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Security, Privacy and Attack in Next Generation Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 June 2023) | Viewed by 5729

Special Issue Editors


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Guest Editor
Department of Mobile Networks and Services, Institute Mines-Telecom/Telecom Sud Paris, 9 rue Charles Fourier, CEDEX, 91011 EVRY, France
Interests: network protocols; network monitoring; network security; cybersecurity; Internet of Things; formal modelling and testing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Montimage EURL, 39 rue Bobillot, 75013 Paris, France
Interests: cybersecurity; penetration testing

Special Issue Information

Dear Colleagues,

Nowadays, next-generation networks (NGN) play an important role in the telecommunication sector, having a colossal importance for future research. NGN communication is ameliorating the world’s lives by providing round-the-clock connectivity together with a high data transfer, and includes a number of promising architectures such as the Internet of Things, personal wireless networks (body area wireless sensor networks, as well as wireless sensor and actuator networks), wireless mesh networks, next-generation internet, cloud computing and virtualized networks, 5G/6G network, and machine-to-machine networks. The NGN communication must be secure and preserve the privacy of its users, requiring innovative methods to address the continuous and emerging security threats.

This Special Issue offers researchers, academics, and industries an opportunity to debate the different issues related to security and privacy in next-generation networks, contributing to relevant theoretical and practical solutions, and the exploration of areas related to the theory, applications, development, experiences, and evaluation studies.

Topics consist of all aspects related to security and privacy issues for next-generation networks, including, but not limited to:

  • Security and privacy models;
  • Risk models;
  • Vulnerability assessment;
  • Mobile identity management;
  • Authentication and access policies;
  • Privacy-aware network solutions and architectures;
  • Security and privacy issues for the Internet of Things;
  • Security and privacy issues in wireless networks and 5G/6G mobile networks;
  • Security management of machine-to-machine networks;
  • Forensics analysis;
  • Malwares and botnets;
  • Cyber threat intelligence;
  • Intrusion and fraud detection;
  • Socio-economic issues;
  • Application to industrial contexts.

Prof. Dr. Ana Rosa Cavalli
Dr. Wissam Mallouli
Guest Editors

Manuscript Submission Information

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Keywords

  • NGN network security
  • NGN network privacy
  • IoT network
  • 5G/6G networks
  • modelling
  • testing
  • detection
  • reaction
  • architectures
  • tools
  • methodologies
  • experimentations

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Published Papers (2 papers)

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Research

18 pages, 3011 KiB  
Article
Performance Evaluation and Cyberattack Mitigation in a Blockchain-Enabled Peer-to-Peer Energy Trading Framework
by Nihar Ranjan Pradhan, Akhilendra Pratap Singh, S. V. Sudha, K Hemanth Kumar Reddy and Diptendu Sinha Roy
Sensors 2023, 23(2), 670; https://doi.org/10.3390/s23020670 - 6 Jan 2023
Cited by 6 | Viewed by 2284
Abstract
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, [...] Read more.
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, leaves traditional security models vulnerable and paves the path for blockchain, a distributed ledger technology (DLT), with its decentralized, open, and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, most of the prototype resilience regarding cybersecurity attack, performance and scalability of transaction broadcasting, and its direct impact on overall performances and attacks are required to be supported, which becomes a performance bottleneck with existing blockchain solutions such as Hyperledger, Ethereum, and so on. In this paper, we design a novel permissioned Corda framework for P2P energy trading peers that not only mitigates a new class of cyberattacks, i.e., delay trading (or discard), but also disseminates the transactions in a optimized propagation time, resulting in a fair transaction distribution. Sharing transactions in a permissioned R3 Corda blockchain framework is handled by the Advanced Message Queuing Protocol (AMQP) and transport layer security (TLS). The unique contribution of this paper lies in the use of an optimized CPU and JVM heap memory scenario analysis with P2P metric in addition to a far more realistic multihosted testbed for the performance analysis. The average latencies measured are 22 ms and 51 ms for sending and receiving messages. We compare the throughput by varying different types of flow such as energy request, request + pay, transfer, multiple notary, sender, receiver, and single notary. In the proposed framework, request is an energy asset that is based on payment state and contract in the P2P energy trading module, so in request flow, only one node with no notary appears on the vault of the node.Energy request + pay flow interaction deals with two nodes, such as producer and consumer, to deal with request and transfer of asset ownership with the help of a notary. Request + repeated pay flow request, on node A and repeatedly transfers a fraction of energy asset state to another node, B, through a notary. Full article
(This article belongs to the Special Issue Security, Privacy and Attack in Next Generation Networks)
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20 pages, 934 KiB  
Article
RAPT: A Robust Attack Path Tracing Algorithm to Mitigate SYN-Flood DDoS Cyberattacks
by Zakwan AlArnaout, Nour Mostafa, Samer Alabed, Wael Hosny Fouad Aly and Ahmed Shdefat
Sensors 2023, 23(1), 102; https://doi.org/10.3390/s23010102 - 22 Dec 2022
Cited by 7 | Viewed by 2696
Abstract
In the recent past, Distributed Denial of Service (DDoS) attacks have become more abundant and present one of the most serious security threats. In a DDoS attack, the attacker controls a botnet of daemons residing in vulnerable hosts that send a significant amount [...] Read more.
In the recent past, Distributed Denial of Service (DDoS) attacks have become more abundant and present one of the most serious security threats. In a DDoS attack, the attacker controls a botnet of daemons residing in vulnerable hosts that send a significant amount of traffic to flood the victim or the network infrastructure. In this paper, a common type of DDoS attacks known as “TCP SYN-Flood” is studied. This type of attack uses spoofed Internet Protocol (IP) addresses for SYN packets by exploiting the weakness in Transmission Control Protocol (TCP) 3-Way handshake used by the TCP/IP suite of protocols, which make the web servers unreachable for legitimate users or even worse, it might lead to server crash. In this paper, a resilient, efficient, lightweight, and robust IP traceback algorithm is proposed using an IP tracing packet for each attack path. The proposed algorithm suggests that edge routers—where the attack starts from—observe the traffic pattern passing through, and if the observed traffic carries the signature of TCP SYN-Flood DDoS attack and a high percentage of it is destined to a particular web server(s), it starts the tracing process by generating an IP trace packet, which accompanies the attack path recording the routers’ IP addresses on the path between the attacker/daemon and the victim, which can extract the path and react properly upon receiving it by discarding any SYN packets originating from that attacker/daemon. To our knowledge, this is the first research that efficiently traces these kinds of attacks while they are running. The proposed solution has low computation and message overhead, efficient detection and tracing time, and converges in near optimal time. The results are validated using extensive simulation runs. Full article
(This article belongs to the Special Issue Security, Privacy and Attack in Next Generation Networks)
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