Thèses sur le sujet « 3D security »

Les modèles 3D sont des contenus précieux très utilisés dans l'industrie, et donc la cible potentielle de piratages. Le tatouage robuste pour les maillages 3D apporte une réponse au problème du traçage de traître. Dans l'état de l'art du domaine, la couche d'adaptation du contenu en particulier est testée face des attaques standards. Une approche robuste à la pose est alors étudiée. Elle utilise une estimation robuste de l'épaisseur, définie comme la distance un nuage de points construits à partir de mesures du diamètre. Les performances expérimentales montrent qu'elle forme un point de départ prometteur pour le tatouage robuste de maillages 3D posés. Pour les maillages statiques, la modulation des distances radiales est une approche efficace du tatouage. Elle a été formulée comme un problème d'optimisation quadratique sous contrainte, dont nous proposons plusieurs extensions : une transformée par étalement, des primitives de référence calculées de manière intégrale, des directions de déplacement arbitraires, et de nouvelles métriques pour minimiser la distorsion perçue par un utilisateur. Des expériences illustrent leurs bénéfices pour le compromis entre la robustesse et la fidélité du tatouage. La sécurité est analysée par l'intermédiaire de deux mécanismes de protection et par une série d'attaques et de contre-Mesures. Un système de resynchronisation est intégré afin d'améliorer la résistance au rognage. Des points de recalage sont insérés dans une configuration spécifique qui porte les informations habituellement éliminées par l'attaque. Au décodage, elles sont récupérées de manière aveugle. Un gain significatif des performances est mesuré expérimentalement
3D models are valuable assets widely used in the industry and likely to face piracy issues. This dissertation deals with robust mesh watermarking that is used for traitor-Tracing. Following a review of state-Of-The-Art 3D watermarking systems, the robustness of several content adaptation transforms are benchmarked. An embedding domain robust against pose is investigated, with a thickness estimation based on a robust distance function to a point cloud constructed from some mesh diameters. A benchmark showcases the performance of this domain that provides a basis for robust watermarking in 3D animations. For static meshes, modulating the radial distances is an efficient approach to watermarking. It has been formulated as a quadratic programming problem minimizing the geometric distortion while embedding the payload in the radial distances. This formulation is leveraged to create a robust watermarking framework, with the integration of the spread-Transform, integral reference primitives, arbitrarily selected relocation directions and alternate metrics to minimize the distortion perceived. Benchmarking results showcase the benefits of these add-Ons w.r.t the fidelity vs. robustness watermarking trade-Off. The watermark security is then investigated with two obfuscation mechanisms and a series of attacks that highlight the remaining limitations. A resynchronization approach is finally integrated to deal with cropping attacks. The resynchronization embeds land-Marks in a configuration that conveys synchronization information that will be lost after cropping. During the decoding, this information is blindly retrieved and significant robustness improvements are achieved

Increasing numbers of alerts produced by network intrusion detection systems (NIDS) have burdened the job of security analysts especially in identifying and responding to them. The tasks of exploring and analysing large quantities of communication network security data are also difficult. This thesis studied the application of visualisation in combination with alerts classifier to make the exploring and understanding of network security alerts data faster and easier. The prototype software, NSAViz, has been developed to visualise and to provide an intuitive presentation of the network security alerts data using interactive 3D visuals with an integration of a false alert classifier. The needs analysis of this prototype was based on the suggested needs of network security analyst's tasks as seen in the literatures. The prototype software incorporates various projections of the alert data in 3D displays. The overview was plotted in a 3D plot named as "time series 3D AlertGraph" which was an extension of the 2D histographs into 3D. The 3D AlertGraph was effectively summarised the alerts data and gave the overview of the network security status. Filtering, drill-down and playback of the alerts at variable speed were incorporated to strengthen the analysis. Real-time visual observation was also included. To identify true alerts from all alerts represents the main task of the network security analyst. This prototype software was integrated with a false alert classifier using a classification tree based on C4.5 classification algorithm to classify the alerts into true and false. Users can add new samples and edit the existing classifier training sample. The classifier performance was measured using k-fold cross-validation technique. The results showed the classifier was able to remove noise in the visualisation, thus making the pattern of the true alerts to emerge. It also highlighted the true alerts in the visualisation. Finally, a user evaluation was conducted to find the usability problems in the tool and to measure its effectiveness. The feed backs showed the tools had successfully helped the task of the security analyst and increased the security awareness in their supervised network. From this research, the task of exploring and analysing a large amount of network security data becomes easier and the true attacks can be identified using the prototype visualisation tools. Visualisation techniques and false alert classification are helpful in exploring and analysing network security data.

Monitoring volumes of malicious network data for across multiple sources can potentially be overwhelming. As a result, vital data is at a greater risk of being overlooked and the time span for analyzing it could be too lengthy. One way to address this issue is to employ network security visualization techniques to evaluate security risks and identify malicious activity to help mitigate compromised nodes on a network. The purpose of this thesis is to introduce a visualization framework to help reduce task-completion time, enhance situational awareness, and decrease user error of complex visualizations for network security applications. From the developed framework, three techniques are suggested as contributions using visualization and interaction: (1) Stereoscopic visualization technique aims to increase user awareness of vulnerabilities and malicious attacks, (2) the recommender system aims to ensure efficient navigation in complex 3D environments, and (3) an interaction system aims to assist in usability of visualization environments using Natural User Interfaces (NUIs). To investigate the aforementioned techniques, the following tools were created: 3D Stereoscopic Vulnerability Assessment Tool (3DSVAT), Parallel 3D Coordinate Visualization (P3D), NAVSEC recommender system, and Interaction System for Network Security (InterSec).

