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Rational Cybersecurity for Business

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ISBN: 9781484259528 Year: Pages: 333 DOI: 10.1007/978-1-4842-5952-8 Language: English
Publisher: Springer Nature
Subject: Computer Science
Added to DOAB on : 2020-09-23 00:04:54
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Use the guidance in this comprehensive field guide to gain the support of your top executives for aligning a rational cybersecurity plan with your business. You will learn how to improve working relationships with stakeholders in complex digital businesses, IT, and development environments. You will know how to prioritize your security program, and motivate and retain your team. Misalignment between security and your business can start at the top at the C-suite or happen at the line of business, IT, development, or user level. It has a corrosive effect on any security project it touches. But it does not have to be like this. Author Dan Blum presents valuable lessons learned from interviews with over 70 security and business leaders. You will discover how to successfully solve issues related to: risk management, operational security, privacy protection, hybrid cloud management, security culture and user awareness, and communication challenges. This open access book presents six priority areas to focus on to maximize the effectiveness of your cybersecurity program: risk management, control baseline, security culture, IT rationalization, access control, and cyber-resilience. Common challenges and good practices are provided for businesses of different types and sizes. And more than 50 specific keys to alignment are included. What You Will Learn Improve your security culture: clarify security-related roles, communicate effectively to businesspeople, and hire, motivate, or retain outstanding security staff by creating a sense of efficacy Develop a consistent accountability model, information risk taxonomy, and risk management framework Adopt a security and risk governance model consistent with your business structure or culture, manage policy, and optimize security budgeting within the larger business unit and CIO organization IT spend Tailor a control baseline to your organization’s maturity level, regulatory requirements, scale, circumstances, and critical assets Help CIOs, Chief Digital Officers, and other executives to develop an IT strategy for curating cloud solutions and reducing shadow IT, building up DevSecOps and Disciplined Agile, and more Balance access control and accountability approaches, leverage modern digital identity standards to improve digital relationships, and provide data governance and privacy-enhancing capabilities Plan for cyber-resilience: work with the SOC, IT, business groups, and external sources to coordinate incident response and to recover from outages and come back stronger Integrate your learnings from this book into a quick-hitting rational cybersecurity success plan Who This Book Is For Chief Information Security Officers (CISOs) and other heads of security, security directors and managers, security architects and project leads, and other team members providing security leadership to your business

Knowledge Manageation and Big Data: Implications for Sustainability, Policy Making and Competitiveness

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ISBN: 9783039280087 9783039280094 Year: Pages: 416 DOI: 10.3390/books978-3-03928-009-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Education
Added to DOAB on : 2020-01-07 09:21:22
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The evolution of knowledge management theory and the special emphasis on human and social capital sets new challenges for knowledge-driven and technology-enabled innovation. Emerging technologies including big data and analytics have significant implications for sustainability, policy making, and competitiveness. This edited volume promotes scientific research into the potential contributions knowledge management can make to the new era of innovation and social inclusive economic growth. We are grateful to all the contributors of this edition for their intellectual work. The organization of the relevant debate is aligned around three pillars: SECTION A. DATA, KNOWLEDGE, HUMAN AND SOCIAL CAPITAL FOR INNOVATION: We elaborate on the new era of knowledge types and the emerging forms of social capital and their impact on technology-driven innovation. Topics include: Social Networks; Smart Education; Social Capital; Corporate Innovation; Disruptive Innovation; Knowledge integration; Enhanced Decision-Making. SECTION B. KNOWLEDGE MANAGEMENT & BIG DATA ENABLED INNOVATION: In this section, knowledge management and big data applications and systems are presented. Selective topic include: Crowdsourcing Analysis; Natural Language Processing; Data Governance; Knowledge Extraction; Ontology Design Semantic Modeling SECTION C. SUSTAINABLE DEVELOPMENT: In the section, the debate on the impact of knowledge management and big data research to sustainability is promoted with integrative discussion of complementary social and technological factors including: Big Social Networks on Sustainable Economic Development; Business Intelligence

