5G networks are increasingly exposed to Distributed Denial of Service (DDoS) attacks launched by mobile botnets exploiting user equipment (UE). Existing studies have treated malware propagation and DDoS impact separately, with no prior simulation work having modeled how Device-to-Device (D2D) malware spreads and translates into network-wide DDoS stress. This paper introduces DDoSimu5G, an extension of Simu5G [33] integrated with the ONE simulator [24], which enables, for the first time, the combined modeling of D2D malware propagation, UE mobility, and botnet-driven traffic loads on 5G infrastructure. The framework is aligned with 3GPP Proximity based Services (ProSe) in the 5G System (5GS) TS 23.304 [1] specifications, supports configurable attack scenarios, and generates diverse datasets, including infection logs, mobility traces, and PCAP traffic. By linking propagation dynamics with DDoS effects, DDoSimu5G provides the research community with a reproducible open-source tool for studying and mitigating emerging D2D-driven threats in 5G networks.

The landscape of healthcare is experiencing a digitalization shift, transferring many medical activities to the patients’ homes, a phenomenon commonly referred to as Hospital-at-Home. While Internet of Things (IoT) devices facilitate the building of such systems, there is a need for powerful middleware that encapsulates device-to-device communication and enables the construction of user-friendly, secure, and robust Hospital-at-Home systems. A key challenge for such middleware is to build a trustworthy and lightweight key management system allowing different devices in the system to exchange messages securely. In this article, we present a simple, easily manageable and scalable such architecture which, in addition, supports long-term data protection using post-quantum cryptographic primitives. Our proposed solution utilizes a Merkle tree to enable the IoT devices to establish trust between each other automatically, even in the absence of an Internet connection. We have implemented the architecture and present performance figures as well as a security analysis of our approach.

The advancement of mobile technologies and their ability to utilize the Global Positioning System (GPS) to accurately locate their substantial number of users, prompt Location-Based Services (LBS) significantly. Ride-sharing is a popular means of transportation that utilizes LBS. With the rapid development of smart cities and their impact on addressing the critical issues of urban life such as transportation, we can safely assume that the autonomous vehicles (AVs) will be a desired way of transportation in the near future. Therefore, the ride sharing service (RSS) providers will need to arrange their services via AVs. However, a user who wants to use a RSS has to submit their trip data (which contains location data) to the service provider. On one hand, the popularity of RSSs makes them an attractive target for cyber-attacks, and on the other hand, multiple studies show that a user’s location data can reveal sensitive information about that user. In this paper, we present a practical ride-sharing protocol for AVs that preserves both anonymity and location privacy of the users. Most of the previous works on the topic, does not provide security against malicious server and/or clients. Moreover, the previously proposed protocols rely on additional entities (e.g., a trusted third party) to satisfy the objectives of their protocols. In the presence of the malicious entities, our proposed protocol guarantees the security and privacy of the server and the clients, without relying on any additional parties. To the best of our knowledge, our protocol is the first scheme that satisfies perfect location privacy. We evaluate the performance of our protocol in a realistic setting and demonstrate its feasibility in the real life application areas, i.e., the protocol only requires 20 milliseconds to process and respond to 1000 simultaneous ride-sharing requests. Moreover, we propose a novel private sum aggregation (PSA) scheme that is designed for the use-cases where the private elements are chosen from a limited set. We believe that our novel PSA scheme may be of independent interest.