Abstract
Internet of Things (IoT) is a network of interconnected devices embedded with software, sensors and essential electronics that allow us to gather and exchange data between them. Through IoT, it is difficult to guarantee the privacy and protection of the users due to various artifacts linked to the Internet. Denial of Service (DoS) and Distribution Denial of Service (DDoS) are among the main security issues in IoT. DoS is a type of attack where attackers try to prevent access by legitimate users to the service. A DDoS is where multiple systems target a single, DoS attack system. This occurs when several systems overload a target system’s bandwidth or resources, normally at one or more servers. This is because of resource-constrained IoT network characteristics that have become a big victim. The early detection of DoS and DDoS attacks will prevent the resource-constrained devices from becoming a target and early death. This paper focuses on vulnerabilities in IoT such as Distributed Denial of Services (DDoS). Many privacy-conserving mechanisms have been discovered (such as automatic solution learning, and DDoS warning mechanisms). And, related work is under way. The goal of this paper is to present the detection and prevention of DDoS in IoT and privacy issues faced by the IoT environment and current mechanisms for its security.
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References
Singh K, Singh P, Kumar K (2017) Application layer HTTP-GET flood DDoS attacks: research landscape and challenges. Comput Secur 65:344–372
Hasan M, Islam M, Zarif II, Hashem MMA (2019) Internet of things attack and anomaly detection in IoT sensors in IoT sites using machine learning approaches. Internet Things 7:
Bakhtiar FA, Pramukantoro ES, Nihri H (2019) A lightweight IDS based on J48 algorithm for detecting DoS attacks on IoT middleware. In: 2019 IEEE 1st global conference life sciences technology, pp 41–42
Kajwadkar S (2018) A novel algorithm for DoS and DDoS attack detection in internet of things. In: 2018 Conference on information communication and technology, pp 1–4
de Lima Filho FS, Silveira FAF, de Medeiros Brito Junior A, Vargas-Solar G, Silveira LF (2019) Smart detection: an online approach for DoS/DDoS attack detection using machine learning. Secur Commun Networks 2019:1–15
Daud M, Rasiah R, George M, Asirvatham D, Rahman AFA, Halim AA (2018) Denial of service: (DoS) impact on sensors. In: 2018 4th International conference on information management ICIM, pp 270–274
Santhosh Kumar S (2017) An anomaly behavior-based detection and prevention of DoS attack in IoT environment. In: 2017 Ninth international conference advanced computing, pp 287–292
Guo K, Wang D, Zhi H, Lu Y, Jiao Z (2020) A trusted resource-based routing algorithm with entropy estimation in integrated space-terrestrial network. IEEE Access 8:122456–122468
Irum A, Khan MA, Noor A, Shabir B (2020) DDoS detection and prevention in internet of things
Alqahtani H, Sarker IH, Kalim A, Hossain SM, Ikhlaq S, Hossain S (2020) Cyber intrusion detection using machine
Cui Y, Liu Q, Zheng K, Huang X (2018) Evaluation of several denial of service attack methods for IoT system. In: 2018 9th International conference on information technology in medicine and education, pp 794–798
Guleria A, Kalra E, Gupta K (2019) Detection and prevention of DoS attacks on network systems. In: 2019 International conference on machine learning, big data, cloud parallel computing, pp 544–548
Huraj L (2018) IoT measuring of UDP-based distributed reflective DoS attack. In: 2018 IEEE 16th international symposium on intelligent systems and informatics, pp 209–214
Ali U (2018) Open access HADEC : hadoop-based live DDoS detection framework
Behal S, Kumar K, Sachdeva M (2018) D-FACE: an anomaly-based distributed approach for early detection of DDoS attacks and flash events. J Netw Comput Appl 111:49–63
Fox MR (1981) Cover letter PC-24(4)
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Sharma, M., Arora, B. (2021). Detection and Prevention of DoS and DDoS in IoT. In: Singh, P.K., Wierzchoń, S.T., Tanwar, S., Ganzha, M., Rodrigues, J.J.P.C. (eds) Proceedings of Second International Conference on Computing, Communications, and Cyber-Security. Lecture Notes in Networks and Systems, vol 203. Springer, Singapore. https://doi.org/10.1007/978-981-16-0733-2_60
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DOI: https://doi.org/10.1007/978-981-16-0733-2_60
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