Group key agreement protocols with implicit key authentication

There have been numerous studies performed on secure group communication over unsecured channels such as the Internet and ad-hoc network. Most of the results are focused on cryptographic methods to share secret keys within the group. In the real world, however, we cannot establish an application for group communication without considering authentication of each peer (group member) since the adversary could digitally disguise itself and intrude into the key sharing process without valid membership. Therefore, authentication is an inevitable component for any secure communication protocols as well as peer group communication. In the classical design of group key protocols, each peer should be authenticated by a separate and centralized authentication server (e.g. Kerberos). Although many practical protocols present efficient ways for authentication, we are still facing the necessity of optimization between authentication and group key sharing. In that sense, implicit key authentication is an ideal property for group key protocols since, once it is possibly put into practice, we do not need any separate authentication procedure as a requisite. There was an attempt to devise implicit key authentication service in conjunction with group key agreement protocol; Authenticated Group Diffie-Hellman (A-GDH) and its stronger version (SA-GDH). Unfortunately, both were proved to have some weakness from the man-in-the-middle attacks. In this project, practical fixes for A-GDH and SA-GDH using Message Authentication Code (MAC) schemes are proposed and performance evaluation is carried out from implementation and experimentation for each: A-GDH, SA-GDH, A-GDH with MAC, and SA-GDH with MAC. Finally, the policies how and where to deploy authenticated GDH protocols are discussed under various group communication scenarios

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Department of Mehcanical EngineeringSurface qualities including topography, texture, mechanical, and chemical stabilities have become an essential requirement in manufacturing along with a new paradigm of industrial revolution. The electron beam irradiation is a special technique for surface modification. Especially, the energy transfer through electrons with rapid thermal gradient inducing phase transformation and re-solidification of materials is the unique characteristics of large pulsed electron beam (LPEB) irradiation, which makes it a potential candidate for surface manufacturing. Despite the previous studies have revealed that the LPEB irradiation could reduce surface roughness and modify surface properties, the application of LPEB in manufacturing processes is rather limited as the mechanisms of LPEB irradiation and corresponding surface modifications are yet to be explored. In order to expand the application area of the LPEB irradiation, the dissertation aims at (1) predictive modeling of the LPEB irradiation to firmly establish the irradiating mechanisms, (2) fundamental understandings on surface modification factors specifying the modification mechanisms, and (3) applying the LPEB irradiation for multiscale and hybrid manufacturing processes based on the modification mechanisms. The first part of the dissertation will be temperature prediction using a numerical model during the LPEB process. The absorptance of electron beam was estimated considering electron scattering, backscattering, and transmission to adopt the natural interactions of electrons with substrates. The model predicts temperature distributions and molten depths depending on the irradiation conditions. The effects of considerations of absorptance containing natural interactions such as scattering, backscattering, and transmission on prediction accuracy were explored by comparing the predictive results between constant and calculated absorptance versus depth. The estimation of absorptance and energy transfer mechanisms resulted in more accurate predictions of molten depths. The experimental investigations of LPEB irradiation were mainly performed on mold steels (KP1 and KP4) and biomedical alloys (Ti-6Al-7Nb) in the second part. The nano-hardness of mold steels increased by 316% (KP1), 144% (KP4), and 154% (Ti-6Al-7Nb), respectively under optimized experimental parameters, which is affected by the increased dislocations in the re-solidified layer and a decreased fraction of the pre-dominant slip plane. Contact angle variations and oxides formation in the re-solidified layer projected that the surface became stable. Corrosion resistance of the irradiated surface was increased, as evidenced from the improved corrosion parameters. Based on the mechanisms of surface hardening, the nitriding process of Ti-6Al-7Nb using the LPEB irradiation was also explored. The atomic concentration of nitrogen atoms at the re-solidified layer could be achieved up to ~18% by LPEB nitriding. Nano-hardness in the re-solidified layer was improved further by ~75% following the LPEB nitriding process, as a result of the formation of TiN. The nitrided layer induced by the LPEB nitriding, consisted of TiN, TiO2, and TiOxNy, which modified the corrosion resistance as evidenced from the improved electrochemical parameters. An increase in the fraction of TiN at the re-solidified layer was considered responsible for the remarkable improvement of surface properties embedding uniformly noble and stable characteristics at the top surface. Based on the fundamental mechanisms of LPEB irradiations specified in the first and second parts, multiscale and hybrid manufacturing processes using the LPEB will be discussed in the last part. The patterned metal masks fabricated by a laser and drilled CFRP composites were selected as a microscale application of the LPEB irradiation as a deburring process based on the melting mechanism. The generated burrs were tried to be eliminated by a LPEB-assisted hybrid deburring process on metal masks. The size of burrs after the process was decreased about 81% from 38.01 ??m to 7.2 ??m comparing to the results of abrasive deburring alone. The distribution of burr size also decreased about 85% and surface roughness (Ra) was modified from 640 nm to 121 nm, indicating the formation of a uniform surface texture. The optimized irradiation also improved the accuracy of the shapes of the holes, and reduced the sizes of the burrs by 97% on drilled CFRP composites. This modified the deviations of hole accuracy by 93%. The unique deburring mechanisms started with evaporation of the resin that coats the carbon fibers was revealed through experimental observations. Moreover, superhydrophobic transformation of patterned metal surfaces was also investigated as one of the microscale applications of LPEB based on the surface modification. The Wenzel-to-Cassie transition occurred at 140?? with a groove depth of 250 ??m after the WEDM fabrication which indicated the development of a hydrophobic surface. However, the contact angle increased to 166.7?? with the Cassie state after the LPEB irradiation at a lower depth of groove (200 ??m). The modification of surface roughness following the LPEB irradiation on the patterns resulted in a decreased the critical angle for Wenzel-to-Cassie transition. FT-IR spectroscopy acquired at the ATR mode specified the elimination of hydrophilic functional groups on the surface following LPEB irradiation. Finally, silver nanowires (AgNWs) were selected as a nanoscale application of LPEB irradiation based on the energy transfer mechanism. The welding of silver nanowires to form percolation networks using the LPEB irradiation was investigated. The welded AgNWs showed modified electrical and mechanical characteristics with a low contact resistance at junctions. Therefore, the LPEB-welded AgNW electrode exhibited modified sheet resistance of 12.63 ??/sq and higher transmittance of 93% (at 550 nm). Furthermore, the outstanding mechanical flexibility was obtained than other AgNW electrodes prepared by thermal annealing. The feasibility of LPEB-welded AgNW electrodes were proved by the fabrication of polymer light-emitting diodes (PLEDs). The result supported that the LPEB-welded AgNWs could become an alternative to indium tin oxide (ITO). The dissertation will explore a comprehensive approach on the LPEB irradiation encompassing materials selection, understanding of the underlying multi-physical phenomena, surface modification mechanisms, surface qualities, and applications of LPEB irradiation for multiscale and hybrid manufacturing processes. This unique research approach will overcome the limitations of conventional finishing processes, incorporate subdivided finishing processes into a single step, and bring a new paradigm of finishing systems. It should be anticipated that the outcome of the dissertation will expand the application areas of the LPEB irradiation in the overall manufacturing industries including automotive, aerospace, biomedical, and semi-conductors in multiscale from macro- to nano-levels.clos

