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2000
Volume 18, Issue 6
  • ISSN: 2666-2558
  • E-ISSN: 2666-2566

Abstract

Background

The rapid development of wireless communications and mobile computation has given rise to the novel Internet of Things (IoT) systems, which is causing considerable research attention and industrial development. However, the lack of synchronization between the timers of IoT devices compromises the network's security.

Aim

The purpose of this patent application is to present a technique for synchronizing the timepieces of IoT gadgets and establishing a secure channel for the transmission of data from source to destination.

Objective

This study proposes a Synchronization Selection Method (SSM) for IoT systems to enhance network security and reduce packet loss.

Methods

The method utilizes time-lay synchronization and RSA algorithm-based secure channel establishment. Time lay is a technique that was developed for IoT devices to achieve efficient clock synchronization of sensor nodes. Before synchronizing the sensor nodes' timings, the cluster leaders initiate the process. Utilizing a finite number of nodes, the proposed method was executed in MATLAB.

Results

Time-lay synchronization involves all network nodes synchronizing their clocks with a third-party clock. In the context of time-lay synchronization, the term “third-party clock” refers to a single specific point that contains the time signal that all nodes in the network use as a reference. This third-party clock is outside of the network nodes and acts as the standard for the precise and synchronized time within the network. Therefore, it can be deduced that each of the techniques possesses its advantages and disadvantages. Each of the synchronization techniques has the potential to significantly benefit the IoT by offering smart clock synchronization that is more secure. Experimental results demonstrate that the proposed method improves throughput and reduces packet loss compared to existing techniques.

Conclusion

The potential of this patent is highly significant for solving the synchronization problem of IoT devices and enhancing network security with decreased network packet loss.

Other

The SSM would be assessed using the parameters of packet loss and throughput.

