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Natural Disaster Resilience Approach (NDRA) to Online Social Networks

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Abstract

Numerous disasters impact people around the world, including floods, cyclones, tsunamis and so on. Disaster resilience (recovery) is a realtime challenge. The research goal of the proposed Natural Disaster Resilience Approach (NDRA) is to fasten and automate disaster resilience within the affected region. Prioritization for saving lives must be provided to the region most affected. Currently almost all people use the Online Social Networks (OSNs) to share their daily activities. Actually only their friends in OSN can note the photos posted by OSN users in the disaster-affected region and in turn can support the friends in need. Our research goal is to conduct speedier and prioritized disaster resilience processes by directly addressing honest disaster help requests from images posted by OSN users. To achieve the above goal, we suggest an approach known as the Natural Disaster Resilience Approach (NDRA). The NDRA is a three-tiered framework: Tier-1: sybil(malicious) user avoidance engine: prevents fake OSN user profile creation; Tier-2: ‘D’- attributed image classifier: determines the originality of the images posted and Tier-3: sybil user prediction: uses an Advanced Sybil Node Prediction Algorithm (ASYNPA) to check the authenticity of the user and priorities for faster resilience requests. In NDRA we use Advogato dataset with 6541 users and 51,127 edges. Ultimately, the comparison is only made between the proposed ASYNPA tier-3 and the existing VoteTrust algorithm, and the graph is plotted against the False Positive (FP) rate, taking into account the precision and recall metrics. Around 99.84% of the expected sybils were confirmed in ASYNPA, which is 3.49% higher than VoteTrust.

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References

  • Abdelgawad H, Shalaby A, Abdulhai B, Gutub A (2014) Microscopic modeling of large-scale pedestrian-vehicle conflicts in the city of Madinah, Saudi Arabia. J Adv Transp 48(6):507–525. https://doi.org/10.1002/atr.1201

    Article  Google Scholar 

  • Abu-Nimeh S, Chen TM, Alzubi O (2011) Malicious and spam posts in online social networks. In: Published by the IEEE computer society, 2011 IEEE

  • Adewole KS, Anuar NB, Kamsin A, Varathan KD, Razak SA (2017) Malicious accounts: dark of the social networks. J Netw Comput Appl 79:41–67

    Article  Google Scholar 

  • Agrawal H, Kaushal R (2016) Analysis of text mining techniques over public pages of Facebook. In: 6th International conference on advanced computing, 2016 IEEE

  • Ahmed M, Mahmood AN, Hu J (2016) A survey of network anomaly detection techniques. J Netw Comput Appl 60:19–31. https://doi.org/10.1016/j.jnca.2015.11.016

    Article  Google Scholar 

  • Al-Ameen MN, Wright M (2016) iPersea: towards improving the sybil-resilience of social DHT. J Netw Comput Appl 71:1–10. https://doi.org/10.1016/j.jnca.2016.05.014

    Article  Google Scholar 

  • Alexander DE (2014) Social media in disaster risk reduction and crisis management. Sci Eng Ethics 20:717–733

    Article  Google Scholar 

  • Alharthi N, Gutub A (2017) Data visualization to explore improving decision-making within hajj services. Sci Model Res 2(1):9–18. https://doi.org/10.20448/808.2.1.9.18

    Article  Google Scholar 

  • Alsaidi A, Gutub A, Alkhodaidi T (2019) Cybercrime on transportation airline. J Forensic Res 10(4):449

    Google Scholar 

  • Aly S, Gutub A (2018) Intelligent recognition system for identifying items and pilgrims. NED Univ J Res Themat Issue Adv Image Video Process 15(2):17–23

    Google Scholar 

  • Anitha V, Akilandeswari J, Sowmya P (2014) Auto defence mechanism for SYBIL attacks in manets using QABR Protocol. In: 2014 International conference on advances in electronics, computers and communications (ICAECC), 2014 IEEE

  • Chakraborty P, Karform S (2012) Designing trust propagation algorithms based on simple multiplicative strategy for social networks. Procedia Technol 6:534–539. https://doi.org/10.1016/j.protcy.2012.10.064

