Approved for public release, distribution is unlimited / The concepts of DoD information operations and network centric warfare are still in their infancy. In order to develop concepts, the right conceptual models need to be developed from which to design and implement these concepts. Information operations and network centric warfare are fundamentally based on trust decisions. However, the key to developing these concepts is for DoD to develop the organizational framework from which trust, inside and outside, of an organization may be achieved and used to its advantage. In this thesis, an organizational model is submitted for review to be applied to DoD information systems and operational organizations. / Outstanding Thesis / Lieutenant, United States Navy

High school pupils operate in a macro (country-specific), meso (school-specific) and micro (personal) context and their information needs are always experienced in a context - sometimes as imposed school assignments or else self-generated, e.g. as everyday life information needs. Pupils source their information through various information channels and there is sometimes a perceived risk to acting on incorrect information. Compared to adults in information-intensive professions, researchers have found that pupils tend to be unconcerned about the credibility of information. Based on a literature survey, a trust model was compiled from a number of other models and adapted to serve as an information channel credibility model portraying the pupil in context with his/her perception of information channel credibility. The model was used as a framework for a study on high school pupils’ perceptions of information channel credibility and factors influencing their perceptions. The study was guided by the following research problem: How can school pupils’ perceptions of information channel credibility inform school-based interventions? In order to find answers, the following sub-questions were addressed: • What has been reported on perceptions of information credibility and information channel credibility, with specific reference to school pupils, students and adults, as well as professionals in information-intensive environments? • How can trust models guide a study of pupils’ perceptions of information channel credibility? • What factors influence school pupils’ perceptions of information channel credibility? • What school-based interventions could be recommended to address the shortcomings in the perceptions of pupils that can prepare them to meet the information requirements of adulthood? A self-administered print questionnaire was used in May 2015 to survey the perceptions of 548 South African high school pupils from three different schools covering the range of the socio-economic spectrum from wealthy through to pupils from poor, unemployed home environments. The study was conducted with grade 8 and grade 12 pupils (entry and exit grades for South African high schools) from a city in the Mpumalanga province of South Africa. Semi-structured interviews were conducted with the principals of the three schools. The results are reported as descriptive statistics supported with inferential statistics and qualitative analysis where relevant. The findings are that pupils’ perceptions of information channel credibility are affected by the perceived risk of acting on incorrect information, their previous experience and the context (i.e. type of information need, whether the need is imposed or self-generated and pupil demographics) in which the information need occurs. Pupils used a level of metacognition with regard to information channel credibility. The model proved useful to guide data collection that can guide school-based interventions. It holds potential to be further adapted to actually reflect school-based interventions. School-based interventions are suggested to encourage responsible assessment of information channel credibility, including the simulation of risk by means of mark allocation for metacognition about information channel credibility, intentional exposure of pupils to a wide range of information needs and exposure to highly credible as well as less credible information channels. / Thesis (PhD)--University of Pretoria, 2016. / Information Science / PhD / Unrestricted

Distributed systems like e-commerce and e-market places, peer-to-peer networks, social networks, and mobile ad hoc networks require cooperation among the participating entities to guarantee the formation and sustained existence of network services. The reliability of interactions among anonymous entities is a significant issue in such environments. The distributed entities establish connections to interact with others, which may include selfish and misbehaving entities and result in bad experiences. Therefore, trustworthiness evaluation using trust management techniques has become a significant issue in securing these environments to allow entities decide on the reliability and trustworthiness of other entities, besides it helps coping with defection problems and stimulating entities to cooperate. Recent models on evaluating trustworthiness in distributed systems have heavily focused on assessing trustworthiness of entities and isolate misbehaviours based on single trust metrics. Less effort has been put on the investigation of the subjective nature and differences in the way trustworthiness is perceived to produce a composite multidimensional trust metrics to overcome the limitation of considering single trust metric. In the light of this context, this thesis concerns the evaluation of entities’ trustworthiness by the design and investigation of trust metrics that are computed using multiple properties of trust and considering environment. Based on the concept of probabilistic theory of trust management technique, this thesis models trust systems and designs cooperation techniques to evaluate trustworthiness in mobile ad hoc networks (MANETs). A recommendation based trust model with multi-parameters filtering algorithm, and multidimensional metric based on social and QoS trust model are proposed to secure MANETs. Effectiveness of each of these models in evaluating trustworthiness and discovering misbehaving nodes prior to interactions, as well as their influence on the network performance has been investigated. The results of investigating both the trustworthiness evaluation and the network performance are promising.