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA
Traditional approaches to constructing 3D structural electronics with conductive and dielectric materials include ink-jet printed, silver-bearing ink and fine copper wire meshes. One approach combines stereo-lithographic 3D-printed photo-polymers with direct-printed silver-bearing conductive inks. Results have shown 3D conductive structures with conductivities in the range 2x10⁶ to 1x10⁷ S/m using annealing temperatures ranging from 110°C to 150°C for 10 to 15 minutes. However, the stereo-lithographic approach suffers from the high cost of the printer and structural deformation during annealing. This paper presents a new method for 3d printing high conductivity metal alloys using consumer-grade 3D printer. The design and construction of the necessary modification will be presented in addition to the new 3D design process. The method yields metal structures with expected conductivities exceeding 2.6x10⁶ S/m. The process is performed without an annealing step, so the polymeric structural material is not exposed to high temperatures for any prolonged time. A UHF ISM band antenna is constructed for an RFID application using this method, the antenna performance is measured, and the results are compared simulations in Ansys HFSS. This new method can reduce total cost, and several low melting-point alloys could raise the conductivity.

A common method of connecting to the internet is a wireless network. These networks can be monitored to discover the area of their coverage, but commercial receivers don't always provide the most accurate results. A software-defined radio was programmed to sniff wireless signals and tested against a commercial receiver and the results were compared. The results suggest that the software-defined radio performs at least as well as the commercial receiver in distance measurements and significantly better in samples taken per minute. It was determined that the software-defined radio is a viable replacement for a commercial receiver in 3D heat mapping.

This work considers novel image-processing and computer-vision techniques to advance the automated analysis of low-resolution, complex 3D volumetric Computed Tomography (CT) imagery obtained in the aviation-security-screening domain. Novel research is conducted in three key areas: image quality improvement, segmentation and classification. A sinogram-completion Metal Artefact Reduction (MAR) technique is presented. The presence of multiple metal objects in the scanning Field of View (FoV) is accounted for via a distance-driven weighting scheme. The technique is shown to perform comparably to the state-of-the-art medical MAR techniques in a quantitative and qualitative comparative evaluation. A materials-based technique is proposed for the segmentation of unknown objects from low-resolution, cluttered volumetric baggage-CT data. Initial coarse segmentations, generated using dual-energy techniques, are refined by partitioning at automatically-detected regions. Partitioning is guided by a novel random-forestbased quality metric (trained to recognise high-quality, single-object segments). A second segmentation-quality measure is presented for quantifying the quality of full segmentations. In a comparative evaluation, the proposed method is shown to produce similar-quality segmentations to the state-of-the-art at reduced processing times. A codebook model constructed using an Extremely Randomised Clustering (ERC) forest for feature encoding, a dense-feature-sampling strategy and a Support Vector Machine (SVM) classifier is presented. The model is shown to offer improvements in accuracy over the state-of-the-art 3D visual-cortex model at reduced processing times, particularly in the presence of noise and artefacts. The overall contribution of this work is a novel, fully-automated and effcient framework for the classification of objects in cluttered 3D baggage-CT imagery. It extends the current state-of-the-art by improving classification performance in the presence of noise and artefacts; by automating the previously-manual isolation of objects and by decreasing processing times by several orders of magnitude.

Globally distributed additive manufacturing is a relatively new frontier in the field of product lifecycle management. Designers are independent of additive manufacturing services, often thousands of miles apart. Manufacturing data must be transmitted electronically from designer to manufacturer to realize the benefits of such a system. Unalterable blockchain legers can record transactions between customers, designers, and manufacturers allowing each to trust the other two without needing to be familiar with each other. Although trust can be established, malicious printers or customers still have the incentive to produce unauthorized or pirated parts. To prevent this, machine instructions are encrypted and electronically transmitted to the printing service, where an authorized printer decrypts the data and prints an approved number of parts or products. The encrypted data may include G-Code machine instructions which contain every motion of every motor on a 3D printer. Once these instructions are decrypted, motor drivers send control signals along wires to the printer's stepper motors. The transmission along these wires is no longer encrypted. If the signals along the wires are read, the motion of the motor can be analyzed, and G-Code can be reverse engineered. This thesis demonstrates such a threat through a simulated attack on a G-Code controlled device. A computer running a numeric controller and G-Code interpreter is connected to standard stepper motors. As G-Code commands are delivered, the magnetic field generated by the transmitted signals is read by a Hall Effect sensor. The rapid oscillation of the magnetic field corresponds to the stepper motor control signals which rhythmically move the motor. The oscillating signals are recorded by a high speed analog to digital converter attached to a second computer. The two systems are completely electronically isolated. The recorded signals are saved as a string of voltage data with a matching time stamp. The voltage data is processed through a Matlab script which analyzes the direction the motor spins and the number of steps the motor takes. With these two pieces of data, the G-Code instructions which produced the motion can be recreated. The demonstration shows the exposure of previously encrypted data, allowing for the unauthorized production of parts, revealing a security flaw in a distributed additive manufacturing environment.
Master of Science
Developed at the end of the 20th century, additive manufacturing, sometimes known as 3D printing, is a relatively new method for the production of physical products. Typically, these have been limited to plastics and a small number of metals. Recently, advances in additive manufacturing technology have allowed an increasing number of industrial and consumer products to be produced on demand. A worldwide industry of additive manufacturing has opened up where product designers and 3D printer operators can work together to deliver products to customers faster and more efficiently. Designers and printers may be on opposite sides of the world, but a customer can go to a local printer and order a part designed by an engineer thousands of miles away. The customer receives a part in as little time as it takes to physically produce the object. To achieve this, the printer needs manufacturing information such as object dimensions, material parameters, and machine settings from the designer. The designer risks unauthorized use and the loss of intellectual property if the manufacturing information is exposed. Legal protections on intellectual property only go so far, especially across borders. Technical solutions can help protect valuable IP. In such an industry, essential data may be digitally encrypted for secure transmission around the world. This information may only be read by authorized printers and printing services and is never saved or read by an outside person or computer. The control computers which read the data also control the physical operation of the printer. Most commonly, electric motors are used to move the machine to produce the physical object. These are most often stepper motors which are connected by wires to the controlling computers and move in a predictable rhythmic fashion. The signals transmitted through the wires generate a magnetic field, which can be detected and recorded. The pattern of the magnetic field matches the steps of the motors. Each step can be counted, and the path of the motors can be precisely traced. The path reveals the shape of the object and the encrypted manufacturing instructions used by the printer. This thesis demonstrates the tracking of motors and creation of encrypted machine code in a simulated 3D printing environment, revealing a potential security flaw in a distributed manufacturing system.