    Article  Google Scholar 

  • Curtis S, Zafar B, Gutub A, Manocha D (2013) Right of way: asymmetric agent interactions in crowds. Vis Comput Int J Comput Gr 29(12):1277–1292. https://doi.org/10.1007/s00371-012-0769-x

    Article  Google Scholar 

  • Dufty N (2012) Using social media to build community disaster resilience. Austral J Emerg Manag 27(1):40–45

    Google Scholar 

  • Eirinaki M, Louta MD, Varlamis I (2013) A Trust-aware system for personalized user recommendations in social networks. IEEE Trans Syst Man Cybern Syst 44(4):409–421. https://doi.org/10.1109/tsmc

    Article  Google Scholar 

  • Gokula Krishnan S, Karthika S, Bose S (2016) Detection of communities in dynamic social networks. In: Fifth international conference on recent trends in information technology, 2016 IEEE

  • Gong NZ, Frank M, Mittal P (2014) SybilBelief: a semi-supervised learning approach for structure-based Sybil detection. In: IEEE transactions on information forensics and security, 2014 IEEE

  • Gutub A (2015) Exploratory data visualization for smart systems. In: Smart Cities 2015—3rd annual digital grids and smart cities workshop, Burj Rafal Hotel Kempinski, Riyadh, Saudi Arabia. https://doi.org/10.13140/RG.2.1

  • Gutub A, Alharthi N (2016) Improving Hajj and Umrah services utilizing exploratory data visualization techniques. In: Hajj Forum 2016—the 16th scientific Hajj research Forum, Organized by the Custodian of the Two Holy Mosques Institute for Hajj Research, Umm Al-Qura University—King Abdulaziz Historical Hall, Makkah, Saudi Arabia. https://doi.org/10.1437/430

  • Gutub A, Aly S (2018) Trialing a smart face-recognition computer system to recognize lost people visiting the two holy mosques. AJFSFM 1(8):1120–1133. https://doi.org/10.26735/165867

    Article  Google Scholar 

  • Halgin DS, Borgatti SP, Huang Z (2020) Prismatic effects of negative ties. Soc Netw 60:26–33

    Article  Google Scholar 

  • Houston B, Mildred JH, Eun FP, Park H, Goldstein Hode M, Halliwell MR, Turner SE, Rachel M, Shivani D, Jonathan V, McElderry A, Griffith SA (2014) Social media and disasters: a functional framework for social media use in disaster planning, response, and research. Wiley Publications, Oxford. https://doi.org/10.1111/disa.12092

    Book  Google Scholar 

  • Hsieh MY, Huang YM, Chao HC (2007) Adaptive security design with malicious user detection in cluster-based sensor networks. Comput Commun 30:2385–2400

    Article  Google Scholar 

  • Islam R, Walkerden G (2014) How bonding and bridging networks contribute to disaster resilience and recovery on the Bangladeshi coast. Int J Disaster Risk Reduct 10:281–291. https://doi.org/10.1016/j.ijdrr.2014.09.016

    Article  Google Scholar 

  • Jamalia M, Nejat A, Ghosh S, Jin F, Cao G (2019) Social media data and post-disaster recovery. Int J Inf Manage 44:25–37. https://doi.org/10.1016/j.ijinfomgt.2018.09.005

    Article  Google Scholar 

  • Jia JS, Jia J, Hsee CK, Shiv B (2016) The role of hedonic behavior in reducing perceived risk: evidence from post earthquake mobile-app data, vol 28. Sage Publication, Thousand Oaks, pp 23–35

    Google Scholar 

  • Jyothi BS, Dharani pragada J (2009) SyMon: defending large structured P2P systems against sybil attack. In: P2P’09—Sept. 9–11, 2009 IEEE

  • Kaysi I, Alshalalfeh B, Sayour M, Gutub A (2012) Rapid transit service in the unique context of Holy Makkah: assessing the first year of operation during the 2010 pilgrimage season. WIT Trans Built Environ Urban Transp XVIII 128:253–267. https://doi.org/10.2495/ut120231

    Article  Google Scholar 

  • Kaysi I, Alshalalfah B, Shalaby A, Sayegh A, Sayour M, Gutub A (2013) Users’ evaluation of rail systems in mass events: case study in mecca, Saudi Arabia. Transp Res Rec J Transp Res Board Issue 2350(1):111–118. https://doi.org/10.3141/2350-13