Keywords

innovation capability --- social capital --- knowledge creation --- human capital investment --- training --- education --- communication --- six sigma --- structural equation model --- leadership --- innovation performance --- knowledge sharing --- social capital --- project-based organization --- citizen-scientist --- climate change --- crowdsourcing --- MTurk --- social networks --- Twitter --- social networks --- big data --- big data analysis --- sustainable development --- text mining --- NLP --- technological information --- patent analysis --- text structure --- top management team --- strategic decision-making --- risk perception --- knowledge creation process --- process innovation capability --- product innovation capability --- sustainable competitive advantage --- data governance --- cloud computing --- cloud data governance --- taxonomy --- systematic review --- holistic --- text feature extraction --- patent analysis --- hybrid neural networks --- mechanical patent classification --- international technological collaboration --- IC manufacturing --- patent association analysis --- social network analysis --- collaboration network --- corporate sustainability --- business intelligence --- multi-dimensional data model --- key performance indicators --- knowledge assets --- knowledge embeddedness --- knowledge specificity --- disruptive innovation --- personalized business mode --- technology acceptance model --- user acceptance --- data analysis --- ontology design --- knowledge management --- heterogeneous architectures --- Big Data --- transformational training programs-TTP --- quality orientation of employees-QOE --- employee loyalty-EL --- universities --- Jordan --- administrative file --- administrative procedure --- sustainability --- open data --- linked data --- provenance --- RDF --- PROV-O --- P-PLAN --- big data --- visualizing --- intellectual structure --- big data environment --- co-citation network --- collaboration network --- sustainability --- bibliometric --- knowledge management --- keywords analysis --- intellectual structure --- emerging trends --- knowledge mapping --- new ventures --- internal social networks --- absorptive capacity --- innovation --- big data --- competitive advantage --- disruptive innovation --- human capital --- innovation --- knowledge management --- sustainability --- smart education --- social networks --- social media --- conceptual maturity model --- technology-enhanced learning process

Big Data Research for Social Sciences and Social Impact

Authors: --- ---
ISBN: 9783039282203 9783039282210 Year: Pages: 416 DOI: 10.3390/books978-3-03928-221-0 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.

Keywords

big data --- illegal accommodation --- institutional innovation --- transaction costs --- housing problem --- building stock management --- Hong Kong --- information diffusion --- community detection --- topic analysis --- sentiment analysis --- social networks --- Social network --- sustainable development --- review voting --- online community --- paradox --- smart citizens --- experimental cities --- smart cities --- technopolitics --- big data --- Barcelona --- data commons --- decision-makers --- policy --- GDPR --- big data --- social sciences --- decision-making --- data analyst --- filtering --- framing --- big data --- maturity model --- temporal analytics --- advanced business analytics --- big data analytic methods --- semantic network analysis --- framings --- NodeXL --- promising technology --- research frontier --- bibliometric analysis --- hype cycle --- technology platforms --- sustainable agri-food systems --- innovation in sustainable agriculture --- online data --- data mining --- TP organics --- big data research --- point of interests (POI) --- sustainability development --- spatial accessibility of residential public services --- Xiamen City --- big data --- sales prediction --- online word-of-mouth --- dynamic topic model --- product attributes --- back-propagation neural network --- systematic and replicable patent analysis method --- problem-solved concept --- context–problem network --- network data analysis --- sustainable wireless energy transmission technology --- big data analytics --- text mining --- association rule --- car review --- skills --- researchers --- early career --- text mining --- social media big data --- lbsn --- check-in density --- spatiotemporal analysis --- KDE --- GWR --- SDE --- Guangzhou --- educational data mining --- learning analytics --- machine learning --- big data --- prediction grades --- destination image --- user-generated content --- online travel review --- big data analytics --- opinion mining --- sentiment analysis --- resource optimisation --- place sustainability --- TripAdvisor --- Greek Attica --- opinion mining --- social media --- social networks --- sentiment analysis --- sentiment polarity classification --- social impact --- big data research --- information systems --- analytics --- decision making --- social sciences --- big data research --- social and humanistic computing --- social sciences --- social good --- social impact --- machine learning --- knowledge management --- web science --- data science --- social inclusive economic growth --- sustainability --- innovation --- innovation networks

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