1Semiconductor supply chain is increasingly getting exposed to variety of security attacks such as Trojan insertion, cloning, counterfeiting, reverse engineering (RE), piracy of Intellectual Property (IP) or Integrated Circuit (IC) and side-channel analysis due to involvement of untrusted parties. In this thesis, we use threshold voltage-defined switches to design a logic gate that will camouflage the conventional logic gates both logically and physically to resist RE and IP piracy. The proposed gate can function as NAND, AND, NOR, OR, XOR, and XNOR robustly using threshold defined switches. We also propose a flavor of camouflaged gate that represents reduced functionality (NAND, NOR and NOT) at much lower overhead. The camouflaged design operates at nominal voltage and obeys conventional reliability limits. A small fraction of gates can be camouflaged to increase the RE effort extremely high. Simulation results indicate 46-53% area, 59-68% delay and 52-76% power overhead when 5-15% gates are identified and camouflaged using the proposed gate. A significant higher RE effort is achieved when the proposed gate is employed in the netlist using controllability, observability and hamming distance sensitivity based gate selection metrics. 1 Information included in this chapter is reprinted from [19] with permission. Copyright permission included in Appendix B.

Submitted by Secretaria Pós de Produção (tpp@vm.uff.br) on 2017-07-27T19:24:17Z No. of bitstreams: 1 D2016 - Glauco Barbosa da Silva.pdf: 5776264 bytes, checksum: d50812d465487f52e8c02b7f636435ab (MD5) / Made available in DSpace on 2017-07-27T19:24:17Z (GMT). No. of bitstreams: 1 D2016 - Glauco Barbosa da Silva.pdf: 5776264 bytes, checksum: d50812d465487f52e8c02b7f636435ab (MD5) / Problem: From Modeling decision maker preferences, the Multicriteria Decision Aid (MCDA) is a field dedicated to the study of real-world decision-making problems that are, usually, too complex and not so well-structured to be considered through the examination of a single point of view (criteria). This feature of MCDA implies that a comprehensive model of a decision maker situation cannot be “created”, but instead, the model should be developed to meet the requirements of the Decision Maker (DM). In general, the development of such a model can only be achieved through an iterative and interactive process, until the preferences of the decision maker are consistently represented in the model. However, an interactive method is a procedure that consists of an alternation of calculation and discussion stages, which presumes that the decision maker is willing to answer a large number of relatively difficult questions. For instance, one of the main difficulties to be faced when interacting with a Decision Maker in order to build a decision aid procedure is the various parameters’ elicitation of the preference model. Methodology: In this thesis, as an alternative to interactive process, among the main streams of MCDA, a Preference Disaggregation Analysis method was used, which is considered to assess or to infer preference models from the given preferential structures and to address decision-aiding activities to elicit preferential information and to construct decision models from decision examples. Combining Composition Probabilistic of Preference with Data Mining techniques, a proposal of a three-step process is presented: attribute selection; clustering; and classification. The first and the second ones are data mining tasks and the last one is a multicriteria task. Purpose: This thesis aims to present a new approach with a Data Mining Layer (attribute selection and/or clustering) in Composition Probabilistic of Preferences in Trichotomic procedure (CPP-TRI), which combines data mining techniques with a Multicriteria Decision Aid method in classification (sorting) problems. Findings: The decision maker ability to comprehend without powerful tools has been exceeded. Therefore, important decisions are often made based not on the information-rich data stored in data repositories, but rather, on intuition of the decision maker. Involved in similar problems, the connections between disaggregation methods and data mining (identifying patterns, extracting knowledge from data, eliciting preferential information and constructing decision models from decision examples) are explored to combine and improve the CPP-TRI Method from Attribute Selection Techniques. / Problem: From Modeling decision maker preferences, the Multicriteria Decision Aid (MCDA) is a field dedicated to the study of real-world decision-making problems that are, usually, too complex and not so well-structured to be considered through the examination of a single point of view (criteria). This feature of MCDA implies that a comprehensive model of a decision maker situation cannot be “created”, but instead, the model should be developed to meet the requirements of the Decision Maker (DM). In general, the development of such a model can only be achieved through an iterative and interactive process, until the preferences of the decision maker are consistently represented in the model. However, an interactive method is a procedure that consists of an alternation of calculation and discussion stages, which presumes that the decision maker is willing to answer a large number of relatively difficult questions. For instance, one of the main difficulties to be faced when interacting with a Decision Maker in order to build a decision aid procedure is the various parameters’ elicitation of the preference model. Methodology: In this thesis, as an alternative to interactive process, among the main streams of MCDA, a Preference Disaggregation Analysis method was used, which is considered to assess or to infer preference models from the given preferential structures and to address decision-aiding activities to elicit preferential information and to construct decision models from decision examples. Combining Composition Probabilistic of Preference with Data Mining techniques, a proposal of a three-step process is presented: attribute selection; clustering; and classification. The first and the second ones are data mining tasks and the last one is a multicriteria task. Purpose: This thesis aims to present a new approach with a Data Mining Layer (attribute selection and/or clustering) in Composition Probabilistic of Preferences in Trichotomic procedure (CPP-TRI), which combines data mining techniques with a Multicriteria Decision Aid method in classification (sorting) problems. Findings: The decision maker ability to comprehend without powerful tools has been exceeded. Therefore, important decisions are often made based not on the information-rich data stored in data repositories, but rather, on intuition of the decision maker. Involved in similar problems, the connections between disaggregation methods and data mining (identifying patterns, extracting knowledge from data, eliciting preferential information and constructing decision models from decision examples) are explored to combine and improve the CPP-TRI Method from Attribute Selection Techniques.

