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2000
Volume 19, Issue 2
  • ISSN: 2666-2558
  • E-ISSN: 2666-2566

Abstract

Background

In the field of digital forensics, the proliferation of Internet of Things (IoT) devices within intelligent residences has presented both new opportunities and challenges. Every gadget, including smart thermostats, security cameras, lighting controls, and even washing machines or refrigerators is equipped by these installers in the range of gadgets offered by manufacturers.

Methods

This research conducts a comprehensive investigation and classification of contemporary forensic tools designed for IoT devices in smart homes, highlighting their characteristics, methods of data collection, types of target devices, analytical methodologies, practical applications, and capabilities for integration. This generally involves a comparison of different forensic products or solutions and evaluation on various criteria such as cost, supportability, maintainable architecture-designs (integration), speedy acquisition speed/performance effectiveness without compromising quality, ease-of-use, and consistency.

Results

A comparative analysis with detailed tables & radar charts identifying the detailed pros and cons of each tool, our findings help forensic professionals understand when to use them for effective decisions. The results show that XRY and UFED by Cellebrite both scored 5/5 in each criterion, showing the best performance in mobile device forensics. Wireshark and tcpdump also have high rates for the accuracy and reliability criteria, with results of 5/5, and are therefore also highly recommended in the area of analysis of network traffic. Magnet AXIOM and NetworkMiner graded evenly well, with a usability rating of four out of five and an integration mark of 4 out of five, which diversified them for computer and mobile forensics. Splunk and ELK Stack scored topping the scalability category, with each scoring out of five, which further confirmed the analysis of logs well for large data sets. These numerical results further underline that the choice of the tool depends on specific forensic requirements.

Conclusion

The authors examine future IoT forensics in smart homes which highlights the necessity of devices working with each other through a standard and sophisticated analysis to deal with dynamic complexity development within this field.

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2024-12-30
2026-03-02
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References

