Benchmarking of lightweight cryptographic algorithms for wireless IoT networks

Wireless Networks - Cryptographic algorithms that can provide both encryption and authentication are increasingly required in modern security architectures and protocols (e.g. TLS v1.3). Many...     

A Privacy-Considerate Framework for Identity Management in Mobile Services

The subscribers’ personal information and services that mobile operators are able to provide to Web developers offer new and exciting possibilities in numerous domains. However, bringing mobile information services to the Web to enable a new generation of mobile Web services presents several research challenges on identity and privacy management. In this paper, we describe a framework for identity management in mobile services that empowers users to govern the use and release of their personal information. Our framework is based on a brokering approach that intermediates between the mobile operator’s information services and the Web service providers. By leveraging on Web services, identity management infrastructure and privacy enhancing technologies, our framework provides an effective, privacy-considerate delivery of services over the mobile Web environment. This paper describes the design principles and architecture of the framework as well as the feasibility, applicability and user-experience evaluation we have carried out.     

A bi-criteria minimum spanning tree routing model for MPLS/overlay networks

The MPLS platform enables the implementation of advanced multipath and multicast routing schemes. This work develops and analyses the performance of a new bi-criteria minimum spanning tree model intended for routing broadcast messages in MPLS networks or constructing tree-based overlay networks. The aim of the model is to obtain spanning trees which are compromise solutions with respect to two important traffic engineering metrics: load balancing cost and average delay bound. An exact solution to the formulated bi-criteria optimization problem is presented, which is based on an algorithm that enables the computation of the set of supported non-dominated spanning trees. An application model and a set of experiments on randomly generated Internet type topologies will also be presented. Finally a network performance analysis of the model considering three network performance metrics will be shown.     

Synergistic Computational‐Experimental Approach to Improve Ionene Polymer‐Based Functional Hydrogels

The manifold applications of ionene‐based materials such as hydrogels in daily life, biomedical sciences, and industrial processes are a consequence of their unique physical and chemical properties, which are governed by a judicious balance between multiple non‐covalent interactions. However, one of the most critical aspects identified for a broader use of different polyelectrolytes is the need of raising their gelation efficiency. This work focuses on surfactant‐free ionene polymers 1 ? 3 containing DABCO and N,N′‐(x‐phenylene)dibenzamide (x = ortho‐/meta‐/para‐) linkages as model systems to develop a combined computational‐experimental approach to improve the hydrogelation through a better understanding of the gelation mechanism. Molecular dynamics simulations of isomeric ionenes 1–3 with explicit water molecules point out remarkable differences in the assembly of the polymeric chains in each case. Interchain regions with high degree of hydration (i.e., polymer···water interactions) and zones dominated by polymer···polymer interactions are evident in the case of ortho‐ ( 1 ) and meta‐ ( 2 ) isomeric ionenes, whereas domains controlled by polymer···polymer interactions are practically inexistent in 3 . In excellent agreement, ortho‐ionene 1 provides experimentally the best hydrogels with unique features such as thixotropic behavior and dispersion ability for single‐walles carbon nanotubes.     

Superparamagnetic Twist‐Type Actuators with Shape‐Independent Magnetic Properties and Surface Functionalization for Advanced Biomedical Applications

Directed nanoparticle self‐organization and two‐photon polymerization are combined to enable three‐dimensional soft‐magnetic microactuators with complex shapes and shape‐independent magnetic properties. Based on the proposed approach, single and double twist‐type swimming microrobots with programmed magnetic anisotropy are demonstrated, and their swimming properties in DI‐water are characterized. The fabricated devices are actuated using weak rotating magnetic fields and are capable of performing wobble‐free corkscrew propulsion. Single twist‐type actuators possess an increase in surface area in excess of 150% over helical actuators with similar feature size without compromising the forward velocity of over one body length per second. A generic and facile combination of glycine grafting and subsequent protein immobilization exploits the actuator's increased surface area, providing for a swimming microrobotic platform with enhanced load capacity desirable for future biomedical applications. Successful surface modification is confirmed by FITC fluorescence.     

Nanometric Micelles with Photo‐Triggered Cytotoxicity

The development of a photo‐responsive micellar system capable of triggering cell death is reported. Precursors of the micelles are synthesized by connecting a lipophilic chain to a hydrophilic polyethylene glycol via a photo‐labile nitrobenzyl group. The resulting amphiphilic units are self‐assembled in water forming 12 nm micelles that are readily internalized into cells. Upon photo‐irradiation, micelles undergo cleavage and yield a cytotoxic nitrosobenzaldehyde derivative, which significantly inhibits the proliferation of MDA‐MB‐231 cells under standard in vitro conditions.     

Array response kernels for EEG and MEG in multilayer ellipsoidal geometry

We present forward modeling solutions in the form of array response kernels for electroencephalography (EEG) and magnetoencephalography (MEG), assuming that a multilayer ellipsoidal geometry approximates the anatomy of the head and a dipole current models the source. The use of an ellipsoidal geometry is useful in cases for which incorporating the anisotropy of the head is important but a better model cannot be defined. The structure of our forward solutions facilitates the analysis of the inverse problem by factoring the lead field into a product of the current dipole source and a kernel containing the information corresponding to the head geometry and location of the source and sensors. This factorization allows the inverse problem to be approached as an explicit function of just the location parameters, which reduces the complexity of the estimation solution search. Our forward solutions have the potential of facilitating the solution of the inverse problem, as they provide algebraic representations suitable for numerical implementation. The applicability of our models is illustrated with numerical examples on real EEG/MEG data of N20 responses. Our results show that the residual data after modeling the N20 response using a dipole for the source and an ellipsoidal geometry for the head is in average lower than the residual remaining when a spherical geometry is used for the same estimated dipole.     

Efficient Design of Pruned Convolutional Neural Networks on FPGA

Journal of Signal Processing Systems - Convolutional Neural Networks (CNNs) have improved several computer vision applications, like object detection and classification, when compared to other...