The problem of this study was to examine the equivalency of two different types of criterion-referenced item-selection techniques on simulated data as item pools varied in degrees of item difficulty. A pretest-posttest design was employed in which pass-fail scores were randomly generated for item pools of twenty-five items. From the item pools, the two techniques determined which items were to be used to make up twelve-item criterion-referenced tests. The twenty-five items also were rank ordered according to the discrimination power of the two techniques.

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Virtual Reality has once again emerged as a platform with great potential for exploratory research. An expectation for the next generation virtual reality platforms is to be used as a tool for graphical designers as a new way to access the virtual world and interact with digital content. Just as mobile applications are developed for smaller screens with touch capabilities and desktop applications for computer screens with the input of mouse and keyboard, the interfaces of VR applications need to be designed with the capabilities and limitations of the platform in mind. A common component in modern graphic editing software is layer management: having the final output of the application divided into sub-components. This thesis explores how layer management can best be implemented in room-scale Virtual Reality with a focus on selection, navigation and manipulation through an iterative design study. The study concludes that, to improve the learnability of a system, interactions should be based on real-world interaction for naturalistic tasks while drawing inspiration from desktop applications for more abstract tasks. Furthermore, the environment needs to be adjusted to the systems designated tasks as well as the physical characteristics of the user. Lastly, as previous studies have suggested, amplifying the movement of manipulated objects in relation to the movement of the controller decreases the required movement of the user, reducing fatigue and increasing the user’s reach. However, this amplification was perceived as a reduction in precision, which some users valued more than movement reduction. Therefore, the amplification factor should be adjusted in relation to the operation’s precision requirements. While directly applicable to layer management in VR, these findings could serve as guidelines for applications utilizing 2D content in a virtual environment, room-scale VR applications designed to perform abstract tasks, and productivity tools for Virtual Reality. / Virtual Reality (VR) har på senare år sett ett uppsving både vad gäller teknisk utveckling och intresse hos konsumenter. Den nya generationens VR-plattformar har stor potential för utforskande studier både vad gäller användningsområden och interaktionsgränssnitt. En av förväntningarna är att VR ska kunna användas inom grafisk formgivning som ett verktyg för att tillgå- och interagera med digitalt innehåll på nya sätt. Precis som mobila applikationer är utvecklade för mindre touch-skärmar och PC-applikationer är designade för mus- och tangentbordsinteraktion med återkoppling genom en datorskärm så kommer gränssnitten för framtidens VR applikationer att vara utformade efter denna plattforms specifikationer. En vanlig komponent i dagens grafiska redigeringsprogramvaror är bildlagerhantering; att ha en bild eller bildruta uppdelad i mindre delar där varje del kan redigeras och påverkas som en separat enhet. Denna uppsats utforskar genom en iterativ designstudie hur bildlagerhantering kan implementeras i en VR miljö med fokus på navigation, val av objekt och manipulation av objekt. Studien visar att interaktionsgränssnitten som baseras på interaktioner med verkligheten och interaktion med traditionella PC applikationer för naturliga respektive abstrakta operationer gör interaktionerna lättare att lära sig och förstå. Förutom de uppgifter som systemet är ämnat att utföra bör även utformningen av den virtuella miljön ta hänsyn till de fysiska egenskaperna hos användaren. Som tidigare studier har visat så kan ett förstärkt utslag av manipulerade objekt i förhållande till kontrollen minska den rörelse som krävs av användaren för att utföra en uppgift och därigenom minska trötthet och öka användarens effektiva räckvidd. Denna förstärkning uppfattades dock som en reducering av precision, vilket vissa användare värdesatte mer än reducering av krävd rörelse. Därför ska förstärkningsgraden sättas i relation till den precision som krävs av varje operation. Studiens resultat är direkt applicerbara för lagerhantering i VR men kan också användas som riktlinjer för VR applikationer som hanterar 2D-innehåll i en 3D miljö samt VR applikationer med syfte att användas som produktivitetsverktyg.