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Detection of distributed denial of service attacks for IoT-based healthcare systems

Kaur Gaganjot, Gupta Prinima

Computer Assisted Methods in Engineering and Science

2023

Vol. 30, no. 2

167--186

One of the major common assaults in the current Internet of things (IoT) network-based healthcare infrastructures is distributed denial of service (DDoS). The most challenging task in the current environment is to manage the creation of vast multimedia data from the IoT devices, which is difficult to be handled solely through the cloud. As the software defined networking (SDN) is still in its early stages, sampling-oriented measurement techniques used today in the IoT network produce low accuracy, increased memory usage, low attack detection, higher processing and network overheads. The aim of this research is to improve attack detection accuracy by using the DPTCM-KNN approach. The DPTCMKNN technique outperforms support vector machine (SVM), yet it still has to be improved. For healthcare systems, this work develops a unique approach for detecting DDoS assaults on SDN using DPTCM-KNN.

Exact and approximation algorithms for sensor placement against DDoS attacks

Junosza-Szaniawski Konstanty, Nogalski Dariusz, Wójcik Agnieszka

Annals of Computer Science and Information Systems

2020

Vol. 21

295--301

In DDoS attack (Distributed Denial of Service), an attacker gains control of many network users by a virus. Then the controlled users send many requests to a victim, leading to lack of its resources. DDoS attacks are hard to defend because of distributed nature, large scale and various attack techniques. One of possible ways of defense is to place sensors in the network that can detect and stop an unwanted request. However, such sensors are expensive so there is a natural question about a minimum number of sensors and their optimal placement to get the required level of safety. We present two mixed integer models for optimal sensor placement against DDoS attacks. Both models lead to a trade-off between the number of deployed sensors and the volume of uncontrolled flow. Since above placement problems are NP-hard, two efficient heuristics are designed, implemented and compared experimentally with exact linear programming solvers.

Design of a distributed HIDS for IoT backbone components

de O. Kfouri Guilherme, Gonçalves Daniel G. V., Dutra Bruno V., de Alencastro João F., de Caldas Filho Francisco L., e Martins Lucas M. C., Praciano Bruno J. G., de O. Albuquerque Robson, de Sousa Jr Rafael T.

Annals of Computer Science and Information Systems

2019

Vol. 20

81--88

Nowadays DDoS attacks using IoT devices are frequent and extensive. Given that IoT network instances are distributed and deployed over conventional Internet gear, DDoS countermeasures in IoT need to be fully distributed and coordinated all over the components that form each IoT instance. This paper presents a designed and prototyped distributed host-based intrusion detection systems (HIDS) that aims to protect the components of IoT network backbones, comprising conventional switches and routers. In our design, a set of the proposed HIDS executes conventional security verifications, like default username and password, known attacks signatures, monitoring the usage of resources, processes, ports and open connections, while also interacting with a Controller of the HIDS set to allow the coordination of intrusion detection actions relative to DDoS attacks all over the IoT instance. The designed distributed HIDS is evaluated in a controlled environment that, although being a local and isolated network, realistically represents IoT network instances.