In device-to-device (D2D) communications, distributed Denial-of-Service (DDoS) attacks can be quite detrimental because it can result in network structure destruction. Towards this end, the research objective of this paper is to identify and prevent DDoS and Denial-of-Service (DoS) attacks (i.e., SYN, Slowloris) in a D2D communication environment. Specifically, by replicating a real-world scenario, we emulate SLowloris attacks in a D2D communication network and generate a D2D Network-specific Slowloris dataset. This dataset along with the CICDDoS2019 dataset was then used to train our proposed Machine learning (ML) model that aids in the detection and prevention of DDoS attacks (Slowloris and SYN) in the considered D2D framework. The whole process of how to construct an emulation network for D2D communication and test it against a variety of attacks and implementations is also demonstrated in the paper. To quantify the detection accuracy in the context of DDoS and DoS attacks, we use various ML algorithms such as Random Forest, Light GBM, XGBoost, and Ada Boost and study their performance with the aid of extensive emulation. The results collected revealed that both Slowloris and CICDDoS2019 datasets achieve greater accuracy with Random Forest. Consequently, the results compel us to develop a technique for combining the identification of DDoS and DoS attacks in binary classification Random Forests with the binary decision. The proposed technique has been evaluated and compared with other related approaches in the open literature demonstrating significant performance in terms of identification and prevention time, processing and memory resources required, and device battery consumption, without affecting the accuracy of the attack identification. Hence, we advocate that our proposed technique can be extremely beneficial in preventing DDoS and DoS attacks in a D2D communication environment, where its lifetime and capabilities are mainly associated with the resources of the D2D device (i.e., CPU, Memory, and battery life).

S.V. Jansi Rani

Iacovos Ioannou

Prabagarane Nagaradjane

Christophoros Christophorou

Vasos Vassiliou

Sai Charan

Sai Prakash

Niel Parekh

Andreas Pitsillides

Computer Communications

计算机和通信网络是信息社会的关键基础设施，具有很高的社会经济价值，因为它们有助于许多关键服务（从医疗保健到金融和交通）的正确运行。互联网是当今计算机通信基础设施的核心。这已将互联网从用于计算机之间数据传输的强大网络转变为全球性、内容丰富的通信和信息系统，其中内容越来越多地由用户生成，因此，需要下一代网络技术、架构和协议来克服传统互联网的局限性，增加新的能力和服务，未来的互联网应该是无处不在、安全、有弹性、更接近人类的。通信范式。COMPUTER COMMUNICATIONS 是一份经过同行评审的国际期刊，发表高质量的科学文章（理论和实践）和调查论文，涵盖未来计算机通信网络的所有方面（在所有层，除了物理层），关注互联网架构、协议、服务和应用程序的演变。

Computer and communication networks are critical infrastructures in the information society, holding significant socio-economic value as they support the proper functioning of many essential services, including healthcare, finance, and transportation. The Internet serves as the core of today's computer communication infrastructure, having evolved from a powerful network for data transmission between computers into a global, content-rich communication and information system. With an increasing amount of user-generated content, there is a pressing need for next-generation network technologies, architectures, and protocols to overcome the limitations of the traditional Internet and enhance new capabilities and services. The future Internet should be ubiquitous, secure, resilient, and more aligned with human communication paradigms. "Computer Communications" is a peer-reviewed international journal that publishes high-quality scientific articles (both theoretical and practical) and survey papers covering all aspects of future computer communication networks (at all layers except the physical layer), with a focus on the evolution of Internet architectures, protocols, services, and applications.

计算机和通信网络是信息社会的关键基础设施，具有重要的社会经济价值，因为它们支持许多关键服务的正常运行，包括医疗保健、金融和交通等。互联网是当今计算机通信基础设施的核心，已经从一个用于计算机之间数据传输的强大网络，转变为一个全球性的、内容丰富的通信和信息系统。用户生成的内容日益增多，因此需要下一代网络技术、架构和协议，以克服传统互联网的局限性，增强新的能力和服务。未来的互联网应当是无处不在、安全、具有弹性，并更贴近人类的通信范式。《Computer Communications》是一份经过同行评审的国际期刊，发表高质量的科学文章（包括理论和实践）以及调查论文，涵盖未来计算机通信网络的各个方面（除了物理层），重点关注互联网架构、协议、服务和应用程序的演变。

Category	Quartile
计算机科学	3
计算机科学, 计算机信息系统	3
计算机科学, 工程电子与电气	3
计算机科学, 电信学	3

Detection of DDoS attacks in D2D communications using machine learning approach

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