Esta investigación plantea un escenario de negocio de importación de ventas minorista, dónde la idea del negocio es distribuir de manera exclusiva una marca de mochilas con modelos innovadores líder en el mercado extranjero al mercado nacional, a fin de poder construir una identidad que sitúe la marca en el top of mind de nuestro mercado objetivo. Este trabajo está estructurado con los siguientes temas que representan cada uno un capítulo de esta investigación los cuales son: los aspectos generales del negocio con visión global, planeamiento estratégico analizando los factores internos y externos, investigación y validación del mercado objetivo, plan de marketing y publicidad de la marca, planeamiento de las operaciones de importación, estructura organizacional y recursos humanos, y el plan económico del financiamiento. El objetivo es comprobar la viabilidad de este negocio a través de un examen detallado de indicadores relevantes que nos permitan mostrar la rentabilidad del proyecto propuesto.
This research covers an import business of retail, which the aim idea is the exclusive distribution of the most important foreign brand of innovate backpacks to the national market and lastly make an identity to put us in the target market’s top of mind. This project contains these important topics which represent each chapter like: General aspects of global business, strategic plan about the thorough analysis of the internal and external factors, target market research and work out, advertising plan of brand, import operations plan, organizational structure and human resources, ultimately financial economic plan. The main focus is proving the feasibility of this business through a detailed examination of relevant indicators which show the proposed project profitability.
Trabajo de investigación

Avec l'augmentation des échanges de données et les évolutions technologiques et sociales récentes, les contenus multimédias prennent une place importante dans le trafic mondial. Aujourd'hui, les objets 3D sont utilisés dans un large nombre d'applications, par exemple, les applications médicales, les simulations, les jeux vidéo, l'animation et les effets spéciaux. La consommation d'objets 3D par le grand public est devenue un marché lucratif pouvant prendre la forme de plateformes de téléchargement d'objets 3D dans différents formats.Cette thèse, en collaboration avec la société STRATEGIES, concerne la protection des objets 3D, et plus particulièrement des maillages 3D contre des utilisations frauduleuses et illégales. Ces maillages 3D représentent de manière surfacique des modèles de chaussures et de maroquineries produits par les clients à l'aide des solutions numériques proposées par la société STRATEGIES. Dans un premier temps, nous proposons une nouvelle méthode d'insertion de données cachées bien plus efficace en termes de temps d'exécution sur des maillages de très grande taille que la méthode précédente développée en collaboration avec la société STRATÉGIES. Nous explorons également des approches de chiffrement sélectif pour le contrôle d'accès aux contenus de très haute qualité selon les besoins des utilisateurs. Dans ce contexte, nous proposons d'utiliser des approches de chiffrement sélectif sur les données géométriques des objets 3D afin de protéger le contenu visuel de ces derniers selon différents cas d'utilisation et différentes représentations de ces données.Dans un second axe de recherche, nous étudions l'application des processus de partage de secret au domaine des objets 3D. Le partage de secret est une approche cherchant à diviser un contenu secret entre plusieurs utilisateurs et autorisant certains sous-groupes d'utilisateurs à reconstruire le secret. Le partage de secret est un système de redondance permettant de reconstruire le secret même si certains utilisateurs ont perdu leurs informations. Le partage d'objet 3D secret est un domaine de recherche peu étudié permettant de protéger un objet 3D entre des collaborateurs. Nous proposons des nouvelles méthodes de partage d'objet 3D secret utilisant les approches de chiffrement sélectif et proposant des propriétés hiérarchiques où les utilisateurs possèdent des droits d'accès différents au contenu 3D en fonction de leur position dans une structure hiérarchique.Enfin, le troisième axe de recherche développé dans ces travaux de thèse porte sur l'analyse de la confidentialité visuelle des objets 3D sélectivement chiffrés plus ou moins fortement. En effet, en fonction du scénario, nos méthodes de chiffrement sélectif d'objets 3D fournissent des résultats pouvant être plus ou moins reconnaissables par les utilisateurs. Cependant, les métriques utilisées pour l'évaluation de la qualité des objets 3D ne permettent pas de distinguer deux objets 3D chiffrés sélectivement avec des niveaux de confidentialité différents. Pour cela, nous présentons la construction d’une base de données d'objets 3D chiffrés sélectivement afin de réaliser des évaluations subjectives de la confidentialité visuelle et tentons de construire une nouvelle métrique corrélée à des évaluations obtenues par le système visuel humain
With the increase of data exchange and latest technological and social developments, multimedia contents are becoming an important part of global trafic. Today, 3D objects are used in a large number of applications, for example, medical applications, simulations, video games, animation and special effects. 3D object usage by the general public has become a lucrative market that can take the form of 3D object downloading platforms with various 3D formats.This thesis, in collaboration with the company STRATEGIES, concerns the 3D object protection, and more particularly 3D meshes against fradulent and illegal uses. These 3D meshes represent surface models of shoes and leather goods produced by customers using digital solutions proposed by STRATEGIES. First, we propose a new method to insert secret data much more efficiently in terms of execution time on very large meshes than the previous method developed in collaboration with the company STRATEGIES. We are also exploring selective encryption approaches to control access to very high quality content according to user needs. In this context, we propose to use selective encryption approaches on the geometric data of 3D objects in order to protect the visual content of these objects according to different use cases and different data representations.In a second research axis, we study the application of secret sharing methods to the domain of 3D objects. Secret sharing is an approach that seeks to divide secret content between multiple users and allows certain subgroups of users to reconstruct the secret. Secret sharing is a redundancy system that allows you to reconstruct the secret even if some users have lost their information. Secret 3D object sharing is a poorly researched domain used to protect a 3D object between collaborators. We propose new secret 3D object sharing methods using selective encryption approaches and providing hierarchical properties where users have different access rights to 3D content based on their position in a hierarchical structure.Finally, the third research axis developed in this thesis deals with the analysis of the visual confidentiality of 3D objects selectively encrypted more or less strongly. Indeed, depending on the scenario, our 3D selective encryption methods provide results that can be more or less recognizable by users. However, the metrics used to evaluate the quality of 3D objects do not distinguish two selectively encrypted 3D objects with different levels of confidentiality. So, we present the construction of a databse of selectively encrypted 3D objects in order to realize subjective assessments of visual confidentiality and try to build a new metric correlated with evaluations obtained by the human visual system

