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Realizing access control to sensitive data offloaded to a Cloud is challenging in the Internet of Things, where various devices with low computational power and different security levels are interconnected. Despite various solutions, the National Institute of Standards and Technology (NIST)’s Attribute-Based Access Control (ABAC) model is one of the preferred techniques in the literature. In this model, users who satisfy access policies using both static and dynamic attributes are allowed to access the data. However, NIST’s ABAC model does not support encryption and therefore does not satisfy data confidentiality. Attribute-Based Encryption (ABE) is a known cryptographic primitive that enables fine-grained access control over encrypted data. However, currently the existing ABE schemes do not meet NIST’s ABAC requirements or are not computationally efficient enough for IoT applications. In this paper, we propose a Multi-Level Security ABAC (MLS-ABAC) scheme that satisfies the requirements of NIST’s ABAC model. Our construction is efficient and relies on a decryption outsourceable Ciphertext-Policy ABE scheme. Additionally, based on realistic application scenarios, only the authorized data users can decrypt the ciphertext, and check the integrity of the retrieved message. Furthermore, we present both conceptual and formal models for our proposed MLS-ABAC architecture along with performance metrics. The experimental results show that the proposed MLS-ABAC achieves a constant ciphertext size of ∼230 bytes and with encryption and decryption running times of ∼18 and ∼10 milliseconds, respectively, independent of the number of attributes.

The use of the Internet of Things (IoT) in the electronic health (e-health) management systems brings with it many challenges, including secure communications through insecure radio channels, authentication and key agreement schemes between the entities involved, access control protocols and also schemes for transferring ownership of vital patient information. Besides, the resource-limited sensors in the IoT have real difficulties in achieving this goal. Motivated by these considerations, in this work we propose a new lightweight authentication and ownership transfer protocol for e-health systems in the context of IoT (LACO in short). The goal is to propose a secure and energy-efficient protocol that not only provides authentication and key agreement but also satisfies access control and preserves the privacy of doctors and patients. Moreover, this is the first time that the ownership transfer of users is considered. In the ownership transfer phase of the proposed scheme, the medical server can change the ownership of patient information. In addition, the LACO protocol overcomes the security flaws of recent authentication protocols that were proposed for e-health systems, but are unfortunately vulnerable to traceability, de-synchronization, denial of service (DoS), and insider attacks. To avoid past mistakes, we present formal (i.e., conducted on ProVerif language) and informal security analysis for the LACO protocol. All this ensures that our proposed scheme is secure against the most common attacks in IoT systems. Compared to the predecessor schemes, the LACO protocol is both more efficient and more secure to use in e-health systems.

Joint Torque sensory Feedback (JTF) can substantially improve the performance of a robotic system. JTF makes it possible to achieve dynamic control of a robotic manipulator without the need for modeling its link dynamics. Moreover, it has been proved that JTF can achieve a precise torque tracking in a manipulator joint by compensating the e ect of joint friction and actuator nonlinearities. Despite these advantages, accurate joint torque measurement encounters several practical challenges. Since much of the torque/force reaction of the link load on the joints appears in the form of nontorsional components, e.g. overhung force and bending moment, the torque sensing device has to not only bear but remain insensitive to these force/moment components. In addition, it is desirable to design the structure of the sensor such that it generates a large strain for a given load torque and therefore has a high sensitivity. However, this is in conflict with the high-sti ness requirement for minimizing the joint angle error introduced by the sensor. The main objectives of this chapter are twofold: Firstly, in Sections 2 and 3, we describe the technical challenges and practical solutions to accurate measurement of joint torques in the presence of the non-torsional components in a robot joint. For a torque sensing device, di erent mechanical structures will be examined and their properties, such as sensitivity and sti ness in di erent directions and decoupling, will be explored. This allows a systematic design of a sensor structure which is suitable for torque measurement in a robot joint. Finally, the state-of-the-art and design of a torque sensor for robots will be presented in Section 4. The design achieves the conflicting requirements of high sti ness for all six force and torque components, high sensitivity for the one driving torque of interest, yet very low sensitivity for the other five force/torque components. These properties, combined with its donut shape and small size make this sensor an ideal choice for direct drive robotic applications. Experimental data validates the basic design ideas underlying the sensor’s geometry, the finite element model utilized in its optimization, and the advertised performance. The second objective is to describe the application of joint torque sensory feedback (JTF)in robot control. The main advantages claimed for JTF are (i) it can simplify the complexity of the system dynamics by eliminating its link dynamics; and (ii) the control system is inherently robust with respect to both external force disturbance and parameter variation. First, assuming both actuator and torque sensor are ideal, we describe robot control with JTF in Section 5. Then, development of an adaptive JTF is presented in Section 6that requires only the incorporation of uncalibrated joint torque signals, i.e., the gains and o sets of multiple sensors are unknown. Also, all physical parameters of the joints including inertia of the rotors, link twist angles, and friction parameters are assumed unknown to the

