Security in Iot Social Networks

Description

Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties. Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks. Provides several characteristics of social, network, and physical security associated with social information networks Presents the security mechanisms and events related to social information networks Covers emerging topics, such as network information structures like on-line social networks, heterogeneous and homogeneous information networks, and modern information networksIncludes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models Front Cover Security in IoT Social Networks Security in IoT Social Networks Copyright Contents Contributors 1 - Security in social networks 1. Introduction 2. Types of social networks 2.1 Personal networks 2.2 Status update networks 2.3 Location networks 2.4 Content-sharing networks 2.5 Shared-interest networks 3. Social networks security requirements 4. SN security technical 4.1 Privacy risks 4.2 Security risks 4.3 Anonymity risks 4.4 Other risks 5. What information is public? 5.1 Information a user shares 5.1.1 Information a user shares may include the following: 5.2 Information gathered through electronic tracking 5.3 Who can access information? 6. Fraud on social networks 6.1 Identity theft 6.1.1 Some fraud techniques to watch for 7. Tips to stay safe, private, and secure 8. Staying safe on social media sites 9. SNS security issues and challenges 10. Five top social media security threats 10.1 Mobile apps 10.2 Social engineering 10.3 Social networking sites 10.4 Your employees 10.5 Lack of a social media policy 11. Privacy and security of social networks for home users 12. Social media security tips to mitigate risks 12.1 Common social media security risks 12.1.1 Human error 12.1.2 Third-party apps 12.1.3 Phishing attacks and scams 12.1.4 Imposter accounts 12.1.5 Malware attacks and hacks 12.1.6 Privacy settings 12.1.7 Unsecured mobile phones 12.2 Social media security tips and best practices 12.2.1 Create a social media policy 12.2.2 Train your staff on social media security best practices 12.2.3 Limit social media access 12.2.4 Set up a system of approvals for social posts 12.2.5 Put someone in charge 12.2.6 Monitor your accounts and engage in social listening 12.2.7 Invest in security technology 12.2.8 Perform a regular audit 13. Securing Social Security's future 14. Humans want Social Security 14.1 Most humans need Social Security 15. Social Security can be strengthened 16. Conclusion References Further reading 2 - Emerging social information networks applications and architectures 1. Introduction 1.1 Introduction to web: historical aspects of the web relative to the social network 1.2 Introduction to social networks 1.3 Social networks architecture 2. Background with new technologies 2.1 Introduction to Semantic Web technology 2.2 Overview of semantic web protocol stack 2.2.1 Syntactic layer 2.2.1.1 RDF/XML 2.2.1.1 RDF/XML 2.2.2 Metadata layer 2.2.2.1 Resource description framework 2.2.2.1 Resource description framework 2.2.2.2 RDFs (RDF schema) 2.2.2.2 RDFs (RDF schema) 2.2.3 Ontology layer 2.2.4 Logic layer 2.2.4.1 SWRL rules (inference) 2.2.4.1 SWRL rules (inference) 2.2.5 Trust and proof layer 2.3 Challenge with semantic web 2.3.1 Semantics-based web search engines 3. Knowledge representation and data processing management 3.1 Introduction to ontology 3.2 Ontology-based knowledge representation 3.2.1 Semantic knowledge representations 3.2.2 Spatial knowledge representation 3.2.3 Temporal knowledge representation 3.3 Query processing in semantic web databases 3.3.1 Query representation and processing 3.3.2 Evaluation of SPARQL queries 3.4 Key challenges in query processing 4. Social information networks applications and architecture 4.1 Introduction to social network architecture and applications 4.2 Challenges in new approaches 4.3 Challenges in the network architecture 4.4 Challenges in software design 4.5 Challenges of social network application development 5. Conclusion References 3 - Cyber security in mobile social networks 1. Introduction 2. Challenges in mobile app security 2.1 Device fragmentation 2.2 Tools for mobile automation testing 2.3 Weak encryptions 2.4 Weak hosting controls 2.5 Insecure data storage 3. What is a mobile threat? 