Cette thèse aborde les problèmes liés à la protection de maillages d'objets 3D. Ces objets peuvent, par exemple, être créés à l'aide d'outil de CAD développés par la société STRATEGIES. Dans un cadre industriel, les créateurs de maillages 3D ont besoin de disposer d'outils leur permettant de vérifier l'intégrité des maillages, ou de vérifier des autorisations pour l'impression 3D par exemple. Dans ce contexte nous étudions l'insertion de données cachées dans des maillages 3D. Cette approche permet d'insérer de façon imperceptible et sécurisée de l'information dans un maillage. Il peut s'agir d'un identifiant, de méta-informations ou d'un contenu tiers, par exemple, pour transmettre de façon secrète une texture. L'insertion de données cachées permet de répondre à ces problèmes en jouant sur le compromis entre la capacité, l'imperceptibilité et la robustesse. Généralement, les méthodes d'insertion de données cachées se composent de deux phases, la synchronisation et l'insertion. La synchronisation consiste à trouver et ordonner les éléments disponibles pour l'insertion. L'un des principaux challenges est de proposer une méthode de synchronisation 3D efficace qui définit un ordre sur les composants des maillages. Dans nos travaux, nous proposons d'utiliser les sommets du maillage, plus précisément leur représentation géométrique dans l'espace comme composants de base pour la synchronisation et l'insertion. Nous présentons donc trois nouvelles méthodes de synchronisation de la géométrie des maillages basées sur la construction d'un chemin hamiltonien dans un nuage de sommets. Deux de ces méthodes permettent de manière conjointe de synchroniser les sommets et de cacher un message. Cela est possible grâce à deux nouvelles méthodes d'insertion haute capacité (de $3$ à $24$ bits par sommet) qui s'appuient sur la quantification des coordonnées. Dans ces travaux nous mettons également en évidence les contraintes propres à ce type de synchronisation. Nous discutons des différentes approches proposées dans plusieurs études expérimentales. Nos travaux sont évalués sur différents critères dont la capacité et l'imperceptibilité de la méthode d'insertion. Nous portons également notre attention aux aspects sécurité des méthodes
This thesis addresses issues relating to the protection of 3D object meshes. For instance, these objects can be created using CAD tool developed by the company STRATEGIES. In an industrial context, 3D meshes creators need to have tools in order to verify meshes integrity, or check permission for 3D printing for example.In this context we study data hiding on 3D meshes. This approach allows us to insert information in a secure and imperceptible way in a mesh. This may be an identifier, a meta-information or a third-party content, for instance, in order to transmit secretly a texture. Data hiding can address these problems by adjusting the trade-off between capacity, imperceptibility and robustness. Generally, data hiding methods consist of two stages, the synchronization and the embedding. The synchronization stage consists of finding and ordering available components for insertion. One of the main challenges is to propose an effective synchronization method that defines an order on mesh components. In our work, we propose to use mesh vertices, specifically their geometric representation in space, as basic components for synchronization and embedding. We present three new synchronisation methods based on the construction of a Hamiltonian path in a vertex cloud. Two of these methods jointly perform the synchronization stage and the embedding stage. This is possible thanks to two new high-capacity embedding methods (from 3 to 24 bits per vertex) that rely on coordinates quantization. In this work we also highlight the constraints of this kind of synchronization. We analyze the different approaches proposed with several experimental studies. Our work is assessed on various criteria including the capacity and imperceptibility of the embedding method. We also pay attention to security aspects of the proposed methods

Facial Ageing (FA) is a very fundamental issue, as ageing in general, is part of our daily life process. FA is used in security, finding missing children and other applications. It is also a form of Facial Recognition (FR) that helps identifying suspects. FA affects several parts of the human face under the influence of different biological and environmental factors. One of the major facial feature changes that occur as a result of ageing is the appearance and development of wrinkles. Facial wrinkles are skin folds; their shapes and numbers differ from one person to another, therefore, an advantage can be taken over these characteristics if a system is implemented to extract the facial wrinkles in a form of maps. This thesis is presenting a new technique for three-dimensional facial wrinkle pattern information that can also be utilised for biometric applications, which will back up the system for further increase of security. The procedural approaches adopted for investigating this new technique are the extraction of two-dimensional wrinkle maps of frontal human faces for digital images and the design of three-dimensional wrinkle pattern formation system that utilises the generated wrinkle maps. The first approach is carried out using image processing tools so that for any given individual, two wrinkle maps are produced; the first map is in a binary form that shows the positions of the wrinkles on the face while the other map is a coloured version that indicates the different intensities of the wrinkles. The second approach of the 3D system development involves the alignment of the binary wrinkle maps on the corresponding 3D face models, followed by the projection of 3D curves in order to acquire 3D representations of the wrinkles. With the aid of the coloured wrinkle maps as well as some ageing parameters, simulations and predictions for the 3D wrinkles are performed.