    Article  Google Scholar 

  • Kim S, Guy SJ, Hillesland K, Zafar B, Gutub A, Manocha D (2015) Velocity-based modeling of physical interactions in dense crowds. Vis Comput 31:541–555. https://doi.org/10.1007/s00371-014-0946-1

    Article  Google Scholar 

  • Kiskani MK, Azimdoost B, Sadjadpour HR (2016) Effect of social groups on the capacity of wireless networks. In: IEEE transactions on wireless communications, January 2016 IEEE

  • Kokciyan N, Yolum P (2016) PRIGUARD: a semantic approach to detect privacy violations in online social networks. In: IEEE transactions on knowledge and data engineering, 2016 IEEE

  • Marín A, Bodin O, Gelcich S, Crona B (2015) Social capital in post-disaster recovery trajectories: Insights from a longitudinal study of tsunami-impacted small-scale fisher organizations in Chile. Glob Environ Change 35:450–462. https://doi.org/10.1016/j.gloenvcha.2015.09.020

    Article  Google Scholar 

  • Muhammad K, Ahmad J, Lv Z, Bellavista P, Yang P, Baik SW (2019) Efficient deep CNN-based fire detection and localization in video surveillance applications. IEEE Trans Syst Man Cybern Syst 49(7):1419–1434. https://doi.org/10.1109/tsmc.2018.2830099

    Article  Google Scholar 

  • National Disaster Management Plan (NDMP) (2016) A publication of: National Disaster Management Authority Government of India, NDMA Bhawan, New Delhi, May 2016

  • Pham A, Huguenin K, Bilogrevic I, Dacosta I, Hubaux JP (2016) SecureRun: cheat-proof and private summaries for location-based activities. In: Transactions on mobile computing, 2016 IEEE

  • Ramalingam D, Chinnaiah V (2018) Fake profile detection techniques in large-scale online social networks: a comprehensive review. Comput Electr Eng 65:165–177

    Article  Google Scholar 

  • Renuga DR, Hemalatha M (2013) Sybil user identification algorithm using connectivity threshold for secured community mining in social network. In: IEEE international conference on computational intelligence and computing research 2013 IEEE

  • Ries S, Aitenbichler E (2009) Limiting Sybil attacks on bayesian trust models in open SOA environments. In: Symposia and workshops on ubiquitous, autonomic and trusted computing 2009 IEEE

  • Shen H, Liu X (2015) Detecting spammers on twitter based on content and social interaction. In: International conference on network and information systems for computers, 2015 IEEE

  • Shi L, Yu S, Lou W, Hou YT (2013) SybilShield: an agent-aided social network-based Sybil defense among multiple communities. In: Proceedings IEEE INFOCOM 2013 IEEE

  • Toleubay Y, James AP (2019) Getting started with TensorFlow deep learning. Deep learning classifiers with memristive networks. Springer, Berlin, pp 57–67

    Google Scholar 

  • Varda DM, Forgette R, Banks D, Contractor N (2009) Social network methodology in the study of disasters: issues and insights prompted by post-katrina research. Popul Res Policy Rev 28:11–29

    Article  Google Scholar 

  • Wei W, Xu F, Tan CC, Li Q (2013) SybilDefender: A defense mechanism for sybil attacks in large social networks. In: IEEE transactions on parallel and distributed systems, 2013 IEEE

  • Yang Z, Xue J, Yang X, Wang X, Dai Y (2016) VoteTrust: leveraging friend invitation graph to defend against social network sybils. In: IEEE Transactions on dependable and secure computing, vol 13(4), July/August 2016

Download references

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Authors and Affiliations

  1. Department of Computer Science and Engineering, SRM Valliammai Engineering College, Kattankulathur, Chengalpattu, Tamil Nadu, 603203, India

    N. Poornima

  2. Department of Electronics and Communication Engineering, SRM Valliammai Engineering College, Kattankulathur, Chengalpattu, Tamil Nadu, 603203, India

    M. Murugan

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Poornima, N., Murugan, M. Natural Disaster Resilience Approach (NDRA) to Online Social Networks. J Ambient Intell Human Comput 12, 5651–5678 (2021). https://doi.org/10.1007/s12652-020-02644-1

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