Multi-body systems’ (MBS) dynamics are often described by the second-order nonlinear equations parameterized by a configuration-dependent inertia matrix and the nonlinear vector containing the Coriolis and centrifugal terms. Since these equations are the cornerstone for simulation and control of robotic manipulators, many researchers have attempted to develop efficient modelling techniques to derive the equations of motion of multi-body systems in novel forms. A unifying idea for most modeling techniques is to describe the equations of motion in terms of general coordinates and their time–derivatives. In classical mechanics of constrained systems, a generalized velocity is taken to be an element of tangential space of configuration manifold, and a generalized force is taken to be the cotangent space. However, neither does space possess a natural metric as the generalized coordinates or the constrains may have a combination of rotational and translational components. As a result, the corresponding dynamic formulation in not invariant and a solution depends on measure units or a weighting matrix selected Aghili (2005); Angeles (2003); Lipkin and Duffy (1988); Luca and Manes (1994); Manes (1992). There also exist other techniques to describe the equations of motion in terms of quasi–velocities, i.e., a vector whose Euclidean norm is proportional to the square root of the system’s kinetic energy, which can lead to simplification of these equations Aghili (2008; 2007); Bedrossian (1992); Gu (2000); Gu and Loh (1987); Herman (2005); Herman and Kozlowski (2006); Jain and Rodriguez (1995); Junkins and Schaub (1997); Kodischeck (1985); Kozlowski (1998); Loduha and Ravani (1995); Papastavridis (1998); Rodriguez and Kertutz-Delgado (1992); Sinclair et al. (2006); Spong (1992). A recent survey on some of these techniques can be found in Herman and Kozlowski (2006). In short, the square–root factorization of mass matrix is used as a transformation to obtain the quasi–velocities, which are a linear combination of the velocity and the generalized coordinates Herman and Kozlowski (2006); Papastavridis (1998). It was shown by Kodistchek Kodischeck (1985) that if the square–root factorization of the inertia matrix is integrable, then the robot dynamics can be significantly simplified. In such a case, transforming the generalized coordinates to quasi–coordinates by making use of the integrable factorization modifies the robot dynamics to a system of double integrator. Then, the cumbersome derivation of the Coriolis and centrifugal terms is not required. It was later realized by Gu et al. Gu and Loh (1987) that such a transformation is a canonical transformation because it satisfies Hamilton’s equations. Rather than deriving the mass matrix of MBS first and then obtaining its factorization, Rodriguez et al. Rodriguez and Kertutz-Delgado (1992)

Recently, blockchain-based Internet of Medical Things (IoMT) has started to receive more attention in the healthcare domain as it not only improves the care quality using real-time and continuous monitoring but also minimizes the cost of care. However, there is a clear trend to include many entities in IoMT systems, such as IoMT sensor nodes, IoT wearable medical devices, patients, healthcare centers, and insurance companies. This makes it challenging to design a blockchain framework for these systems where scalability is a most critical factor in blockchain technology. Motivated by this observation, in this survey we review the state-of-the-art in blockchain-IoMT systems. Comparison and analysis of such systems prove that there is a substantial gap, which is the negligence of scalability. In this survey, we discuss several approaches proposed in the literature to improve the scalability of blockchain technology, and thus overcoming the above mentioned research gap. These approaches include on-chain and off-chain techniques, based on which we give recommendations and directions to facilitate designing a scalable blockchain-based IoMT system. We also recommended that a designer considers the well-known trilemma along with the various dimensions of a scalable blockchain system to prevent sacrificing security and decentralization as well. Moreover, we raise several research questions regarding benchmarking; addressing these questions could help designers determining the existing bottlenecks, leading to a scalable blockchain.

