Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2025/r/gumushane/10471
  A comprehensive and realistic performance evaluation of post-quantum security for consumer IoT devices

  Hanna, Yacoub; Bozhko, Jessica; Tonyali, Samet; Harrilal-Parchment, Ricardo; Cebe, Mumin; Akkaya, Kemal

  The computational capacity envisaged for quantum computers poses a significant threat to today's traditional cryptographic algorithms. Although they are not yet large enough to compromise current cryptographic protocols, one can practice retrospective decryption since data packets traveling through the Internet can be easily sniffed. This threat extends to wireless communication security within consumer IoT devices that use lightweight cryptography due to limited computational power. Thus, countermeasures against potential quantum attacks should be preemptively adopted. NIST is leading efforts to standardize several algorithms as quantum-resistant Key Exchange Mechanisms (KEMs) and Digital Signatures. In this paper, we investigate the viability of these Post-Quantum algorithms in the Transport Layer Security (TLS) of power-constrained IoT devices. Specifically, it focuses on two widely used IoT network protocol stacks, i.e., Bluetooth Low Energy (BLE) and Wi-Fi. To this end, we build a realistic IoT testbed running IP over BLE. Our evaluation considers the impact of several realistic factors for the first time, such as using a chain of certificates on the server side and incorporating certificate validation methods such as Online Certificate Status Protocol (OCSP) and Certificate Revocation Lists (CRL). We also evaluate the impact of mutual authentication between the server and the client. Utilizing the outcomes of this evaluation, we then propose a novel approach for IoT devices to dynamically choose the most efficient KEM algorithm for TLS based on the device's physical network interface. The performance results provide valuable insights with respect to the TLS latency and energy consumption of consumer IoT devices.

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• MakaleYayıncıda açık erişim2025/r/gumushane/12344
  GeMID: Generalizable models for IoT device identification

  Kostas, Kahraman; Yasa Kostas, Rabia; Just, Mike; Lones, Michael A.

  With the proliferation of devices on the Internet of Things (IoT), ensuring their security has become paramount. Device identification (DI), which distinguishes IoT devices based on their traffic patterns, plays a crucial role in both differentiating devices and identifying vulnerable ones, closing a serious security gap. However, existing approaches to DI that build machine learning models often overlook the challenge of model generalizability across diverse network environments. In this study, we propose a novel framework to address this limitation and to evaluate the generalizability of DI models across data sets collected within different network environments. Our approach involves a two-step process: first, we develop a feature and model selection method that is more robust to generalization issues by using a genetic algorithm with external feedback and datasets from distinct environments to refine the selections. Second, the resulting DI models are then tested on further independent datasets to robustly assess their generalizability. We demonstrate the effectiveness of our method by empirically comparing it to alternatives, highlighting how fundamental limitations of commonly employed techniques such as sliding window and flow statistics limit their generalizability. Moreover, we show that statistical methods, widely used in the literature, are unreliable for device identification due to their dependence on network-specific characteristics rather than device-intrinsic properties, challenging the validity of a significant portion of existing research. Our findings advance research in IoT security and device identification, offering insight into improving model effectiveness and mitigating risks in IoT networks.

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