3.1 Application-based threats 3.2 Web-based threats 3.3 Network threats 3.4 Physical threats 4. Types of wireless attacks 4.1 Packet sniffing 4.2 Rogue access point 4.3 Password theft 4.4 Man-in-the-middle attack 4.5 Jamming 4.6 War driving 4.7 Bluetooth attacks 4.8 WEP/WPA attacks 5. Attacks based on communication 5.1 Consequences 5.2 Attack based on SMS and MMS 6. Attacks based on vulnerabilities in software applications and hardware 6.1 Other attacks are based on flaws in the operating system or applications on the phone 6.1.1 Web browser 6.1.2 Operating system 6.2 Attacks based on hardware vulnerabilities 6.2.1 Electromagnetic waveforms 6.2.2 Juice jacking 6.2.3 Jailbreaking and rooting 7. Portability of malware across platforms 7.1 Resource monitoring in the smartphone 7.2 Battery 7.3 Memory usage 7.4 Network traffic 7.5 Services 7.6 Network surveillance 7.7 Spam filters 7.8 Encryption of stored or transmitted information 7.9 Telecom network monitoring 7.10 Manufacturer surveillance 7.11 Remove debug mode 7.12 Default settings 7.13 Security audit of apps 7.14 Detect suspicious applications demanding rights 7.15 Revocation procedures 7.16 Avoid heavily customized systems 7.17 User awareness 7.18 Being skeptical 7.19 Permissions given to applications 8. How to secure your mobile device 8.1 Use strong passwords/biometrics 8.2 Ensure public or free Wi-Fi is protected 8.3 Utilize VPN 8.4 Encrypt your device 8.5 Install an antivirus application 9. Mobile security threats you should take seriously 9.1 Data leakage 9.2 Social engineering 9.3 Wi-Fi interference 9.4 Out-of-date devices 9.5 Cryptojacking attacks 9.6 Poor password hygiene 9.7 Physical device breaches 10. Tips for securing Wi-Fi 10.1 Use WPA2 security 10.2 Minimize your network reach 10.3 Use firewalls 10.4 Use a VPN on open networks 10.5 Update software and firmware 10.6 Use strong passwords 10.7 Change the login credentials 10.8 Disable your SSID (service set identifier) broadcast 10.9 Enable MAC filtering 11. Challenges and open issues 11.1 Key technical recommendations 12. Conclusion References Further reading 4 - Influence of social information networks and their propagation 1. Social influence: a brief outline 1.1 Brief introduction to social networking 2. Social media “friends” 3. Homophily or influence? 4. Social networks and influence 5. Social influence and viral cascades 5.1 The connection between social organizations and social pandemics 6. Viral marketing and its impact 6.1 Various models and validation 6.1.1 Different impact models in social networks 6.1.2 Singular impact 6.1.3 Community impact 6.1.4 Influence maximization 7. Case study and applications 8. Summary References 5 - Pragmatic studies of diffusion in social networks 1. Introduction 1.1 Issue: information diffusion 1.1.1 Determinant factors 1.1.1.1 Network connection 1.1.1.2 Signposts 1.1.1.3 Content posters 1.2 Issue: information summarization 1.3 Major contributions 2. Literature survey 2.1 Information diffusion 2.1.1 User influences in OSN 2.1.2 Precise time to post 2.1.3 Prediction popularity of content posts 2.1.3.1 Prediction popularity using content post 2.1.3.2 Dynamic sentiment of new content posts 2.2 Issue: information summarization 2.2.1 Interesting topics 3. Research guidelines 3.1 Explanatory model 3.2 Epidemics model 3.2.1 SI model 3.2.2 SIS model 3.2.3 SIR model 3.3 Influence models 3.3.1 Individual influence 3.3.2 Community influence 3.3.3 Influence maximization 4. Predictive model 4.1 Model 1: independent cascade 4.2 Model 2: linear threshold 4.3 Model 3: game theory 5. Future directions 6. Discussion and conclusion References 6 - Forensic analysis in social networking