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Investigation of Sinkhole Attacks and Network Simulation on 6LoWPAN

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Cryptology and Network Security with Machine Learning (ICCNSML 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 918))

  • 83 Accesses

Abstract

Sinkhole attacks have been the most dangerous threat to security in recent times. The attackers send malicious requests to Domain Name Server (DNS) that causes unavailability of services and redirects the victim to the destination designed by the malicious attacker. The malicious attacker with the help of these compromised devices forms a BOTNET and uses it for malicious purposes like ransomware, extortion, unauthorized access, fraudulent attempts, data theft, financial gains, eavesdropping, repudiation, etc. The attacker node or the sinkhole node was placed at three different locations to observe the change in count of DIO messages. The purpose of this research was to detect that at what locations can attacker gather a large amount of data. It was observed that when the attacker node was placed at the edge and along the communication links, there was a significant increase in the count of DIO messages. This means that at these points, attacker can gather a lot of information.

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Authors and Affiliations

  1. Indira Gandhi Delhi Technical University for Women, Delhi, India

    Shreya Singh & Deepak Kumar Sharma

  2. Mata Sundari College for Women, Delhi, India

    Megha Gupta

Authors
  1. Shreya Singh
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  2. Megha Gupta
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  3. Deepak Kumar Sharma
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Correspondence to Shreya Singh .

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Editors and Affiliations

  1. Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

    Atul Chaturvedi

  2. Department of Mathematics, Indian Institute of Technology Jammu, Jammu, India

    Sartaj Ul Hasan

  3. Applied Statistics Unit, Indian Statistical Institute, Kolkata, India

    Bimal Kumar Roy

  4. Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel

    Boaz Tsaban

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Singh, S., Gupta, M., Sharma, D.K. (2024). Investigation of Sinkhole Attacks and Network Simulation on 6LoWPAN. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_6

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  • DOI: https://doi.org/10.1007/978-981-97-0641-9_6

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