Au cours des dernières décennies, les objets 3D sont devenus un élément essentiel de la vie quotidienne, tant dans le contexte privé que professionnel. Ces objets 3D sont souvent stockés sur le cloud et transférés sur des réseaux plusieurs fois au cours de leur existence, où ils sont susceptibles de faire l'objet d'attaques malveillantes. Par conséquent, des méthodes de sécurisation des objets 3D, comme le chiffrement ou l'insertion des données cachées, sont essentielles. Le chiffrement est utilisé pour protéger la confidentialité visuelle du contenu d’un objet 3D. Il est également possible d'utiliser des schémas de chiffrement sélectif, dans lesquels seulement une partie de l’objet 3D est chiffrée. L'insertion des données cachées est généralement utilisée pour protéger les droits d'auteur ou l'authenticité des objets 3D. Toutefois, lorsqu'un objet 3D est chiffré, un tiers, tel qu'un serveur, peut avoir besoin d'intégrer des données dans l'objet 3D confidentiel. Dans ce cas, les données sont cachées dans le domaine chiffré. Les objets 3D sont souvent constitués de millions de sommets, de sorte que le stockage et le partage en ligne sont coûteux. Par conséquent, la compression des objets 3D est essentielle. Dans ce travail, nous présentons trois contributions dans différents domaines de recherche.Premièrement, nous présentons notre travail sur une nouvelle méthode permettant d'obtenir un objet 3D marqué à partir d'une insertion de données cachées de haute capacité dans le domaine chiffré. Basée sur des propriétés homomorphiques du cryptosystème de Paillier, notre méthode permet d'insérer plusieurs messages secrets dans le domaine chiffré avec une haute capacité. Ces messages peuvent être extraits dans le domaine en clair après le déchiffrement de l'objet 3D. À notre connaissance, nous sommes les premiers à proposer une méthode d'insertion de données cachées dans le domaine chiffré où les données cachées de haute capacité sont conservées dans le domaine en clair après le déchiffrement de l'objet 3D. Le chiffrement et l'insertion de données cachées dans le domaine chiffré sont conformes au format et sans expansion de taille, malgré l'utilisation du cryptosystème de Paillier.Nous présentons ensuite notre travail sur une mesure d'évaluation du niveau de sécurité visuelle des objets 3D chiffrés sélectivement. Basé sur une nouvelle base de données composée d'objets 3D chiffrés sélectivement et évalués, nous proposons un modèle pour déterminer les paramètres de sécurité en fonction du niveau de sécurité souhaité. Enfin, nous détaillons notre score 3DVS qui sert à mesurer le niveau de sécurité visuelle des objets 3D chiffrés sélectivement.Nous présentons également, à notre connaissance, la première méthode permettant de déchiffrer hiérarchiquement un objet 3D chiffré en fonction d'un trousseau de clés généré. Ce trousseau se compose d'un ensemble de clés qui permettent un déchiffrement plus ou moins fort de l'objet 3D chiffré. Chaque objet 3D déchiffré hiérarchiquement a un niveau de sécurité visuelle différent, où l'objet 3D est plus ou moins accessible visuellement. Notre méthode est essentielle lorsqu'il s'agit d'empêcher des fuites des secrets commerciales au sein d'une entreprise ou par des attaquants extérieurs. Elle est également écologique et plus sécurisée que les méthodes traditionnelles de chiffrement sélectif.Enfin, nous présentons notre travail sur des méthodes conjointes de sécurité et de compression basées sur la méthode de compression d'objets 3D de Google, Draco, dans laquelle nous intégrons une étape de sécurité dans Draco, qui est en train de devenir la nouvelle norme de l'industrie. Ces étapes de sécurité sont le chiffrement, le chiffrement sélectif et le tatouage
Over the last few decades, 3D objects have become an essential part of everyday life, in both private and professional contexts. These 3D objects are often stored on the cloud and transferred over networks many times during their existence, where they are susceptible to malicious attacks. Therefore, 3D object security, such as encryption or data hiding, is essential. Encryption is used to protect the visual confidentiality of the 3D object's content. Selective encryption schemes can also be used, where part of a component, such as a part of each vertex, is encrypted. Data hiding is generally used to protect the copyright or the authenticity of the 3D object. However, when a 3D object is encrypted, a third party such as a server may need to embed data in the confidential 3D object. In this case, data hiding in the encrypted domain is performed. In many applications, 3D objects often consist of millions of vertices, and so storing and sharing them online is expensive, time consuming and not environmentally friendly. Consequently, 3D object compression is essential. In this work, we present three contributions in different research areas. First, we present our work on a new method to obtain a watermarked 3D object from high-capacity data hiding in the encrypted domain. Based on the homomorphic properties of the Paillier cryptosystem, our proposed method allows us to embed several secret messages in the encrypted domain with a high-capacity. These messages can be extracted in the plaintext domain after the 3D object decryption. To the best of our knowledge, we are the first to propose a data hiding method in the encrypted domain where the high-capacity watermark is conserved in the plaintext domain after the 3D object is decrypted. The encryption and the data hiding in the encrypted domain are format compliant and without size expansion, despite the use of the Paillier cryptosystem. Then, we present our work on an evaluation metric for the visual security level of selectively encrypted 3D objects. We present a new dataset composed of evaluated selectively encrypted 3D objects. We propose a model to determine the security parameters according to a desired security level. Finally, we detail our proposed 3DVS score which serves to measure the visual security level of selectively encrypted 3D objects. We also present a method which allows us to hierarchically decrypt an encrypted 3D object according to a generated ring of keys. This ring consists of a set of keys that allow a stronger or weaker decryption of the encrypted 3D object. Each hierarchically decrypted 3D object has a different visual security level, where the 3D object is more or less visually accessible. Our method is essential when it comes to preventing trade secrets from being leaked from within a company or by exterior attackers. It is also ecologically friendly and more secure than traditional selective encryption methods. Finally, we present our work on joint security and compression methods based on Google's 3D object compression method Draco, where we integrate a security step in Draco, which is becoming the new industry standard. These security steps are encryption, selective encryption and watermarking