applications 1. Introduction 1.1 Unparallel opportunities 1.2 Nature of cyber crime 1.3 Addressing issues 1.4 Motivation 1.5 Objectives 2. Background 2.1 Criminal recording 2.2 Social behavioral analysis (SBA) 2.3 Subset of behavioral evidence analysis (S-BEA) 2.3.1 Equivocal forensic analysis 2.3.2 Victimology 2.3.3 Crime scene 2.3.4 Lawbreaker characteristics 2.3.5 Principles of subset of behavioral evidence analysis 3. Digital forensics 4. Investigation models in digital forensic 4.1 Model 1: crime scene investigation 4.2 Model 2: abstract digital forensics 4.3 Model 3: integrated investigation process 4.4 Model 4: hierarchical objective-based (HOB) framework 4.5 Model 5: Cohen's digital forensics 4.6 Model 6: systematic forensic investigation 4.7 Model 7: harmonized forensic investigation 4.8 Model 8: integrated forensic investigation 4.9 Model 9: Mir's forensic model 4.10 Model 10: general limitation 5. Integrating behavioral analysis 5.1 Cyberstalker: forensic methodology 5.2 Roger's behavioral analysis 6. Sexually exploitative child imagery 6.1 Online prevalence 6.2 Characterize the sexual victims 6.3 Characterize the sexual offenders 7. Offender typologies and theories 7.1 Offender motivation 7.2 Offender typologies 7.3 Cyberstalkers 8. Research methodologies 8.1 Research paradigm 8.2 Methodology 8.3 Research strategy 9. Conclusion References 7 - Recommender systems: security threats and mechanisms 1. Introduction 1.1 Motivation 2. Features of recommender systems 3. Common classification of recommender systems 3.1 Content-based approach 3.2 Collaborative filtering (CF) approach 3.3 Hybrid approach 4. Sources of recommender systems 5. Literature review 5.1 Data masking method 5.2 Differential privacy 5.3 Secure multiparty computation 5.4 Homomorphic encryption 6. Quality measures for evaluating recommender systems 7. Challenges in implementing recommender systems 8. Basic scheme 8.1 Centralized scheme 8.2 Distributed scheme 8.3 Framework of securing rating matrix, similarity, and aggregate computations in centralized and distributed schemes 8.3.1 Collaborative recommender model 8.3.1.1 Securing item–item similarity computation 8.3.1.2 Generating recommendations 8.3.1.3 Securing the user–user similarity computation 8.3.2 Content-based recommender model 8.3.3 Trust-aware recommendations 8.3.4 Identifying attack paths 9. Conclusion References 8 - Evolving cloud security technologies for social networks 1. Introduction 1.1 Motivation 1.2 Background 1.3 Privacy protection and data integration 2. Evolution of computing platforms in social networks 2.1 Evolution of cloud services 2.2 Cloud computing paradigm for SNs 2.3 Edge computing and fog computing 3. Access control and security policies in social networks 3.1 Architecture and use case model 3.2 Issues 4. Cloud security technologies 4.1 Cloud computing paradigm 4.2 Edge computing paradigm 4.3 The threat model for SNs 4.4 Privacy and security threats in social networking applications 4.5 Recommendations 5. Manifesting mechanism 5.1 Security modeling 5.2 Access control enforcement for fog/edge computing 6. Conclusion References 9 - Fake news in social media recognition using Modified Long Short-Term Memory network 1. Introduction 2. Literature review 3. Existing fake news detection techniques 3.1 Dataset description 3.2 Preprocessing 3.3 Feature extraction 3.4 MLSTM 3.4.1 Basic operations 3.4.2 Memory cell building blocks 4. Performance analysis 5. Experimentation and results 6. Conclusion and future work Appendix: References 10 - Security aspects and UAVs in Socialized Regions 1. Introduction 2. UAVs: a brief introduction 2.1 Technical challenges 3. UAV using IOT in smart cities 3.1 IOT platforms 3.2 Case study 4. UAV transportation system 4.1 ITS for smart cities 4.2 Applications 4.3 Cyber security and privacies 5. UAV issues in cyber security and public safety 6. UAV in smart cities: Dubai 6.1 Challenges References Index A B C D E F G H I J K L M N O P Q R S T U V W Y Z Back Cover