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References

  1. FevgasA. TsompanopoulouP. BozanisP. iMuse Mobile Tour: A personalized multimedia museum guide opens to groups.2011 IEEE Symposium on Computers and Communications (ISCC), Kerkyra, Greece, 28 June 2011 - 01 July 2011, pp. 971-975.10.1109/ISCC.2011.5983968
     [Google Scholar]
  2. KandaA. AraiM. SuzukiR. KobayashiY. KunoY. Recognizing groups of visitors for a robot museum guide tour.2014 7th International Conference on Human System Interactions (HSI), Costa da Caparica, Portugal, 16-18 June 2014, pp. 123-128.10.1109/HSI.2014.6860460
     [Google Scholar]
  3. KhangA. MisraA. GuptaS.K. ShahV. AI-Aided IoT Technologies and Applications for Smart Business and Production.CRC Press202310.1201/9781003392224
     [Google Scholar]
  4. MoudgilV. HewageK. HussainS.A. SadiqR. Integration of IoT in building energy infrastructure: A critical review on challenges and solutions.Renew. Sustain. Energy Rev.202317411312110.1016/j.rser.2022.113121
     [Google Scholar]
  5. LathaN.R. GopinathM.P. Analysis of IoT applications in highly precise agriculture farming.Recent Pat. Eng.2025192111
     [Google Scholar]
  6. GajendrasinhN.M. Knowledge representation of sensor dataset with IoT collaboration of semantic web and IoT: Storage of temperature and humidity details.Recent Pat. Eng.202519218
     [Google Scholar]
  7. LiC. WangJ. WangS. ZhangY. A review of IoT applications in healthcare.Neurocomputing2023127017
     [Google Scholar]
  8. JungJ. DaiJ. LiuB. WuQ. Artificial intelligence in fracture detection with different image modalities and data types: A systematic review and meta-analysis.PLOS Digital Health202431e000043810.1371/journal.pdig.000043838289965
     [Google Scholar]
  9. DaiJ. LatifiS. A deep learning framework for prediction of the mechanism of action.Int. J. Comput. Appl.2021183121710.5120/ijca2021921383
     [Google Scholar]
  10. DineshA. AvinashK. ManpreetS. Research on internet of medical things: Systematic review, research trends and challenges.Recent Adv. Comput. Sci. Commun.2024176111
     [Google Scholar]
  11. RameshB. KuruvaL. A comprehensive study of deep learning techniques to predict dissimilar diseases in diabetes mellitus using IoT.Recent Adv. Comput. Sci. Commun.2024174118
     [Google Scholar]
  12. RamyaT. GopinathM.P. IoT based predictive modeling techniques for cancer detection in healthcare systems.Recent Pat. Eng.2025192113
     [Google Scholar]
  13. OmarA.M. AhlamM.F. Edge computing towards smart applications: A survey.Recent Adv. Comput. Sci. Commun.2023161118
     [Google Scholar]
  14. SunitaG. SakarG. Energy efficiency in iot based on sensor node deployment pattern.Recent Adv. Comput. Sci. Commun.202215615
     [Google Scholar]
  15. AkulN. PradyotK. AbhishekG. AmitT. IoT-based smart pill reminding system.Recent Adv. Comput. Sci. Commun.202417217
     [Google Scholar]
  16. DaiJ. A novel medical assistance system based on data mining.2014 IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA), , Ottawa, ON, Canada, 29-30 September 2014, pp. 264-266.10.1109/WARTIA.2014.6976247
     [Google Scholar]
  17. YuN. HanQ. Context-aware community: Integrating contexts with contacts for proximity-based mobile social networking.2013 IEEE International Conference on Distributed Computing in Sensor Systems, Cambridge, MA, USA, 20-23 May 2013, pp. 141-148.10.1109/DCOSS.2013.16
     [Google Scholar]
  18. AlliouiH. MourdiY. Exploring the full potentials of IoT for better financial growth and stability: A comprehensive survey.Sensors20232319801510.3390/s2319801537836845
     [Google Scholar]
  19. YiğitlerH. BadihiB. JänttiR. Overview of time synchronization for iot deployments: Clock discipline algorithms and protocols.Sensors202020205928
     [Google Scholar]
  20. GuoB. ZhangD. WangZ. YuZ. ZhouX. Opportunistic IoT: Exploring the harmonious interaction between human and the internet of things.J. Netw. Comput. Appl.20133661531153910.1016/j.jnca.2012.12.028
     [Google Scholar]
  21. LinH-T. Applying location based services and social network services onto tour recording.2012 Ninth International Conference on Computer Science and Software Engineering (JCSSE), , Bangkok, Thailand, 30 May 2012 - 01 June 2012, pp. 197-200.
     [Google Scholar]