Quality of Antenatal Care and its Relationship with Women’s Intended Use of their ANC Facility for Delivery: A National Cross-sectional Study in Kenya

Maternal deaths have been one of the leading causes of deaths in sub-Saharan Africa. Delivering at an institution can prevent the majority of maternal deaths in developing countries. A national cross-sectional survey of Kenya was used to determine if the quality of antenatal care (ANC) provided to women is associated with their intention to deliver at the same facility. Multilevel mixed-effects logistic regression was used to examine this relationship. Quality of ANC variables assessed in this study were not significantly associated with women’s intention to deliver at the same facility. Mothers preferred to deliver at hospitals, rather than clinics/dispensaries. ANC facility being the closest facility from their home was also positively associated with their intention to deliver at the same facility. Findings from this study suggest that there is a need to increase Kenyan women’s perspective towards lower-level facilities and their access to healthcare facilities for delivery

Large-scale Medical Image Processing

Department of Electrical EngineeringDeep learning based approaches for vision motivated many researchers in Medical Image processing ???elds due to the powerful performances. Compare to the natural image data, the medical image data set commonly consumes huge memory with complex data structures. In addition, to demonstrate the large scale images for clinical purpose such as CT scans or pathological image data, it is commonly known to be di???cult so that direct application of conventional deep models with typical GPU usage should be considered. For example, in the pathological data which is the image of microscope of human cells to classify tumor cells or not, the size of image slide is far larger than natural high resolution images while the ???eld of view (FOV) that we are interested region is tiny. On the other hand, to handle the large scale of CT data which is using X-ray beams to visualize in-vivo hardness structures, due to the memory limitation of GPU device, the patch-wise method is suppressed to yield high performance and is disturbed to compute faster. Thus, in this paper, we investigate the how data balancing method e???ectively enhance the deep approach method when there is only unbalanced dataset. Furthermore, we propose the e???cient memory utilization of multi-gpu method for deep learning with large scale CT images.clos

Efficient and effective human action recognition in video through motion boundary description with a compact set of trajectories

Human action recognition (HAR) is at the core of human-computer interaction and video scene understanding. However, achieving effective HAR in an unconstrained environment is still a challenging task. To that end, trajectory-based video representations are currently widely used. Despite the promising levels of effectiveness achieved by these approaches, problems regarding computational complexity and the presence of redundant trajectories still need to be addressed in a satisfactory way. In this paper, we propose a method for trajectory rejection, reducing the number of redundant trajectories without degrading the effectiveness of HAR. Furthermore, to realize efficient optical flow estimation prior to trajectory extraction, we integrate a method for dynamic frame skipping. Experiments with four publicly available human action datasets show that the proposed approach outperforms state-of-the-art HAR approaches in terms of effectiveness, while simultaneously mitigating the computational complexity