Technical advancements in 3D projection has recently made presentation of holographic images possible by using self-contained devices. Instead of using a screen to present objects, glasses like Microsoft HoloLens can render objects that appear as holograms around the user. SAAB Defence and Security are evaluating if this new technology can complement their command and control system 9LV Combat Management System. This degree project is a study of the technical possibilities and limitations of introducing holographic display of sonar tracks used for detecting submarines or sea mines. The project was started with a background study into what methods are available to render 3D underwater terrain. A basic hologram representing a map of littoral terrain was constructed and simulated sonar tracks from the command and control system was mapped into the terrain. Implementation of the application was done using the Unity 3D game engine that has built in support for the HoloLens. Performance evaluation was done using Unity3D profiler that is an extensive application evaluation tool that maintain overhead to a minimum. An evaluation of HoloLens usage onboard two different boats was done to conclude if the equipment can be used in the normal 9LV CMS operating environment. Results show that it is possible to successfully use holographic display for sonar tracks, but due to limited processing power of the HoloLens terrain detail will be reduced. Holograms are orientated by combining camera spatial mapping and an inertial measurement unit. Usage tests onboard a vessel indicates that holograms will unexpectedly move and the HoloLens will loose spatial mapping due to acceleration forces caused by seastate.
Tekniska framsteg inom presentation av 3D-objekt har nyligen möjliggjort användning av hologram presenterade med portabel utrustning. Istället för att använda en vanlig skärm kan glasögon, som Microsoft HoloLens, rendera objekt som användaren upplever i sin omgivning som hologram. SAAB Defence and Security utvärderar om den nya teknologin kan användas som ett komplement till deras ledningssystem 9LV Combat Management System. Det här examensarbetet är en studie av de tekniska möjligheter och begränsningar som finns för att bygga en applikation som visar sonar-information som ett hologram, främst att användas för ubåtsjakt och upptäckt av sjöminor. Projektet inleddes med en bakgrundsstudie om vilka metoder som finns tillgängliga för att rendera en 3D-karta av en havsbotten. En enkel applikation med en karta som föreställer en del av skärgården tas fram med simulerad sonar-information från ledningssystemet inlagt i kartan. Implementationen av applikationen gjordes med spelmotorn Unity3D som har inbyggt stöd för Microsoft HoloLens. Prestandautvärdering genomfördes genom att använda ett inbyggt profileringsverktyg i Unity3D som har liten påverkan på prestandan. Utvärdering av möjlig användningsmiljö gjordes genom att testa utrustningen ombord på två olika båtar för att avgöra om HoloLens kan användas i 9LV CMS normala operativa förhållanden. Resultaten visar att det är möjligt att använda holografisk visning för sonar-data men upplösningen av terrängen för kartan är något låg på grund av den begränsade beräkningskraften i Microsoft HoloLens. Hologram i Microsoft HoloLens orienteras genom att kombinera en djupseende kamera med en intern referensenhet. Användningstester ombord på båt visar på att vid accelerationer som uppkommer av sjöhävning tappar HoloLensen rumsuppfattningen tillfälligt och stoppar renderingen av hologrammet.

This thesis proposes a new method for detecting malicious cyber-physical attacks on additive manufacturing (AM) systems. The method makes use of a physical hash, which links digital data to the manufactured part via a disconnected side-channel measurement system. The disconnection ensures that if the network and/or AM system become compromised, the manufacturer can still rely on the measurement system for attack detection. The physical hash takes the form of a QR code that contains a hash string of the nominal process parameters and toolpath. It is manufactured alongside the original geometry for the measurement system to scan and compare to the readings from its sensor suite. By taking measurements in situ, the measurement system can detect in real-time if the part being manufactured matches the designer's specification. A proof-of-concept validation was realized on a material extrusion machine. The implementation was successful and demonstrated the ability of this method to detect the existence (and absence) of malicious attacks on both process parameters and the toolpath. A case study for detecting changes to the toolpath is also presented, which uses a simple measurement of how long each layer takes to build. Given benchmark readings from a 30x30 mm square layer created on a material extrusion system, several modifications were able to be detected. The machine's repeatability and measurement technique's accuracy resulted in the detection of a 1 mm internal void, a 2 mm scaling attack, and a 1 mm skewing attack. Additionally, for a short to moderate length build of an impeller model, it was possible to detect a 0.25 mm change in the fin base thickness. A second case study is also presented wherein dogbone tensile test coupons were manufactured on a material extrusion system at different extrusion temperatures. This process parameter is an example of a setting that can be maliciously modified and have an effect on the final part strength without the operator's knowledge. The performance characteristics (Young's modulus and maximum stress) were determined to be statistically different at different extrusion temperatures (235 and 270 °C).
Master of Science