  22. GuoB. YuZ. ChenL. ZhouX. MaX. MobiGroup: Enabling lifecycle support to social activity organization and suggestion with mobile crowd sensing. IEEE Trans.IEEE Trans. Hum. Mach. Syst.201646339040210.1109/THMS.2015.2503290
     [Google Scholar]
  23. HuangC.M. LeeC.H. LaiH.Y. Energy-aware group LBS using D2D offloading and M2M-based mobile proxy handoff mechanisms over the mobile converged networks.IEEE Trans. Emerg. Top. Comput.20164452854010.1109/TETC.2015.2417674
     [Google Scholar]
  24. NamiotD. SneppeM.S. Social streams based on network proximity.IJSSBC20133423424210.1504/IJSSC.2013.058375
     [Google Scholar]
  25. JishaS. PhilipM. Rfid based security platform for internet of things in health care environment.2016 Online International Conference on Green Engineering and Technologies (IC-GET), Coimbatore, India, 19-19 November 2016, pp. 1-3.10.1109/GET.2016.7916693
     [Google Scholar]
  26. SándorH. Sebestyén-PálG. Optimal security design in the internet of things.2017 5th International Symposium on Digital Forensic and Security (ISDFS), Tirgu Mures, Romania, 26-28 April 2017, pp. 1-6.10.1109/ISDFS.2017.7916496
     [Google Scholar]
  27. ZhongZ. PengJ. HuangK. ZhongZ. Analysis on physical-layer security for Internet of Things in ultra dense heterogeneous networks.2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Chengdu, China, 15-18 December 2016, pp. 39-43.10.1109/iThings‑GreenCom‑CPSCom‑SmartData.2016.34
     [Google Scholar]
  28. MukhopadhyayD. PUFs as promising tools for security in internet of things.IEEE Des. Test201633310311510.1109/MDAT.2016.2544845
     [Google Scholar]
  29. SundaramB.V. RamnathM. PrasanthM. SundaramV. Encryption and hash based security in Internet of Things.2015 3rd International Conference on Signal Processing, Communication and Networking (ICSCN), Chennai, India, 26-28 March 2015, pp. 1-6.
     [Google Scholar]
  30. PetrovV. EdelevS. KomarM. KoucheryavyY. Towards the era of wireless keys: How the IoT can change authentication paradigm.2014 IEEE World Forum on Internet of Things (WF-IoT), Seoul, Korea (South), 06-08 March 2014, pp. 51-56.
     [Google Scholar]
  31. RanjanA.K. SomaniG. Access control and authentication in the internet of things environment.Connect. Fram. Smart Devices Internet Things from a Distrib. Comput. Perspect.201628330510.1007/978‑3‑319‑33124‑9_12
     [Google Scholar]
  32. TalwanaJ.C. HuaH.J. Smart world of Internet of Things (IoT) and its security concerns.2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Chengdu, China, 15-18 December 2016, pp. 240-245.
     [Google Scholar]
  33. Al-FuqahaA. GuizaniM. MohammadiM. AledhariM. AyyashM. Internet of things: A survey on enabling technologies, protocols, and applications.IEEE Commun. Surv. Tutor.20151742347237610.1109/COMST.2015.2444095
     [Google Scholar]
  34. MahapatraC. ShengZ. LeungV.C.M. Energy-efficient and distributed data-aware clustering protocol for the Internet-of-Things.2016 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Vancouver, BC, Canada, 15-18 May 2016, pp. 1-5.10.1109/CCECE.2016.7726709
     [Google Scholar]
  35. YunJ. AhnI.Y. SungN.M. KimJ. A device software platform for consumer electronics based on the internet of things.IEEE Trans. Consum. Electron.201561456457110.1109/TCE.2015.7389813
     [Google Scholar]
  36. NovoO. BeijarN. OcakM. KjällmanJ. KomuM. KauppinenT. Capillary networks-bridging the cellular and IoT worlds.2015 IEEE 2nd World Forum on Internet of Things (WF-IoT), Milan, Italy, 14-16 December 2015, pp. 571-578.10.1109/WF‑IoT.2015.7389117
     [Google Scholar]
  37. AtzoriL. GubbiJ. BuyyaR. MarusicS. PalaniswamiM. Internet of Things (IoT): A vision, architectural elements, and future direction.Futur. Gener Comput Syst2013
     [Google Scholar]
  38. SuoH. WanJ. ZouC. LiuJ. Security in the internet of things: A review.2012 International Conference on Computer Science and Electronics Engineering, Hangzhou, China, 23-25 March 2012, pp. 648-651.
     [Google Scholar]
  39. GiulianoR. MazzengaF. NeriA. VegniA.M. VallettaD. Security implementation in heterogeneous networks with long delay channel.2012 IEEE First AESS European Conference on Satellite Telecommunications (ESTEL), Rome, Italy, 02-05 October 2012, pp. 1-6.10.1109/ESTEL.2012.6400176
     [Google Scholar]