This paper presents development of an optimal feedback linearization control for interior permanent magnet synchronous machines operating in a nonsteady-state operating point, i.e., varying torque and speed, to achieve precision tracking performance and energy saving by minimizing the copper loss. An isomorphism mapping between the dq axes phase voltages and two auxiliary control inputs over full ranges of torque and speed is established by the linearization controller using the notion of orthogonal projection. The auxiliary control inputs are defined to be exclusively responsible for torque generation and power consumption. Subsequently, an analytical solution for the optimal-linearization control is derived in a closed form by applying the Hamiltonian of optimal control theory in conjunction with the Pontryagin's minimum principle. The optimal controller takes the maximum voltage limit and torque tracking constraint into account while maximizing machine efficiency for nonconstant operational load torque and speed. Unlike the convectional quadratic regulator-based control of electric motors, the proposed control approach does not rely on steady-state operation conditions and hence, it is suitable for such applications as electric vehicles and robotics. Experimental results demonstrate torque-tracking and energy-efficiency performance of a motor operating with nonconstant torque.

In recent years, RFID (radio-frequency identification) systems are widely used in many applications. One of the most important applications for this technology is the Internet of things (IoT). Therefore, researchers have proposed several authentication protocols that can be employed in RFID-based IoT systems, and they have claimed that their protocols can satisfy all security requirements of these systems. However, in RFID-based IoT systems we have mobile readers that can be compromised by the adversary. Due to this attack, the adversary can compromise a legitimate reader and obtain its secrets. So, the protocol designers must consider the security of their proposals even in the reader compromised scenario. In this paper, we consider the security of the ultra-lightweight RFID mutual authentication (ULRMAPC) protocol recently proposed by Fan et al. They claimed that their protocol could be applied in the IoT systems and provide strong security. However, in this paper we show that their protocol is vulnerable to denial of service, reader and tag impersonation and de-synchronization attacks. To provide a solution, we present a new authentication protocol, which is more secure than the ULRMAPC protocol and also can be employed in RFID-based IoT systems.

This technical note presents a non-minimal order dynamics model for many analysis, simulation, and control problems of constrained mechanical systems passing through singular configurations during their motion by making use of linear projection operator. The distinct features of this model describing dynamics of the dependent coordinates are: i) The mass matrix $\bar{M}(q)$ is always positive definite even at singular configurations; ii) matrix $\dot{\bar{M}}-2\bar{C}$ is skew symmetric, where all nonlinear terms are lumped into vector $\bar{C}(q,\dot{q})\dot{q}$ after elimination of constraint forces. Eigenvalue analysis shows that the condition number of the constraint mass matrix can be minimized upon adequate selection of a scalar parameter called “virtual mass” thereby reducing the sensitivity to round-off errors in numerical computation. It follows by derivation of two oblique projection matrices for computation of constraint forces and actuation forces. It is shown that projection-based model allows feedback control of dependent coordinates which, unlike reduced-order dependent coordinates, uniquely define spatial configuration of constrained systems.

Heterogeneous wireless sensor networks (HWSNs) are employed in many real-time applications, such as Internet of sensors (IoS), Internet of vehicles (IoV), healthcare monitoring, and so on. As wireless sensor nodes have constrained computing, storage and communication capabilities, designing energy-efficient authentication protocols is a very important issue in wireless sensor network security. Recently, Amin et al. presented an untraceable and anonymous three-factor authentication (3FA) scheme for HWSNs and argued that their protocol is efficient and can withstand the common security threats in this sort of networks. In this article, we show how their protocol is not immune to user impersonation, de-synchronization and traceability attacks. In addition, an adversary can disclose session key under the typical assumption that sensors are not tamper-resistant. To overcome these drawbacks, we improve the Amin et al.&rsquo, s protocol. First, we informally show that our improved scheme is secure against the most common attacks in HWSNs in which the attacks against Amin et al.&rsquo, s protocol are part of them. Moreover, we verify formally our proposed protocol using the BAN logic. Compared with the Amin et al.&rsquo, s scheme, the proposed protocol is both more efficient and more secure to be employed which renders the proposal suitable for HWSN networks.