  1. Buil-GilD. KempS. KuenzelS. CoventryL. ZakharyS. TilleyD. NicholsonJ. The digital harms of smart home devices: A systematic literature review.Comput. Human Behav.202314510777010.1016/j.chb.2023.107770
    [Google Scholar]
  2. JanarthananT. BagheriM. ZargariS. IoT forensics: An overview of the current issues and challenges.Advanced Sciences and Technologies for Security Applications.New York City, United StatesSpringer202122325410.1007/978‑3‑030‑60425‑7_10
    [Google Scholar]
  3. KimS. ParkM. LeeS. KimJ. Smart home forensics—data analysis of IoT devicesElectronics 2020202098121510.3390/electronics9081215
    [Google Scholar]
  4. IqbalA. OlegardJ. GhimireR. JamshirS. ShalaginovA. Smart home forensics: An exploratory study on smart plug forensic analysisProceedings - 2020 IEEE international conference on big data, Big DataAtlanta, GA, USA20202283229010.1109/BigData50022.2020.9378183
    [Google Scholar]
  5. PhilominS. SinghA. IkuesanA. VenterH. Digital forensic readiness framework for smart homesProceedings of the 15th International Conference on Cyber Warfare and Security, ICCWS2020627636
    [Google Scholar]
  6. VolarevicI. TomicM. MilohanicL. Network forensics2022 45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO – Proceedings.Opatija, Croatia20221025103010.23919/MIPRO55190.2022.9803427
    [Google Scholar]
  7. WuT. BreitingerF. NiemannS. IoT network traffic analysis: Opportunities and challenges for forensic investigators?Forensic Sci. Int. Digit. Investig.20213830112310.1016/j.fsidi.2021.301123
    [Google Scholar]
  8. PluskalJ. BreitingerF. RyšavýO. Netfox detective: A novel open-source network forensics analysis tool.Forensic Sci. Int. Digit. Investig.20203530101910.1016/j.fsidi.2020.301019
    [Google Scholar]
  9. RohatgiS. SharmaA. SharmaB. Internet of things mobility forensics.Digital Forensics and Internet of Things: Impact and Challenges, A. Gehlot, R. Singh, J. Singh, N.R. Sharma, Ed.2021738610.1002/9781119769057.ch6
    [Google Scholar]
  10. JonesG.M. WinsterS.G. An insight into digital forensics: History, frameworks, types and toolsCyber Security and Digital Forensics: Challenges and Future TrendsM.M. Ghonge, S. Pramanik, and R. Mangrulkar, Eds. Beverly, MA, USA: Scrivener Publishing; Hoboken, NJ, USA: Wiley202110512510.1002/9781119795667.ch6
    [Google Scholar]
  11. KaushikK. TayalS. BhardwajA. KumarM. Advanced Smart Computing Technologies in Cybersecurity and Forensics.Boca Raton, FL, USA: CRC Press202110.1201/9781003140023
    [Google Scholar]
  12. HoS. GreesonH. KarabiyikU. Smart home forensics: Identifying ddos attack patterns on IoT devicesAvailable: https://commons.erau.edu/adfsl/2022/presentations/6 Accessed: May 27
    [Google Scholar]
  13. BhardwajA. KaushikK. BharanyS. KimS. Forensic analysis and security assessment of IoT camera firmware for smart homes.Egyptian Informatics Journal202324410040910.1016/j.eij.2023.100409
    [Google Scholar]
  14. OmolaraA.E. AlabdulatifA. AbiodunO.I. AlawidaM. AlabdulatifA. AlshouraW.H. ArshadH. The internet of things security: A survey encompassing unexplored areas and new insights.Comput. Secur.202211210249410.1016/j.cose.2021.102494
    [Google Scholar]
  15. StatisticianM. ApplicationsE. RekhaG. SudhaT. A study on iot forensic investigation in the new age of intelligent crimes.Mathematical Statistician and Engineering Applications20227143274328110.17762/MSEA.V71I4.889
    [Google Scholar]
  16. KrishnaR.R. PriyadarshiniA. JhaA.V. AppasaniB. SrinivasuluA. BizonN. State-of-the-art review on IoT threats and attacks: Taxonomy, challenges and solutions.Sustainability20211316946310.3390/su13169463
    [Google Scholar]
  17. PariseG. MohlaD. PariseL. LombardiM. IoT innovations and forensic engineering in the digital age.IEEE Trans. Ind. Appl.20215732098210310.1109/TIA.2021.3057344
    [Google Scholar]
  18. MrdovicS. IoT Forensics.Security of Ubiquitous Computing Systems, G. Avoine, J. Hernandez-Castro, Ed.Springer Cham202121522910.1007/978‑3‑030‑10591‑4_13
    [Google Scholar]
  19. SurangeG. KhatriP. Integrated intelligent IoT forensic framework for data acquisition through open-source tools.Int. J. Inf. Technol.20221463011301810.1007/s41870‑022‑01025‑5
    [Google Scholar]
  20. AkbarM.A. AlsanadA. MahmoodS. AlothaimA. A multicriteria decision making taxonomy of IoT security challenging factors.IEEE Access2021912884112886110.1109/ACCESS.2021.3104527
    [Google Scholar]
  21. KaushikK. Multinomial naive bayesian classifier framework for systematic analysis of smart IoT devices.Sensors20222219731810.3390/s22197318
    [Google Scholar]
  22. BhardwajA. KaushikK. BharanyS. RehmanA.U. HuY-C. EldinE.T. GhamryN.A. IoT: Traffic data flow analysis and modeling experiment for smart IoT devices.Sustainability (Basel)202214211464510.3390/su142114645
    [Google Scholar]