Les éléments optiques diffractifs (EOD) sont maintenant largement utilisés dans les applications universitaires et industrielles grâce à leurs caractéristiques ultra-minces et compactes et à leur très flexible manipulation des fronts d'ondes lumineuses. Malgré ces excellentes propriétés, la portée d'application des EOD est souvent limitée par le fait que la plupart des DOE sont conçus pour générer uniquement des motifs projetés en 2D, et plus important encore, pour être utilisés uniquement avec des sources laser monochromatiques, cohérentes, souvent collimatées. Les contraintes de coût et de sécurité oculaire des sources laser limitent fortement les applications de visualisation des EOD telles que les hologrammes de sécurité, et la nature 2D des motifs générés limite les applications de réalité virtuelle ou augmentée. Pour surmonter ces restrictions, cette thèse vise la conception et la fabrication de structures diffractives 3D sélectives en longueur d'onde qui peuvent produire un objet 3D "flottant" perçu à plusieurs angles de vue derrière le substrat EOD lorsqu'il est éclairé par des sources LED blanches facilement disponibles et bon marché. Dans une première approche, nous développons et validons expérimentalement une série de nouveaux algorithmes de conception pour des structures EOD conventionnelles, optiquement "minces" sous un éclairage incohérent et divergent ; d'abord pour projeter des motifs 2D, puis pour créer des images 2D virtuelles et enfin des motifs 3D virtuels. Dans un deuxième temps, nous exploitons les capacités des structures optiquement "épaisses" de type Bragg pour introduire une sélectivité spectrale (vers des modèles de sortie de couleur) et améliorer l'efficacité de la diffraction. Comme l'approximation des éléments minces n'est pas valable pour la conception de structures photoniques 3D optiquement épaisses, nous développons un algorithme d'optimisation des essaims de particules basé sur un modèle de diffraction rigoureux pour concevoir des structures diffractives synthétiques optiquement épaisses très innovantes. La fabrication rentable de ces structures micro et nano-photoniques entièrement 3D proposées est très difficile lorsqu'on utilise les techniques lithographiques traditionnelles actuelles qui sont généralement limitées, en pratique, à la fabrication de structures 2D ou 2,5D. À cette fin, le département d'optique de l'IMT Atlantique met actuellement au point un prototype avancé de photoplotter de polymérisation à deux photons massivement parallélisés (2PP) pour la fabrication de structures photoniques entièrement tridimensionnelles de grande surface. Nous présentons nos contributions à la conception et au développement des modules d'illumination critiques et de haute uniformité pour le nouveau prototype de photoplotteur 2PP. La recherche et le développement de cette thèse contribuent à l'élargissement des applications de l'EOD à des domaines actuellement inaccessibles. Les méthodes de conception développées peuvent également trouver des applications dans des domaines d'affichage holographique tels que la réalité augmentée automobile
Diffractive Optical Elements (DOEs) are now widely used in academic and industrial applications due to their ultrathin, compact characteristics and their highly flexible manipulation of light wave-fronts. Despite these excellent properties, the scope of DOE applications is often limited by the fact that most DOEs are designed to generate only 2D projected patterns, and even more importantly, for use only with monochromatic, coherent, often collimated, laser sources. The cost and eye safety constraints of laser sources severely restrict DOE visualisation applications such as security holograms, and the 2D nature of the generated patterns limits virtual or augmented reality applications. To overcome these restrictions, this thesis targets the design and fabrication of wavelength selective 3D diffractive structures which can produce a perceived multiple view-angle “floating” 3D object behind the DOE substrate when illuminated by readily available and cheap white LED sources. In an initial approach we develop and experimentally validate a series of novel design algorithms for conventional optically “thin” DOE structures under incoherent, divergent illumination; first to project 2D patterns, then to create virtual 2D images and finally virtual 3D patterns. In a second stage, we leverage the capacities of optically “thick”, Bragg-like structures to introduce spectral selectivity (towards colour output patterns) and improve diffraction. Since the thin element approximation is invalid when designing optically thick 3D photonic structures we develop a particle swarm optimization algorithm based on a rigorous diffraction model to design highly innovative optically thick synthetic diffractive structures. The cost-effective fabrication of such proposed fully 3Dmicro- and nano-photonics structures is highly challenging when using current traditional lithographic techniques which are generally limited, in practice, to the fabrication of 2D or 2.5D structures. To this end, an advanced prototype massively parallelized two-photon polymerization (2PP) photoplotter for the fabrication of large area fully 3D photonic structures is currently being developed by the IMT Atlantique Optics Department. We present our contributions to the design and development of the critical, high uniformity illumination modules for the new prototype 2PP photoplotter. The research and development in this thesis contributes to the broadening of DOE applications to fields which are currently inaccessible. The developed design methods can also find applications in holographic display fields such as automotive augmented reality

Biometrics is a critical component of cybersecurity that identifies persons by verifying their behavioral and physical traits. It is the most precise and powerful physical security solution for identity verification presently in use. In biometric-based authentication, each individual can be correctly recognized based on their intrinsic behavioral or physical features. The human ear is an important biometric with highly discriminating features such that even identical twins have different ear shapes. Owing to the easy acquisition, invariance to expression, and stable structure over a long period of time, ear image analysis has the edge over other biometric traits such as faces, fingerprints, palmprints, and iris. These advantages allow the use of ear images for numerous applications, including biometric identification, asymmetry analysis for clinical purposes, genetic relationship study, and gender recognition. In ear-based biometrics, one of the significant steps is to localize ears in profile face images. Most ear detection approaches use 2D images for ear region localization as they require fewer computations. Due to the importance of being able to handle unconstrained images for object detection and segmentation. However, 2D image-based approaches are limited to constrained scenarios due to their sensitivity to lighting conditions and pose variations. Therefore, 3D images can be used to overcome the limitations of 2D images. Recent developments in 3D imaging techniques open the door for 3D image-based applications, including biometrics, robotics, medical diagnosis, and autonomous driving. Generally, 3D data can be represented in various forms, such as point clouds, volumetric grids, depth images, and meshes. Point cloud representation is becoming more popular as it reserves the original geometric information in 3D domains without discretization. However, conventional convolutional neural networks cannot be applied directly to point clouds due to the irregular order of the points. Therefore, most work using 3D images generally converts point cloud data to Euclidean structured format before sending it to the CNN architectures. This representation conversion introduces unnecessarily voluminous data and wraps natural invariances of the data due to the generation of quantization artefacts. This work presents a complete pipeline for ear biometrics that can detect ears directly from 3D point clouds of profile face images and recognize a person with the novel matching algorithm You Morph Once (YMO). This technology can be used in the field of cyber security as a form of biometric authentication, which is a way to identify and verify the identity of a person using unique physical characteristics such as ear shape. The use of ear biometrics as a form of identification can provide an additional level of security, as ears are unique to each individual and difficult to replicate or falsify. Additionally, using 3D point clouds and the 3D Morphable Ear Model (3DMEM) model allows for greater accuracy and robustness in identification, making it harder for hackers to bypass the system. The proposed pipeline can be integrated into various security systems, such as access controls, online authentication, and personal identification. These systems could be used for highly secure areas such as government buildings, military bases, and banks, where the traditional form of authentication like password and PIN is not enough to protect sensitive information.

This dissertation deals with the platform Z-Wave. This platform tries to create an universal system for smart home. The theoretical part of the work describes in details the platform itself as well as the applicable libraries for programming of applications and the available equipments. The practical part presents the new custom gateway. The hardware of this gateway is designed with utilization of the Z-Wave module, Raspberry Pi 3 microcomputer, touchscreen, powerbank and the body of the system. The body has been designed in the Solid Works CAD system and printed on a 3D printer. The needed firmware was loaded into the Z-Wave module ZM5304 and this module has been interconnected with the Raspberry Pi 3 through the printed circuit board of the custom design. The gateway drives OpenZWave network through the new own application written with help of Python wrapper of the library OpenZWave and other open source components. The part of the work is also the list and description of the alternative commercial gateways available on the Czech market.