This paper presents an analytical closed-form solution to improper integral $\mu(r)=\int_0^{\infty} x^r dx$, where $r \geq 0$. The solution technique is based on splitting the improper integral into an infinite sum of definite integrals with successive integer limits. The exact solution of every definite integral is obtained by making use of the binomial polynomial expansion, which then allows expression of the entire summation equivalently in terms of a weighted sum of Riemann zeta functions. It turns out that the solution fundamentally depends on whether or not $r$ is an integer. If $r$ is a non-negative integer, then the solution is manifested in a finite series of weighted Bernoulli numbers, which is then drastically simplified to a second order rational function $\mu(r)=(-1)^{r+1}/(r+1)(r+2)$. This is achieved by taking advantage of the relationships between Bernoulli numbers and binomial coefficients. On the other hand, if $r$ is a non-integer real-valued number, then we prove $\mu(r)=0$ by the virtue of the elegant relationships between zeta and gamma functions and their properties., Comment: 7 pages, 1 figure

Visually guided robotic capturing of a moving object often requires long-term prediction of the object motion not only for a smooth capture but because visual feedback may not be continually available, e.g., due to vision obstruction by the robotic arm, as well. This paper presents a combined prediction and motion-planning scheme for robotic capturing of a drifting and tumbling object with unknown dynamics using visual feedback. A Kalman filter estimates the states and a set of dynamics parameters of the object needed for long-term prediction of the motion from noisy measurements of a vision system. Subsequently, the estimated states, parameters, and predicted motion trajectories are used to plan the trajectory of the robot's end-effector to intercept a grapple fixture on the object with zero relative velocity (to avoid impact) in an optimal way. The optimal trajectory minimizes a cost function, which is a weighted linear sum of travel time, distance, cosine of a line-of-sight angle (object alignment for robotic grasping), and a penalty function acting as a constraint on acceleration magnitude. Experiments are presented to demonstrate the robot-motion planning scheme for autonomous grasping of a tumbling satellite. Two robotics manipulators are employed: One arm drifts and tumbles the mockup of a satellite, and the other arm that is equipped with a robotic hand tries to capture a grapple fixture on the satellite using the visual guidance system.

Fault tolerance is critical for servomotors used in high-risk applications, such as aerospace, robots, and military. These motors should be capable of continued functional operation, even if insulation failure or open-circuit of a winding occur. This paper presents a fault-tolerant (FT) torque controller for brushless dc (BLdc) motors that can maintain accurate torque production with minimum power dissipation, even if one of its phases fails. The distinct feature of the FT controller is that it is applicable to BLdc motors with any back-electromotive-force waveform. First, an observer estimates the phase voltages from a model based on Fourier coefficients of the motor waveform. The faulty phases are detected from the covariance of the estimation error. Subsequently, the phase currents of the remaining phases are optimally reshaped so that the motor accurately generates torque as requested while minimizing power loss subject to maximum current limitation of the current amplifiers. Experimental results illustrate the capability of the FT controller to achieve ripple-free torque performance during a phase failure at the expenses of increasing the mean and maximum power loss by 28% and 68% and decreasing the maximum motor torque by 49%.

This paper presents a new conceptual design for reconfigurable robots. Unlike conventional reconfigurable robots, our design does not achieve reconfigurability by utilizing modular joints. Rather, the robot is equipped with passive joints, i.e., joints without actuator or sensor, which permit changing the Denavit-Hartenberg (DH) parameters such as the link length and twist angle. The passive joints will become controllable when the robot forms a closed kinematic chain. Also, each passive joint is equipped with a built-in brake mechanism that is normally locked, but the lock can be released whenever the parameters are to be changed. Such a versatile and agile robot is particularly suitable for space application for its simple, compact, and light design. The kinematics and recalibration of this kind of reconfigurable robot are thoroughly analyzed. A stable reconfiguration-control algorithm is devised to take the robot from one configuration to another by directly regulating the passive joints to the associated, desired DH parameters. Conditions for the observability and the controllability of the passive joints are also derived in detail.

This paper presents a method to control a manipulator system grasping a rigid-body payload so that the motion of the combined system as a consequence of external applied forces is the same as any other free-floating rigid-body (with different inertial properties). This allows 0-g emulation of a scaled spacecraft prototype under the test in a 1-g laboratory environment. The controller consisting of motion feedback and force/moment feedback adjusts the motion of the test spacecraft so as to match that of the flight spacecraft, even if the latter has flexible appendages (such as solar panels) and the former is rigid. The stability of the overall system is analytically investigated, and the results show that the system remains stable provided that the inertial properties of two spacecraft are different and that an upperbound on the norm of the inertia ratio of the payload to the manipulator is respected. Important practical issues such as calibration and sensitivity analysis to sensor noise and quantization are also presented. Finally, experimental results obtained from a robotic setup for spacecraft emulation with a milli-gravity accuracy are presented.