  40. SicariS. RizzardiA. GriecoL.A. Coen-PorisiniA. Security, privacy and trust in Internet of Things: The road ahead.Comput. Netw.20157614616410.1016/j.comnet.2014.11.008
     [Google Scholar]
  41. MohsinM. AnwarZ. Where to kill the cyber kill-chain: An ontology-driven framework for iot security analytics.2016 International Conference on Frontiers of Information Technology (FIT), Islamabad, Pakistan, 2016, pp. 23-28.10.1109/FIT.2016.013
     [Google Scholar]
  42. KodaliR.K. JainV. BoseS. BoppanaL. IoT based smart security and home automation system.2016 International Conference on Computing, Communication and Automation (ICCCA), Greater Noida, India, 29-30 April 2016, pp. 1286-1289.10.1109/CCAA.2016.7813916
     [Google Scholar]
  43. NasrI. AtallahL.N. CherifS. GellerB. Time synchronization in IoT networks: Case of a wireless body area network.2016 International Symposium on Signal, Image, Video and Communications (ISIVC), Tunis, Tunisia, 21-23 November 2016, pp. 297-301.10.1109/ISIVC.2016.7894004
     [Google Scholar]
  44. GuoZ. KarimianN. TehranipoorM.M. ForteD. Hardware security meets biometrics for the age of IoT.2016 IEEE International Symposium on Circuits and Systems (ISCAS), Montreal, QC, Canada, 22-25 May 2016, pp. 1318-1321.10.1109/ISCAS.2016.7527491
     [Google Scholar]
  45. AbelsT. KhannaR. MidkiffK. Future proof IoT: Composable semantics, security, QoS and reliability.2017 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), Phoenix, AZ, USA, 15-18 January 2017, pp. 1-4.
     [Google Scholar]
  46. GiulianoR. MazzengaF. NeriA. VegniA.M. Security access protocols in IoT capillary networks.IEEE Internet Things J.20174364565710.1109/JIOT.2016.2624824
     [Google Scholar]
  47. SasiT. LashkariA.H. LuR. XiongP. IqbalS. A comprehensive survey on iot attacks: Taxonomy, detection mechanisms and challenges.J. Inf. Intell.2023
     [Google Scholar]
  48. AbdalrdhaZ.K. AL-QinaniI.H. AbbasF.N. Subject review: Key generation in different cryptography algorithm.Int. J. Sci. Res. Sci. Eng. Technol.2019623024010.32628/IJSRSET196550
     [Google Scholar]
  49. WhitmanM.E. MattordH.J. Principles of information security.MAThomson Course Technology Boston2009
     [Google Scholar]
  50. GörmüşS. AydınH. UlutaşG. Security for the internet of things: A survey of existing mechanisms, protocols and open research issues.J. Fac. Eng. Archit. Gazi Univ.20183312471272
     [Google Scholar]
  51. WeberR.H. Internet of Things – New security and privacy challenges.Comput. Law Secur. Rep.2010261233010.1016/j.clsr.2009.11.008
     [Google Scholar]
  52. WortmanP.A. TehranipoorF. KarimianN. ChandyJ.A. Proposing a modeling framework for minimizing security vulnerabilities in IoT systems in the healthcare domain.2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Orlando, FL, USA, 16-19 February 2017, pp. 185-188.10.1109/BHI.2017.7897236
     [Google Scholar]
  53. KharchenkoV. KolisnykM. PiskachovaI. BardisN. Reliability and security issues for IoT-based smart business center: Architecture and Markov model.2016 Third International Conference on Mathematics and Computers in Sciences and in Industry (MCSI), Chania, Greece, 27-29 August 2016, pp. 313-318.10.1109/MCSI.2016.064
     [Google Scholar]
  54. TekeogluA. TosunA.Ş. A testbed for security and privacy analysis of IoT devices.2016 IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), Brasilia, Brazil, 10-13 October 2016, pp. 343-348.10.1109/MASS.2016.051
     [Google Scholar]
  55. GiorgiG. NarduzziC. Configurable clock service for time-aware IoT applications.2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Turin, Italy, 22-25 May 2017, pp. 1-6.10.1109/I2MTC.2017.7969751
     [Google Scholar]
  56. IsmailS. DawoudD.W. RezaH. Securing wireless sensor networks using machine learning and blockchain: A review.Future Internet202315620010.3390/fi15060200
     [Google Scholar]
  57. KhalafO.I. AbdulsahibG.M. Optimized dynamic storage of data (ODSD) in IoT based on blockchain for wireless sensor networks.Peer-to-Peer Netw. Appl.20211452858287310.1007/s12083‑021‑01115‑4
     [Google Scholar]
  58. NurlanZ. ZhukabayevaT. OthmanM. AdamovaA. ZhakiyevN. Wireless sensor network as a mesh: Vision and challenges.IEEE Access202210466710.1109/ACCESS.2021.3137341
     [Google Scholar]
  59. RamasamyL.K. Blockchain-based wireless sensor networks for malicious node detection: A survey.IEEE Access2021912876512878510.1109/ACCESS.2021.3111923
