7,662 research outputs found

    South American Expert Roundtable : increasing adaptive governance capacity for coping with unintended side effects of digital transformation

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    This paper presents the main messages of a South American expert roundtable (ERT) on the unintended side effects (unseens) of digital transformation. The input of the ERT comprised 39 propositions from 20 experts representing 11 different perspectives. The two-day ERT discussed the main drivers and challenges as well as vulnerabilities or unseens and provided suggestions for: (i) the mechanisms underlying major unseens; (ii) understanding possible ways in which rebound effects of digital transformation may become the subject of overarching research in three main categories of impact: development factors, society, and individuals; and (iii) a set of potential action domains for transdisciplinary follow-up processes, including a case study in Brazil. A content analysis of the propositions and related mechanisms provided insights in the genesis of unseens by identifying 15 interrelated causal mechanisms related to critical issues/concerns. Additionally, a cluster analysis (CLA) was applied to structure the challenges and critical developments in South America. The discussion elaborated the genesis, dynamics, and impacts of (groups of) unseens such as the digital divide (that affects most countries that are not included in the development of digital business, management, production, etc. tools) or the challenge of restructuring small- and medium-sized enterprises (whose service is digitally substituted by digital devices). We identify specific issues and effects (for most South American countries) such as lack of governmental structure, challenging geographical structures (e.g., inclusion in high-performance transmission power), or the digital readiness of (wide parts) of society. One scientific contribution of the paper is related to the presented methodology that provides insights into the phenomena, the causal chains underlying “wanted/positive” and “unwanted/negative” effects, and the processes and mechanisms of societal changes caused by digitalization

    Cloud service discovery and analysis: a unified framework

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    Over the past few years, cloud computing has been more and more attractive as a new computing paradigm due to high flexibility for provisioning on-demand computing resources that are used as services through the Internet. The issues around cloud service discovery have considered by many researchers in the recent years. However, in cloud computing, with the highly dynamic, distributed, the lack of standardized description languages, diverse services offered at different levels and non-transparent nature of cloud services, this research area has gained a significant attention. Robust cloud service discovery approaches will assist the promotion and growth of cloud service customers and providers, but will also provide a meaningful contribution to the acceptance and development of cloud computing. In this dissertation, we have proposed an automated cloud service discovery approach of cloud services. We have also conducted extensive experiments to validate our proposed approach. The results demonstrate the applicability of our approach and its capability of effectively identifying and categorizing cloud services on the Internet. Firstly, we develop a novel approach to build cloud service ontology. Cloud service ontology initially is built based on the National Institute of Standards and Technology (NIST) cloud computing standard. Then, we add new concepts to ontology by automatically analyzing real cloud services based on cloud service ontology Algorithm. We also propose cloud service categorization that use Term Frequency to weigh cloud service ontology concepts and calculate cosine similarity to measure the similarity between cloud services. The cloud service categorization algorithm is able to categorize cloud services to clusters for effective categorization of cloud services. In addition, we use Machine Learning techniques to identify cloud service in real environment. Our cloud service identifier is built by utilizing cloud service features extracted from the real cloud service providers. We determine several features such as similarity function, semantic ontology, cloud service description and cloud services components, to be used effectively in identifying cloud service on the Web. Also, we build a unified model to expose the cloud service’s features to a cloud service search user to ease the process of searching and comparison among a large amount of cloud services by building cloud service’s profile. Furthermore, we particularly develop a cloud service discovery Engine that has capability to crawl the Web automatically and collect cloud services. The collected datasets include meta-data of nearly 7,500 real-world cloud services providers and nearly 15,000 services (2.45GB). The experimental results show that our approach i) is able to effectively build automatic cloud service ontology, ii) is robust in identifying cloud service in real environment and iii) is more scalable in providing more details about cloud services.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 201

    Enhancing Trust Management in Cloud Environment

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    AbstractTrust management has been identified as vital component for establishing and maintaining successful relational exchanges between e-commerce trading partners in cloud environment. In this highly competitive and distributed service environment, the assurances are insufficient for the consumers to identify the dependable and trustworthy Cloud providers. Due to these limitations, potential consumers are not sure whether they can trust the Cloud providers in offering dependable services. In this paper, we propose a multi-faceted trust management system architecture for cloud computing marketplaces, to support customers in identifying trustworthy cloud providers. This paper presents the important threats to a trust system and proposed a method for tackling these threats. It described the desired feature of a trust management system. It security components to determine the trustworthiness of e- commerce participants to helps online customers to decide whether or not to proceed with a transaction. Based on this framework, we proposed an approach for filtering out malicious feedbacks and a trust metric to evaluate the trustworthiness of service provider. Results of various simulation experiments show that the proposed multi-attribute trust management system can be highly effective in identifying risky transaction in electronic market places

    Investigating the influence of special on-off attacks on challenge-based collaborative intrusion detection networks

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    Intrusions are becoming more complicated with the recent development of adversarial techniques. To boost the detection accuracy of a separate intrusion detector, the collaborative intrusion detection network (CIDN) has thus been developed by allowing intrusion detection system (IDS) nodes to exchange data with each other. Insider attacks are a great threat for such types of collaborative networks, where an attacker has the authorized access within the network. In literature, a challenge-based trust mechanism is effective at identifying malicious nodes by sending challenges. However, such mechanisms are heavily dependent on two assumptions, which would cause CIDNs to be vulnerable to advanced insider attacks in practice. In this work, we investigate the influence of advanced on–off attacks on challenge-based CIDNs, which can respond truthfully to one IDS node but behave maliciously to another IDS node. To evaluate the attack performance, we have conducted two experiments under a simulated and a real CIDN environment. The obtained results demonstrate that our designed attack is able to compromise the robustness of challenge-based CIDNs in practice; that is, some malicious nodes can behave untruthfully without a timely detection

    The future of Cybersecurity in Italy: Strategic focus area

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    This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management

    Secure Cloud-Edge Deployments, with Trust

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    Assessing the security level of IoT applications to be deployed to heterogeneous Cloud-Edge infrastructures operated by different providers is a non-trivial task. In this article, we present a methodology that permits to express security requirements for IoT applications, as well as infrastructure security capabilities, in a simple and declarative manner, and to automatically obtain an explainable assessment of the security level of the possible application deployments. The methodology also considers the impact of trust relations among different stakeholders using or managing Cloud-Edge infrastructures. A lifelike example is used to showcase the prototyped implementation of the methodology

    Manipulation of Online Reviews: Analysis of Negative Reviews for Healthcare Providers

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    There is a growing reliance on online reviews in today’s digital world. As the influence of online reviews amplified in the competitive marketplace, so did the manipulation of reviews and evolution of fake reviews on these platforms. Like other consumer-oriented businesses, the healthcare industry has also succumbed to this phenomenon. However, health issues are much more personal, sensitive, complicated in nature requiring knowledge of medical terminologies and often coupled with myriad of interdependencies. In this study, we collated the literature on manipulation of online reviews, identified the gaps and proposed an approach, including validation of negative reviews of the 500 doctors from three different states: New York and Arizona in USA and New South Wales in Australia from the RateMDs website. The reviews of doctors was collected, which includes both numerical star ratings (1-low to 5-high) and textual feedback/comments. Compared to other existing research, this study will analyse the textual feedback which corresponds to the clinical quality of doctors (helpfulness and knowledge criteria) rather than process quality experiences. Our study will explore pathways to validate the negative reviews for platform provider and rank the doctors accordingly to minimise the risks in healthcare
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