Model uncertainty is an important factor hindering reliability of any model-based failure detection and identification (FDI) method. Use of joint torque sensing reduces significantly the complexity of robot modeling by excluding hardly-identifiable link dynamics from overall manipulator dynamics. Application of such model in the proposed FDI filter increases reliability of fault monitoring against modeling uncertainty. The proposed filter is based on a smooth velocity observer of degree 2 n where n stands for the number of manipulator joints. No velocity measurement and assumption on smoothness of faults are used in the fault detection process.

This paper describes the design and control of an integrated direct-drive joint suitable for applications that require a high-precision motion control system. The joint integrates a direct-drive synchronous motor with axial air gap, a torque sensor, and a high-resolution position sensor. The key design aspects of the integrated joint, like the motor's armature, cooling system, motor housing, bearing arrangement, sensors, and power electronics are detailed. We also present a number of advanced implementations in motor torque control, optimal joint torque sensory feedback, and motion control using positive joint torque feedback. Experimental results illustrate an outstanding performance regarding thermal response, torque ripple, reference trajectory tracking, torque disturbance rejection, and joint stiffness.

The application of joint-torque sensory feedback (JTF) in robot control has been proposed in the past as a substitute for the computed torque method. A controller based on JTF does not require computation of link dynamics. However, the traditional JTF assumes precise measurement of joint torque. This paper presents an adaptive JTF control algorithm that does not rely on this assumption. First, the robot dynamics with JTF is presented in a standard form, where the inertia matrix appears symmetric and positive definite. Subsequently, properties of the dynamics is inves tigated and a condition on the number of parallel joint axes for dynamic decoupling is derived. This can lead to further simplification of control structure for a class of robots. Secondly, an adaptive control law is developed incorporating uncalibrated joint torque signals, i.e., the gains and offsets of multiple sensors are unknown, into the control system. No dynamic model of a robot link is required, and all physical parameters of the joints including inertia of the rotors, link twist angles, and friction parameters are assumed unknown to the controller. Stability analysis together with a condition for bounded control input are presented. The control algorithm is experimentally applied to a robotic arm and experimental results illustrate high tracking performance, albeit neither was the torque sensor calibrated nor the parameters were known.

This paper presents a unified approach for inverse and direct dynamics of constrained multibody systems that can serve as a basis for analysis, simulation, and control. The main advantage of the dynamics formulation is that it does not require the constraint equations to be linearly independent. Thus, a simulation may proceed even in the presence of redundant constraints or singular configurations, and a controller does not need to change its structure whenever the mechanical system changes its topology or number of degrees of freedom. A motion-control scheme is proposed based on a projected inverse-dynamics scheme which proves to be stable and minimizes the weighted Euclidean norm of the actuation force. The projection-based control scheme is further developed for constrained systems, e.g., parallel manipulators, which have some joints with no actuators (passive joints). This is complemented by the development of constraint force control. A condition on the inertia matrix resulting in a decoupled mechanical system is analytically derived that simplifies the implementation of the force control. Finally, numerical and experimental results obtained from dynamic simulation and control of constrained mechanical systems, based on the proposed inverse and direct dynamics formulations, are documented.

This work describes the design of a new one-axis torque sensor. It achieves the conflicting requirements of high stiffness for all six force and torque components, high sensitivity for the one driving torque of interest, and yet very low sensitivity for the other five force/torque components. These properties, combined with its donut shape and small size, make this sensor an ideal choice for direct-drive robotic applications. Experimental data validate the basic design ideas underlying the sensor’s geometry, the finite element model used in its optimization, and the advertised performance.

This paper presents a new model for torque generation of permanent-magnet synchronous motors and their control based on Fourier coefficients. A new commutation strategy delivers ripple-free torque and simultaneously minimizes copper losses for the case when the motor's servo amplifier dynamics are negligible. However, multipole motors give rise to high frequency control signals, and often the dynamics of the current amplifier are no longer negligible. For this case, we present a new commutation strategy. Which minimizes the torque ripple and the velocity induced change. In the torque transfer function. The performance of both commutation laws is validated via simulations based on experimental data from a synchronous motor. Minimal computational requirements make these algorithms ideal for real time implementation.