     [Google Scholar]
  60. GaurV. KumarR. Analysis of machine learning classifiers for early detection of DDoS attacks on IoT devices.Arab. J. Sci. Eng.20224721353137410.1007/s13369‑021‑05947‑3
     [Google Scholar]
  61. SarhanM. LayeghyS. PortmannM. Feature analysis for machine learning-based iot intrusion detection.arXiv Preprint2021
     [Google Scholar]
  62. DiwanT.D. ChoubeyS. HotaH.S. GoyalS.B. JamalS.S. ShuklaP.K. TiwariB. Feature entropy estimation (FEE) for malicious IoT traffic and detection using machine learning.Mob. Inf. Syst.2021202111310.1155/2021/8091363
     [Google Scholar]
  63. Galeano-BrajonesJ. Carmona-MurilloJ. Valenzuela-ValdésJ.F. Luna-ValeroF. Detection and mitigation of DoS and DDoS attacks in IoT-based stateful SDN: An experimental approach.Sensors202020381610.3390/s2003081632028711
     [Google Scholar]
  64. PriyadarshiniI. MohantyP. AlkhayyatA. SharmaR. KumarS. SDN and application layer DDoS attacks detection in IoT devices by attention‐based Bi‐LSTM‐CNN.Trans. Emerg. Telecommun. Technol.20233411e475810.1002/ett.4758
     [Google Scholar]
  65. DuR. LiS. Type classification and identification of IoT devices by using traffic characteristics.Wirel. Netw.202411710.1007/s11276‑024‑03736‑y
     [Google Scholar]
  66. TalebkhahM. SaliA. MarjaniM. GordanM. HashimS.J. RokhaniF.Z. IoT and big data applications in smart cities: Recent advances, challenges, and critical issues.IEEE Access20219554655548410.1109/ACCESS.2021.3070905
     [Google Scholar]
  67. FadiA-T. DeebakB.D. Seamless authentication: For IoT-big data technologies in smart industrial application systems.IEEE Trans. Industr. Inform.20201729192927
     [Google Scholar]
  68. NižetićS. ŠolićP. López-de-Ipiña González-de-ArtazaD. PatronoL. Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future.J. Clean. Prod.202027412287710.1016/j.jclepro.2020.12287732834567
     [Google Scholar]
  69. UmairM. CheemaM.A. CheemaO. LiH. LuH. Impact of COVID-19 on IoT adoption in healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT.Sensors20212111383810.3390/s2111383834206120
     [Google Scholar]
  70. RathiV.K. RajputN.K. MishraS. GroverB.A. TiwariP. JaiswalA.K. HossainM.S. An edge AI-enabled IoT healthcare monitoring system for smart cities.Comput. Electr. Eng.20219610752410.1016/j.compeleceng.2021.107524
     [Google Scholar]
  71. KumaranG.J. LoguK. A cloud based secured fully anonymous HMAC encryption algorithm in comparison with diffie-hellman algorithm for improved key.AIP Conf. Proc.20242729030002 10.1063/5.0180771
     [Google Scholar]
  72. VermaR. VermaR. AnandA. Securing the key of improved playfair cipher using the diffie–hellman algorithm.Advances in Soft Computing Applications.River Publishers202312113610.1201/9781003425885‑7
     [Google Scholar]
  73. RoutisG. KatsourisG. RoussakiI. Cryptography-based location privacy protection in the Internet of Vehicles.J. Ambient Intell. Humaniz. Comput.20241583119313910.1007/s12652‑024‑04752‑8
     [Google Scholar]
  74. AhmadI. RodriguezF. KumarT. SuomalainenJ. JagatheesaperumalS.K. WalterS. AsgharM.Z. LiG. PapakonstantinouN. YlianttilaM. HuuskoJ. SauterT. HarjulaE. Communications security in industry X: A Sulrvey.IEEE Open J. Commun. Soc.20245982102510.1109/OJCOMS.2024.3356076
     [Google Scholar]
  75. VuoriT. A methodology for assessing cyber security in Zigbee-based IoT., Master of Science in Technology Thesis, Department of Computing, Faculty of Technology, University of Turku, Turku, Finland. June 2024 https://urn.fi/URN:NBN:fi-fe2024061251326
    [Google Scholar]
/content/journals/rascs/10.2174/0126662558317378240905143354
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Development of Synchronization Selection Method in IoT with Secure Channel Bidirectional Communication
Recent Advances in Computer Science and Communications 18, E26662558317378 (2025); https://doi.org/10.2174/0126662558317378240905143354
/content/journals/rascs/10.2174/0126662558317378240905143354
/content/journals/rascs/10.2174/0126662558317378240905143354
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  • Article Type:     Research Article
Keyword(s): artificial intelligence; bidirectional communication; information technology; IoT; secure channel; wireless communications

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