Industry 4.0 related technologies such as augmented and mixed reality, connectivity and digitalisation as well as the current trend of robotisation have resulted a number of technical solutions to support the production in factories. The combination of human-robot collaboration and augmented reality shows good promises. The challenges in this case come from the need to reconfigure the physical production layout and how to deliver the digital instructions to the operator. This paper introduces a model for collaborative assembly tasks that uses a mobile user interface based on the depth sensors and a projector. The novelty of this research comes from the adaptivity of the user interface, as it can be freely moved between the tasks around the workstation based on the operator needs and requirements of the tasks. The ability to move projection surface is achieved by detecting the surface position using Aruco markers and computing required transformation of the projector image.acceptedVersionPeer reviewe