This research created a new theoretical Soft Computing (SC) hybridized network intrusion detection diagnostic system including complex hybridization of a 3D full color Self-Organizing Map (SOM), Artificial Immune System Danger Theory (AISDT), and a Fuzzy Inference System (FIS). This SOM+ diagnostic archetype includes newly defined intrusion types to facilitate diagnostic analysis, a descriptive computational model, and an Invisible Mobile Network Bridge (IMNB) to collect data, while maintaining compatibility with traditional packet analysis. This system is modular, multitaskable, scalable, intuitive, adaptable to quickly changing scenarios, and uses relatively few resources.

Government agencies and corporations are growing increasingly reliant on networks for day-to-day operations including communication, data processing, and data storage. As a result, these networks are in a constant state of growth. These burgeoning networks cause the number of network security events requiring investigation to grow exceptionally, creating new problems for network security analysts. The increasing number of attacks propagated against high-value networks only increases the gravity. Therefore, security analysts need assistance to be able to continue to monitor network events at an acceptable rate. Network analysts rely on many different systems and tools to properly secure a network. One line of defense is an intrusion detection system or IDS. Intrusion detection systems monitor networks for suspicious activity and then print alerts to a log file. An important part of effective intrusion detection is finding relationships between network events, which allows for detection of network anomalies. However, network analysts typically monitor these logs in a sparsely formatted view, which simply isn’t effective for large networks. Therefore, a Visual Intrusion Detection System or VIDS is an interesting solution to aid network security analysts in properly securing the networks. The visualization tool takes a log file and represents the alerts on a three-dimensional graph. Previous research shows that humans have an innate ability to match patterns based on visual cues, which we hope will allow network analysts to match patterns between alerts and identify anomalies. In addition, the tool will leverage the user’s intuition and experience to aid intrusion detection by allowing them to manipulate the view of the data. The objective of this thesis is to quantify and measure the effectiveness of this Visual Intrusion Detection System built as an extension to the SNORT open source IDS. The purpose of the visualization is to give network security analysts an alternative view from what traditional network security software provides. This thesis will also explore other features that can be built into a Visual Intrusion Detection System to improve its functionality.
Department of Computer Science

With the increase in globalization of Integrated Circuit (IC) design and production, hardware trojans have become a serious threat to manufacturers as well as consumers. These trojans could be intensionally or accidentally embedded in ICs to make a system vulnerable to hardware attacks. The implementation of critical applications using ICs makes the effect of trojans an even more serious problem. Moreover, the presence of untrusted foundries and designs cannot be eliminated since the need for ICs is growing exponentially and the use of third party software tools to design the circuits is now common. In addition if a trusted foundry for fabrication has to be developed, it involves a huge investment. Therefore, hardware trojan detection techniques are essential. Very Large Scale Integration (VLSI) system designers must now consider the security of a system against internal and external hardware attacks. Many hardware attacks rely on system vulnerabilities. Moreover, an attacker may rely on deprocessing and reverse engineering to study the internal structure of a system to reveal the system functionality in order to steal secret keys or copy the system. Thus hardware security is a major challenge for the hardware industry. Many hardware attack mitigation techniques have been proposed to help system designers build secure systems that can resist hardware attacks during the design stage, while others protect the system against attacks during operation. In this dissertation, the idea of quantifying hardware attacks, hardware trojans, and hardware trojan detection techniques is introduced. We analyze and classify hardware attacks into risk levels based on three dimensions Accessibility/Resources/Time (ART). We propose a methodology and algorithms to aid the attacker/defender to select/predict the hardware attacks that could use/threaten the system based on the attacker/defender capabilities. Because many of these attacks depends on hardware trojans embedded in the system, we propose a comprehensive hardware trojan classification based on hardware trojan attributes divided into eight categories. An adjacency matrix is generated based on the internal relationship between the attributes within a category and external relationship between attributes in different categories. We propose a methodology to generate a trojan life-cycle based on attributes determined by an attacker/defender to build/investigate a trojan. Trojan identification and severity are studied to provide a systematic way to compare trojans. Trojan detection identification and coverage is also studied to provide a systematic way to compare detection techniques and measure their e effectiveness related to trojan severity. We classify hardware attack mitigation techniques based on the hardware attack risk levels. Finally, we match these techniques to the attacks the could countermeasure to help defenders select appropriate techniques to protect their systems against potential hardware attacks.
Graduate
0544
0984
samerm@uvic.ca

碩士
國立交通大學
多媒體工程研究所
96
A vision-based vehicle system for security patrolling in indoor environments using an autonomous vehicle is proposed. A small vehicle with wireless control and a web camera which has the capabilities of panning, tilting, and zooming is used as a test bed. At first, an easy-to-use learning technique is proposed, which has the capability of extracting specific features, including navigation path, floor color, monitored object, and vehicle location with respect to monitored objects. Next, a security patrolling method by vehicle navigation with obstacle avoidance and security monitoring capabilities is proposed. The vehicle navigates according to the node data of the path map which is created in the learning phase and monitors concerned objects by a simplified scale-invariant feature transform (simplified-SIFT) algorithm proposed in this study. Accordingly, we can extract the features of each monitored object from acquired images and match them with the corresponding learned data by the Hough transform. Furthermore, a vehicle location estimation technique for path correction utilizing the monitored object matching result is proposed. In addition, techniques for obstacle avoidance are also proposed, which can be used to find the clusters of floor colors, detect obstacles in environments with various floor colors, and integrate a technique of goal-directed minimum path following to guide the vehicle to avoid obstacles. Good experimental results show the flexibility and feasibility of the proposed methods for the application of security patrolling in indoor environments.