Now showing 1 - 7 of 7
  • Publication
    6G Security Challenges and Potential Solutions
    Although the fifth generation wireless networks are yet to be fully investigated, the vision and key elements of the 6th generation (6G) ecosystem have already come into discussion. In order to contribute to these efforts and delineate the security and privacy aspects of 6G networks, we survey how security may impact the envisioned 6G wireless systems with the possible challenges and potential solutions. Especially, we discuss the security and privacy challenges that may emerge with the 6G requirements, novel network architecture, applications and enabling technologies including distributed ledger technologies, physical layer security, distributed artificial intelligence (AI)/ machine learning (ML), Visible Light Communication (VLC), THz bands, and quantum communication
    Scopus© Citations 63  20
  • Publication
    Enabling End-to-End Secure Connectivity for Low-Power IoT Devices with UAVs
    The proliferation of the Internet of Things (IoT) technologies have strengthen the self-monitoring and autonomous characteristics of the sensor networks deployed in numerous application areas. The recent developments of the edge computing paradigms have also enabled on-site processing and managing the capabilities of sensor networks. In this paper, we introduce a system model that enables end-to-end secure connectivity between low-power IoT devices and UAVs, that helps to manage the data processing tasks of heterogeneous wireless sensor networks. The performance of proposed solution is analyzed by using simulation results. Moreover, in order to demonstrate the practical usability of the proposed solution, the prototype implementation is presented using commercial off-the-shelf devices.
    Scopus© Citations 11  350
  • Publication
    ESSMAR: Edge Supportive Secure Mobile Augmented Reality Architecture for Healthcare
    The recent advances in mobile devices and wireless communication sector transformed Mobile Augmented Reality (MAR) from science fiction to reality. Among the other MAR use cases, the incorporation of this MAR technology in the healthcare sector can elevate the quality of diagnosis and treatment for the patients. However, due to the highly sensitive nature of the data available in this process, it is also highly vulnerable to all types of security threats. In this paper, an edge-based secure architecture is presented for a MAR healthcare application. Based on the ESSMAR architecture, a secure key management scheme is proposed for both the registration and authentication phases. Then the security of the proposed scheme is validated using formal and informal verification methods.
    Scopus© Citations 2  321
  • Publication
    Micro-Operator driven Local 5G Network Architecture for Industrial Internet
    In addition to the high degree of flexibility and customization required by different vertical sectors, 5G calls for a network architecture that ensures ultra-responsive and ultra-reliable communication links. The novel concept called micro-operator (uO) enables a versatile set of stakeholders to operate local 5G networks within their premises with a guaranteed quality and reliability to complement mobile network operators' (MNOs) offerings. In this paper, we propose a descriptive architecture for emerging 5G uOs which provides user specific and location specific services in a spatially confined environment. The architecture is discussed in terms of network functions and the operational units which entail the core and radio access networks in a smart factory environment which supports industry 4.0 standards. Moreover, in order to realize the conceptual design, we provide simulation results for the latency measurements of the proposed uO architecture with respect to an augmented reality use case in industrial internet. Thereby we discuss the benefits of having uO driven local 5G networks for specialized user requirements, rather than continuing with the conventional approach where only MNOs can deploy cellular networks.
    Scopus© Citations 27  407
  • Publication
    Robust and Resilient Federated Learning for Securing Future Networks
    Machine Learning (ML) and Artificial Intelligence (AI) techniques are widely adopted in the telecommunication industry, especially to automate beyond 5G networks. Federated Learning (FL) recently emerged as a distributed ML approach that enables localized model training to keep data decentralized to ensure data privacy. In this paper, we identify the applicabil- ity of FL for securing future networks and its limitations due to the vulnerability to poisoning attacks. First, we investigate the shortcomings of state-of-the-art security algorithms for FL and perform an attack to circumvent FoolsGold algorithm, which is known as one of the most promising defense techniques currently available. The attack is launched with the addition of intelligent noise at the poisonous model updates. Then we propose a more sophisticated defense strategy, a threshold-based clustering mechanism to complement FoolsGold. Moreover, we provide a comprehensive analysis of the impact of the attack scenario and the performance of the defense mechanism.
    Scopus© Citations 1  189
  • Publication
    How DoS attacks can be mounted on Network Slice Broker and can they be mitigated using blockchain?
    Several recent works talk about the potential use of network slice brokering mechanism to facilitate the resource allocation of network slicing in next generation networks. This involves network tenants on the one hand and resource/infrastructure providers on the other hand. However, the potential downside of deploying Network Slice Broker (NSB) is that it can be victimized by DoS (Denial of Service) attack. Thus, the aim of this work is three fold. First, to present the possible ways in which DoS/DDoS attacks can be mounted on NSB and their adverse effects. Second, to propose and implement initial blockchain-based solution named as Security Service Blockchain (SSB) to prevent DoS attacks on NSB. Third, to enumerate the challenges and future research directions to effectively utilize blockchain for mitigating DoS/DDoS attacks on NSB. To evaluate the performance the proposed SSB framework is implemented using Hyperledger Fabric. The results manifest that the latency impact of the legitimate slice creation over scaled up malicious traffic remains minimal with the use of SSB framework. The integration of SSB with NSB results in gaining several fold reduction in latency under DoS attack scenario.
      10Scopus© Citations 7
  • Publication
    Federated Learning based Anomaly Detection as an Enabler for Securing Network and Service Management Automation in Beyond 5G Networks
    Network automation is a necessity in order to meet the unprecedented demand in the future networks and zero touch network architecture is proposed to cater such requirements. Closed-loop and artificial intelligence are key enablers in this proposed architecture in critical elements such as security. Apart from the arising privacy concerns, machine learning models can also face resource limitations. Federated learning is a machine learning-based technique that addresses both privacy and com- munication efficiency issues. Therefore, we propose a federated learning-based model incorporating the ZSM architecture for network automation. The paper also contains the simulations and results of the proposed multi-stage federated learning model that uses the UNSW-NB15 dataset.
    Scopus© Citations 11  296