  23. TouqeerH. ZamanS. AminR. HussainM. Al-TurjmanF. BilalM. Smart home security: Challenges, issues and solutions at different IoT layers.J. Supercomput.20217712140531408910.1007/s11227‑021‑03825‑1
    [Google Scholar]
  24. BhardwajA. KaushikK. AlshehriM. MohamedA.A-B. KeshtaI. ISF: Security analysis and assessment of smart home IoT-based firmwareACM Trans. Sens. Netw.202210.1145/3578363
    [Google Scholar]
  25. GrisposG. TursiF. ChooK.K.R. MahoneyW. GlissonW.B. A digital forensics investigation of a smart scale IoT ecosystemProceedings - 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom.Shenyang, China,202171071710.1109/TrustCom53373.2021.00104
    [Google Scholar]
  26. NetworkMiner. "The NSM and network forensics analysis tool." Netresec. [Online].Available: https://www.netresec.com/?page=NetworkMiner. [Accessed: May 27, 2024].
  27. Exterro. "FTK Imager – Forensic data imaging and preview solution." Exterro. [Online].Available: https://www.exterro.com/digital-forensics-software/ftk-imager [Accessed: May 27, 2024].
  28. MSAB. "XRY — Mobile data forensic phone extraction & recovery." MSAB. [Online].Available: https://www.msab.com/product/xry-extract/ [Accessed: May 27, 2024].
  29. Belkasoft. "Belkasoft X Forensic | A reliable end-to-end DFIR solution." Belkasoft. [Online].Available: https://belkasoft.com/x [Accessed: May 27, 2024].
  30. Cellebrite. "Cellebrite UFED | Access and collect mobile device data." Cellebrite. [Online].Available: https://cellebrite.com/en/ufed/ [Accessed: May 27, 2024].
  31. BrownN. August Lock REST APIs (the basics), Medium. [Online].Available: https://nolanbrown.medium.com/august-lock-rest-apis-the-basics-7ec7f31e7874 [Accessed: May 27, 2024].
    [Google Scholar]
  32. Allegion Schlage Home APIAllegion Developer Portal. [Online]. Available: https://developer.allegion.com/en/products/schlage-home/getting-started.html. [Accessed: May 27, 2024].
  33. LogRhythm SIEM security & SOC services | Cloud & self-hostedLogRhythm. [Online]. Available: https://logrhythm.com/ [Accessed: May 27, 2024].
  34. Splunk, "Splunk | The key to enterprise resilienceSplunk. [Online]. Available: https://www.splunk.com/ [Accessed: May 27, 2024].
  35. Elastic, "ELK stack: Elasticsearch, Kibana, Beats & LogstashElastic. [Online]. Available: https://www.elastic.co/elastic-stack/ [Accessed: May 27, 2024].
  36. Graylog, "SIEM, log management & API protectionGraylog. [Online]. Available: https://graylog.org/ [Accessed: May 27, 2024].
  37. Gephi, "Gephi – The open graph viz platformGephi.org. [Online]. Available: https://gephi.org/ [Accessed: May 27, 2024].
  38. Tableau, "Business intelligence and analytics softwareTableau. [Online]. Available: https://www.tableau.com/ [Accessed: May 27, 2024].
  39. Magnet Forensics. Magnet AXIOM | Digital forensic softwareMagnet Forensics. [Online]. Available: https://www.magnetforensics. com/products/magnet-axiom/ [Accessed: May 27, 2024].
  40. AT&T Cybersecurity. Enhance security with OSSIMAT&T Cybersecurity. [Online]. Available: https://cybersecurity.att.com/products/ossim. [Accessed: May 27, 2024].
  41. Altair, "Data analytics and AI platform | Altair RapidMinerAltair. [Online]. Available: https://altair.com/altair-rapidminer [Accessed: May 27, 2024].
  42. KaushikK. BhardwajA. DahiyaS. Smart home iot forensics: Current status, challenges, and future directionsInternational Conference on Advancement in Computation & Computer Technologies (InCACCT)Gharuan, India202371672110.1109/InCACCT57535.2023.10141730
    [Google Scholar]
  43. FarooqM. HassanM. IoT smart homes security challenges and solution.Int. J. Sec. & Networks.202116423524310.1504/IJSN.2021.119395
    [Google Scholar]
  44. AlShaerM. AlShehhiK. AbdullaS. The internet of things (IoT) forensic investigation process.J. Inf. Sec. Cybercrimes Res.20236215016110.26735/DBEU2801
    [Google Scholar]
  45. KhodayarsereshtE. MajumdarS. Digital forensics for emerging technologies: Present and futureCyber Security and Digital Forensics: Challenges and Future TrendsM.M. Ghonge, S. Pramanik, and R. Mangrulkar, Eds. Hoboken, NJ, USA: Wiley (World Scientific Series in Digital Forensics & Cybersecurity)202311110.1142/9789811273209_0001
    [Google Scholar]
  46. BhardwajA. KaushikK. BharanyS. ElnaggarM.F. MossadM.I. KamelS. Comparison of IoT communication protocols using anomaly detection with security assessments of smart devices.Processes (Basel)20221010195210.3390/pr10101952
    [Google Scholar]
  47. HuangB. ChakiD. BouguettayaA. LamK-Y. A survey on conflict detection in IoT-based smart homes.ACM Comput. Surv.202456514010.1145/3629517
    [Google Scholar]
  48. PiaseckiS. UrquhartL. McAuleyP.D. Defence against the dark artefacts: Smart home cybercrimes and cybersecurity standards.Comput. Law Secur. Rep.20214210554210.1016/j.clsr.2021.105542
    [Google Scholar]
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