Dynamic spectrum access enabled by cognitive radio networks are envisioned to drive the next generation wireless networks that can increase spectrum utility by opportunistically accessing unused spectrum. Due to the policy constraint that there could be no interference to the primary (licensed) users, secondary cognitive radios have to continuously sense for primary transmissions. Typically, sensing reports from multiple cognitive radios are fused as stand-alone observations are prone to errors due to wireless channel characteristics. Such dependence on cooperative spectrum sensing is vulnerable to attacks such as Secondary Spectrum Data Falsification (SSDF) attacks when multiple malicious or selfish radios falsify the spectrum reports. Hence, there is a need to quantify the trustworthiness of radios that share spectrum sensing reports and devise malicious node identification and robust fusion schemes that would lead to correct inference about spectrum usage. In this work, we propose an anomaly monitoring technique that can effectively capture anomalies in the spectrum sensing reports shared by individual cognitive radios during cooperative spectrum sensing in a multi-channel distributed network. Such anomalies are used as evidence to compute the trustworthiness of a radio by its neighbours. The proposed anomaly monitoring technique works for any density of malicious nodes and for any physical environment. We propose an optimistic trust heuristic for a system with a normal risk attitude and show that it can be approximated as a beta distribution. For a more conservative system, we propose a multinomial Dirichlet distribution based conservative trust framework, where Josang*s Belief model is used to resolve any uncertainty in information that might arise during anomaly monitoring. Using a machine learning approach, we identify malicious nodes with a high degree of certainty regardless of their aggressiveness and variations introduced by the pathloss environment. We also propose extensions to the anomaly monitoring technique that facilitate learning about strategies employed by malicious nodes and also utilize the misleading information they provide. We also devise strategies to defend against a collaborative SSDF attack that is launched by a coalition of selfish nodes. Since, defense against such collaborative attacks is difficult with popularly used voting based inference models or node centric isolation techniques, we propose a channel centric Bayesian inference approach that indicates how much the collective decision on a channels occupancy inference can be trusted. Based on the measured observations over time, we estimate the parameters of the hypothesis of anomalous and non-anomalous events using a multinomial Bayesian based inference. We quantitatively define the trustworthiness of a channel inference as the difference between the posterior beliefs associated with anomalous and non-anomalous events. The posterior beliefs are updated based on a weighted average of the prior information on the belief itself and the recently observed data. Subsequently, we propose robust fusion models which utilize the trusts of the nodes to improve the accuracy of the cooperative spectrum sensing decisions. In particular, we propose three fusion models: (i) optimistic trust based fusion, (ii) conservative trust based fusion, and (iii) inversion based fusion. The former two approaches exclude untrustworthy sensing reports for fusion, while the last approach utilizes misleading information. All schemes are analyzed under various attack strategies. We propose an asymmetric weighted moving average based trust management scheme that quickly identifies on-off SSDF attacks and prevents quick trust redemption when such nodes revert back to temporal honest behavior. We also provide insights on what attack strategies are more effective from the adversaries* perspective. Through extensive simulation experiments we show that the trust models are effective in identifying malicious nodes with a high degree of certainty under variety of network and radio conditions. We show high true negative detection rates even when multiple malicious nodes launch collaborative attacks which is an improvement over existing voting based exclusion and entropy divergence techniques. We also show that we are able to improve the accuracy of fusion decisions compared to other popular fusion techniques. Trust based fusion schemes show worst case decision error rates of 5% while inversion based fusion show 4% as opposed majority voting schemes that have 18% error rate. We also show that the proposed channel centric Bayesian inference based trust model is able to distinguish between attacked and non-attacked channels for both static and dynamic collaborative attacks. We are also able to show that attacked channels have significantly lower trust values than channels that are not– a metric that can be used by nodes to rank the quality of inference on channels.

Distributed systems like e-commerce and e-market places, peer-to-peer networks, social networks, and mobile ad hoc networks require cooperation among the participating entities to guarantee the formation and sustained existence of network services. The reliability of interactions among anonymous entities is a significant issue in such environments. The distributed entities establish connections to interact with others, which may include selfish and misbehaving entities and result in bad experiences. Therefore, trustworthiness evaluation using trust management techniques has become a significant issue in securing these environments to allow entities decide on the reliability and trustworthiness of other entities, besides it helps coping with defection problems and stimulating entities to cooperate. Recent models on evaluating trustworthiness in distributed systems have heavily focused on assessing trustworthiness of entities and isolate misbehaviours based on single trust metrics. Less effort has been put on the investigation of the subjective nature and differences in the way trustworthiness is perceived to produce a composite multidimensional trust metrics to overcome the limitation of considering single trust metric. In the light of this context, this thesis concerns the evaluation of entities’ trustworthiness by the design and investigation of trust metrics that are computed using multiple properties of trust and considering environment. Based on the concept of probabilistic theory of trust management technique, this thesis models trust systems and designs cooperation techniques to evaluate trustworthiness in mobile ad hoc networks (MANETs). A recommendation based trust model with multi-parameters filtering algorithm, and multidimensional metric based on social and QoS trust model are proposed to secure MANETs. Effectiveness of each of these models in evaluating trustworthiness and discovering misbehaving nodes prior to interactions, as well as their influence on the network performance has been investigated. The results of investigating both the trustworthiness evaluation and the network performance are promising. / Ministry of Higher Education in Libya and the Libyan Cultural Attaché bureau in London