Exploring Consumers’ Attitudes of Smart TV Related Privacy Risks

A number of privacy risks are inherent in the Smart TV ecosystem. It is likely that many consumers are unaware of these privacy risks. Alternatively, they might be aware but consider the privacy risks acceptable. In order to explore this, we carried out an online survey with 200 participants to determine whether consumers were aware of Smart TV related privacy risks. The responses revealed a meagre level of awareness. We also explored consumers’ attitudes towards specific Smart TV related privacy risks. We isolated a number of factors that influenced rankings and used these to develop awareness-raising messages. We tested these messages in an online survey with 155 participants. The main finding was that participants were generally unwilling to disconnect their Smart TVs from the Internet because they valued the Smart TV’s Internet functionality more than their privacy. We subsequently evaluated the awareness-raising messages in a second survey with 169 participants, framing the question differently. We asked participants to choose between five different Smart TV Internet connection options, two of which retained functionality but entailed expending time and/or effort to preserve privacy

Simulating the conflict between reputation and profitability for online rating portals

We simulate the process of possible interactions between a set of competitive services and a set of portals that provide online rating for these services. We argue that to have a profitable business, these portals are forced to have subscribed services that are rated by the portals. To satisfy the subscribing services, we make the assumption that the portals improve the rating of a given service by one unit per transaction that involves payment. In this study we follow the 'what-if' methodology, analysing strategies that a service may choose from to select the best portal for it to subscribe to, and strategies for a portal to accept the subscription such that its reputation loss, in terms of the integrity of its ratings, is minimised. We observe that the behaviour of the simulated agents in accordance to our model is quite natural from the real-would perspective. One conclusion from the simulations is that under reasonable conditions, if most of the services and rating portals in a given industry do not accept a subscription policy similar to the one indicated above, they will lose, respectively, their ratings and reputations, and, moreover the rating portals will have problems in making a profit. Our prediction is that the modern portal-rating based economy sector will eventually evolve into a subscription process similar to the one we suggest in this study, as an alternative to a business model based purely on advertising

Enhancing Undergraduate AI Courses through Machine Learning Projects

It is generally recognized that an undergraduate introductory Artificial Intelligence course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core topics that are typically covered. The paper presents work funded by the National Science Foundation to address this problem and to enhance the student learning experience in the course. Our work involves the development of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. A suite of hands-on semester-long projects are developed, each involving the design and implementation of a learning system that enhances a commonly-deployed application. The projects use machine learning as a unifying theme to tie together the core AI topics. In this paper, we will first provide an overview of our model and the projects being developed and will then present in some detail our experiences with one of the projects – Web User Profiling which we have used in our AI class

Knowledge Representation Concepts for Automated SLA Management

Outsourcing of complex IT infrastructure to IT service providers has increased substantially during the past years. IT service providers must be able to fulfil their service-quality commitments based upon predefined Service Level Agreements (SLAs) with the service customer. They need to manage, execute and maintain thousands of SLAs for different customers and different types of services, which needs new levels of flexibility and automation not available with the current technology. The complexity of contractual logic in SLAs requires new forms of knowledge representation to automatically draw inferences and execute contractual agreements. A logic-based approach provides several advantages including automated rule chaining allowing for compact knowledge representation as well as flexibility to adapt to rapidly changing business requirements. We suggest adequate logical formalisms for representation and enforcement of SLA rules and describe a proof-of-concept implementation. The article describes selected formalisms of the ContractLog KR and their adequacy for automated SLA management and presents results of experiments to demonstrate flexibility and scalability of the approach.Comment: Paschke, A. and Bichler, M.: Knowledge Representation Concepts for Automated SLA Management, Int. Journal of Decision Support Systems (DSS), submitted 19th March 200

Technology Readiness Motivators and Online Behavioural Advertising: A Perceived Benefits-Risk Assessment Using Privacy Calculus Theory

Purpose: The present research intended to find whether the technology readiness motivators, Optimism, and innovativeness, impact the user's intention to accept Online Behavioural Advertising (OBA), an area that requires additional research.   Theoretical framework: Even though these personalized advertisements provide an enhanced user experience, they provide users with advertisements based on their online surfing behavior, and unfortunately, at the same time, it also creates privacy concerns. At the same time, Privacy Calculus Theory (PCT) is considered an appropriate theory when it comes to a rational benefits-costs assessment of the privacy-centred decision-making by internet users.   Design/Methodology: Based on an extensive literature review, a conceptual model is being proposed, and a scenario-based questionnaire was developed and pursued on internet users' experience of the subject matter. Six hundred ten valid responses were received, and PLS-SEM was used to analyze the results.   Findings: The results show that Optimism and innovativeness have a direct and indirect effect on the intention to accept Online Behavioural Advertising (OBA). Technology readiness Motivators have a detrimental impact on the intention to accept OBA.   Research, Practical and Social implications: Based on our findings, we may be able to gain a deeper understanding of the theory behind targeted, data-driven digital advertising and the way in which it pertains to online shopping. Presented here is evidence to support the theory that the predisposition of users toward new technology could be the reason for users ranking perceived benefits higher than risk.   Originality/Value: This study attributes original work in the sense that it is the first time that an individual’s predisposition towards technology has been taken into consideration while analysing the acceptance of OBA grounded on the Privacy Calculus framework

Finding secure compositions of software services: Towards a pattern based approach

In service based systems, there is often a need to replace services at runtime as they become either unavailable or they no longer meet required quality or security properties. In such cases, it is often necessary to build compositions of services that can replace a problematic service because no single service with a sufficient match to it can be located. In this paper, we present an approach for building compositions of services that can preserve required security properties. Our approach is based on the use of secure composition patterns which are applied in connection with basic discovery mechanisms to build secure service compositions