03184oam 2200769I 450 991045457600332120210107002535.01-134-82065-81-280-32064-80-203-42917-60-203-29543-910.4324/9780203429174 (CKB)111056485522812(EBL)166812(OCoLC)264502837(SSID)ssj0000140458(PQKBManifestationID)11157264(PQKBTitleCode)TC0000140458(PQKBWorkID)10052929(PQKB)11366709(MiAaPQ)EBC166812(OCoLC)52069608(EXLCZ)9911105648552281220180331d1997 uy 0engur|n|---|||||txtccrDo organizations have feelings? /Martin AlbrowNew York :Routledge,1997.1 online resource (199 p.)First published 1996 by Routledge, London.0-415-11547-7 0-415-11546-9 Includes bibliographical references (pages ) and index.Book Cover; Title; Contents; Preface; Acknowledgements; INTRODUCTION: THE NECESSITY FOR THE SOCIOLOGY OF ORGANIZING; Objectivity and reflexivity; THE STUDY OF ORGANIZATIONS; OBJECTIVITY OR BIAS?; THE DIALECTIC OF SCIENCE AND VALUES IN THE STUDY OF ORGANIZATIONS; Reassessing Weber for current uses; THE APPLICATION OF THE WEBERIAN CONCEPT OF RATIONALIZATION TO CONTEMPORARY CONDITIONS; REDEFINING AUTHORITY FOR POST-WEBERIAN CONDITIONS; Feeling for new organization; SINE IRA ET STUDIO; OR DO ORGANIZATIONS HAVE FEELINGS?; REVISING ACCOUNTS OF ORGANIZATIONAL FEELINGOrganizing returns from the socialSOCIOLOGY FOR POSTMODERN ORGANIZERS; WORKING THE NET with; SOCIOLOGY FOR ORGANIZATION IN THE GLOBAL AGE; Notes; Bibliography; Index; This book argues that adequate explanation of the way that organizations function for those engaged in business and those who study it must transcend the traditional divide between reason and emotion.Industrial managementSocial responsibility of businessSocial ScienceBusinessSocial responsibility of businessSocial aspectsIndustrial managementManagementHILCCBusiness & EconomicsHILCCManagement Styles & CommunicationHILCCElectronic books.Industrial management.Social responsibility of business.Social Science.Business.Social responsibility of businessSocial aspectsIndustrial managementManagementBusiness & EconomicsManagement Styles & Communication302.35658.4/08Albrow Martin.113343FlBoTFGFlBoTFGBOOK9910454576003321Do organizations have feelings1979318UNINA04955nam 2200481 450 991048871340332120220327091830.0981-336-726-1(CKB)4100000011979650(MiAaPQ)EBC6676429(Au-PeEL)EBL6676429(OCoLC)1259623724(PPN)260302511(EXLCZ)99410000001197965020220327d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierCyber security meets machine learning /Xiaofeng Chen, Willy Susilo, Elisa BertinoSingapore :Springer,[2021]©20211 online resource (168 pages)981-336-725-3 Intro -- Preface -- Contents -- IoT Attacks and Malware -- 1 Introduction -- 2 Background -- 2.1 Cybersecurity Kill Chains -- 2.2 Major IoT Security Concerns -- 3 Attack Classification -- 3.1 Passive/Information Stealing Attacks -- 3.2 Service Degradation Attacks -- 3.3 DDoS Attacks -- 4 IoT Malware Analysis and Classification -- 5 AI-Based IDS Solutions -- 6 Conclusion -- References -- Machine Learning-Based Online Source Identification for Image Forensics -- 1 Introduction -- 2 Related Work -- 2.1 Features Engineering for Image Source Identification -- 2.2 Statistical Learning-Based Image Source Identification -- 3 Proposed Scheme: OSIU -- 3.1 Unknown Sample Triage -- 3.2 Unknown Image Discovery -- 3.3 (K+1)-class Classification -- 4 Experiments and Results -- 4.1 Dataset and Experiment Settings -- 4.2 Features -- 4.3 Evaluation Metrics -- 4.4 Performance of Triaging Unknown Samples -- 4.5 Performance of OSIU -- 5 Conclusion -- References -- Reinforcement Learning Based Communication Security for Unmanned Aerial Vehicles -- 1 Introduction -- 2 Communication Security for Unmanned Aerial Vehicles -- 2.1 UAV Communication Model -- 2.2 Attack Model -- 3 Reinforcement Learning Based UAV Communication Security -- 3.1 Reinforcement Learning Based Anti-Jamming Communications -- 3.2 Reinforcement Learning Based UAV Communications Against Smart Attacks -- 4 UAV Secure Communication Game -- 4.1 Game Model -- 4.2 Nash Equilibrium of the Game -- 5 Related Work -- 5.1 General Anti-jamming Policies in UAV-Aided Communication -- 5.2 Reinforcement Learning in Anti-jamming Communication -- 5.3 Game Theory in Anti-jamming Communication -- 6 Conclusion -- References -- Visual Analysis of Adversarial Examples in Machine Learning -- 1 Introduction -- 2 Adversarial Examples -- 3 Generation of Adversarial Examples -- 4 Properties of Adversarial Examples.5 Distinguishing Adversarial Examples -- 6 Robustness of Models -- 7 Challenges and Research Directions -- 8 Conclusion -- References -- Adversarial Attacks Against Deep Learning-Based Speech Recognition Systems -- 1 Introduction -- 2 Background and Related Work -- 2.1 Speech Recognition -- 2.2 Adversarial Examples -- 2.3 Related Work -- 3 Overview -- 3.1 Motivation -- 3.2 Technical Challenges -- 4 White-Box Attack -- 4.1 Threat Model of White-Box Attack -- 4.2 The Detail Decoding Process of Kaldi -- 4.3 Gradient Descent to Craft Audio Clip -- 4.4 Practical Adversarial Attack Against White-Box Model -- 4.5 Experiment Setup of CommanderSong Attack -- 4.6 Evaluation of CommanderSong Attack -- 5 Black-Box Attack -- 5.1 Threat Model of Black-Box Attack -- 5.2 Transferability Based Approach -- 5.3 Local Model Approximation Approach -- 5.4 Alternate Models Based Generation Approach -- 5.5 Experiment Setup of Devil's Whisper Attack -- 5.6 Evaluation of Devil's Whisper Attack -- 6 Defense -- 7 Conclusion -- Appendix -- References -- A Survey on Secure Outsourced Deep Learning -- 1 Introduction -- 2 Deep Learning -- 2.1 Brief Survey on Deep Learning -- 2.2 Architecture of Deep Learning -- 2.3 Main Computation in Deep Learning -- 3 Outsourced Computation -- 3.1 Brief Survey on Outsourced Computation -- 3.2 System Model -- 3.3 Security Requirements -- 4 Outsourced Deep Learning -- 4.1 Brief Review on Outsourced Deep Learning -- 4.2 Privacy Concerns in Outsourced Deep Learning -- 4.3 Privacy-Preserving Techniques for Outsourced Deep Learning -- 4.4 Taxonomy Standard -- 4.5 Privacy-Preserving Training Outsourcing -- 4.6 Privacy-Preserving Inference Outsourcing -- 5 Conclusion and Future Research Perspectives -- References.ss.Machine learningTechniqueMachine learningSecurity measuresMachine learningTechnique.Machine learningSecurity measures.006.31Chen Xiaofeng850517Susilo WillyBertino ElisaMiAaPQMiAaPQMiAaPQBOOK9910488713403321Cyber security meets machine learning2814028UNINA