Through its implication on the International Space Station (ISS), Canada is responsible for the verification of all robotic tasks involving the SPDM. To this end, the Canadian Space Agency is building the SPDM Task Verification Test-bed (STVF). Risks associated with the proposed concept have been identified, particularly in the area of control systems, dynamic behaviour and contact stability of the STVF Manipulator Test-bed (SMT). To mitigate these risks, a one degree-of-freedom prototype is implemented to validate the proposed control system architecture. The results are presented and discussed in light of the final SMT implementation.

This article describes design specifications of a new sensor that can accurately measure the torsion moment in a direct-drive robot, even in the presence of strong overhang, thrust forces, and bending moments. Introducing a torque sensor into a robot joint adds flexibility. Although torsional flexibility can be compensated for by sophisticated controllers, deflection in the other axes is more problematic. Consequently, another design criterion dictates high stiffness in non-torsional directions. The sensor design must optimize, and trade off among several conflicting design criteria. Also, many design iterations are required to arrive at a final design. Despite this complexity, it is possible to arrive at a novel basic sensor design. Thin-section rectangular bars experience high stress/ strain concentrations under torsion loads, which yield high sensitivity without sacrificing stiffness. This fact suggests that an appropriate structure should be primarily stressed by torsion. The team used the finite element analysis (FEA) capabilities of I-DEAS from Structural Dynamics Research Corp. to finalize the dimensions so that performance would be optimized. FEA was also used to select the location and proper size of the strain gauges.

The paper presents a new paradigm and conceptual design for reconfigurable robots. Unlike conventional reconfigurable robots, our design doesn't achieve reconfigurability by utilizing modular joints. But the robot is equipped with passive joints, i.e. joints with no actuator or sensor, which permit changing the Denavit-Hartenberg (DV) parameters such as the arm length, and the twist angle. The passive joints are controllable when the robot forms a closed kinematic chain. Also each passive joint is equipped with a built-in brake mechanism which is normally locked but it can be released whenever changing of the parameters is required. Kinematics analysis of such a robot plus control synthesis and mechanical design of the brake mechanism are described.

Adenosarcoma is a rare tumour which usually originates from endometrium. This paper presents a 69-year-old woman with adenosarcoma of uterus and a history of breast cancer and 10 years tamoxifen therapy.

This work presents the analysis, simulation, design, and assembly of a three-degree-of-freedom reconfigurable robotic arm. Unlike conventional reconfigurable robots, the final design illustrated in this paper does not achieve re-configurability through modular joints; instead, it is equipped with passive telescopic joints. These passive joints allow the robotic arm to change its Denavit-Hartenberg parameters via an innovative braking system. The robotic arm itself presents many advantages; not only is it versatile to perform various tasks, but it can be packed into a small volume, as usually required for launch in space applications.

Health care is an essential service that uses a great deal of sensitive personal data which has a high black market value being a lucrative target for data theft and ransomware attacks. It is clear that the necessary cybersecurity measures should be in place to ensure the protection of this medical and personal data. This is not a one-shot exercise; a broad range of data protection tools need to be integrated and combined to mitigate a large scala of cybersecurity attacks. The ProTego project has performed research on a set of advanced data protection techniques that can be used by hospital and care centers to protect the sensitive data in their systems. These techniques include data encryption, access control, end-device security and secure network communication. Within this whitepaper, the research contributions of the ProTego project in each of these domains will be discussed. Each of the proposed cybersecurity mitigation tool is aimed at preventing specific cybersecurity risks. Besides the strong security protection offered by this technology, another approach is the modular approach taken in the ProTego project. Since there are no strong dependencies between the individual components, depending on the specific needs of the end-user (e.g., hospital), one can opt to only use a subset of the available ProTego cybersecurity risk mitigation tools. Moreover, although the ProTego project specifically focused on a healthcare settings, the tools presented in this whitepaper can be applied in other settings that require data protection as well.

Preserving the confidentiality of sensitive Electronic Health Records (EHRs), stored on a medical server, is an essential issue in healthcare systems. The system should have the means to avoid unauthorized users from accessing this sensitive information. This security problem has been tackled in the ProTego project, where an access control mechanism is developed as an integral part of a toolkit for data protection in healthcare. Without the appropriate access control mechanisms, it is impossible to protect the EHRs. This white paper discusses multiple technical approaches to provide access control and key management for healthcare systems.