Law Enforcement Agencies (LEAs) heavily rely on Lawful Interception (LI) tools to investigate criminal and terrorist activities. The growing frequency of cybercrime, terrorism-related offenses, and illegal trades in the European Union (EU) has driven LEAs to explore novel LI techniques that align with the developing 5G and Beyond 5G network architectures. Moreover, the emergence of extremely dynamic and distributed networks, the increased usage of end-to-end encryption applications, and privacy protections present limitations for traditional LI approaches. In order to provide a technological solution capable of extending the 3GPP LI standard, this paper presents a novel LI framework designed on top of the standardized 3GPP LI architecture, leveraging an inspection-friendly end-to-end cryptography mechanism (e.g., a Key Escrow algorithm) at the application layer. Moreover, the proposed Lawful Interception (LI) framework enables authorized LEAs to decrypt intercepted end-to-end encrypted data within the core network. Firstly, a security proof validates the security of the proposed LI framework under two attack scenarios. Subsequently, a proof-of-concept workstation implementation that emulates a 5G network for end-to-end data exchange and cloud-based deployment validates the suggested LI framework by affirming the LEA capabilities in decrypting intercepted data. Additionally, the system performance has been studied through experimental tests, ensuring the scalability of the conceived solution and revealing the possibility of intercepting data with mainly real-time latency without affecting the Quality of Service (QoS) experienced by the user.

Low-Power and Lossy Networks (LLNs) are based on constrained devices. Energy conservation is one of the main constraints, and the traditional IPv6 Neighbor Discovery Protocol (IPv6-NDP) was neither designed nor suitable to cope with it. This inefficiency arises from non-transitive wireless links and heavy multicast transmission, sometimes rendering it impractical in LLNs. Substantial work has been done by the Internet Engineering Task Force (IETF) to optimize the IPv6-ND protocol, known as IPv6 over Low power Wireless Personal Area Network - Neighbor Discovery Protocol (6LoWPAN-NDP). Despite these improvements, full implementation is yet to be achieved in commercial, open-source, or proprietary sectors. In this article, we debate both Neighbor Discovery Protocols (NDPs), examining various aspects. We implemented 6LoWPAN-NDP in a well-known ns3 simulator. We discuss the complexity of 6LoWPAN-NDP and see why open-source, commercial, or proprietary sectors have not widely adopted it. We present how both protocols function optimally in meshunder and non-meshunder scenarios. We present results and analysis of both NDPs control messages’ behavior. At the same time, data traffic is turned on and off, and we demonstrate the operational behavior of Link-local Unicast Address (LUA) and Global Unicast Address (GUA) in meshunder and non-meshunder scenarios. The presented implementation can be helpful in enabling large-scale simulations and evaluating scenario-specific protocol parameters, along with protocol extensions.

The combination of Composite Base Stations (CBSs) and Dynamic Spectrum Scheduling (DSS) can enable high-speed connectivity in urban environments, providing seamless connectivity to users and supporting a wide range of high-bandwidth applications. This paper investigates the performance of CBSs combining Fifth Generation (5G) cellular network and Fourth Generation (4G) Long-Term Evolution (LTE) modes in an urban environment such as a university campus. The comparison considers sub-6GHz and mmWave frequencies (28GHz) and a DSS to improve network performance and increase overall system capacity. The results show that the CBS approach improves network performance, increasing system capacity and provides high-speed connectivity to users. Additionally, this research highlights the potential of mmWave frequencies for use in heterogeneous networks to improve coverage over a large area. The findings of this study offer valuable insights for network planners and operators, demonstrating the benefits and challenges of CBS deployment

Abstract Cell injection is an approach used for the delivery of small sample substances into a biological cell and is widely used in drug development, gene injection, intracytoplasmic sperm injection and in-vitro fertilization. Robotic cell injection systems provide the automation of the process as opposed to the manual and semi-automated cell injection systems, which require expert operators and involve time consuming processes and also have lower success rates. The automation of the cell injection process is obtained by controlling the orientation and movement of its various components, like injection manipulator, microscope etc., and planning the motion of the injection pipette by controlling the force of the injection. The conventional techniques to analyze the cell injection process include paper-and-pencil proof and computer simulation methods. However, both these techniques suffer from their inherent limitations, such as, proneness to human error for the former and the approximation of the mathematical expressions involved in the numerical algorithms for the latter. Formal methods have the capability to overcome these limitations and can provide an accurate analysis of these cell injection systems. Model checking, i.e., a state-based formal method, has been recently used for analyzing these systems. However, it involves the discretization of the differential equations capturing the continuous dynamics of the system and thus compromises on the completeness of the analysis of these safety-critical systems. In this paper, we propose a higher-order-logic theorem proving (a deductive-reasoning based formal method) based framework for analyzing the dynamical behavior of the robotic cell injection systems upto 4-DOF. The proposed analysis, based on the HOL Light theorem prover, enabled us to identify some discrepancies in the simulation and model checking based analysis of the same robotic cell injection system.

Advancement in information and communication technology within financial services industry facilitates the trend to automate the trade life cycle. Algorithmic trading has emerged not only as a standard trading and analytical platform but also created the need for generic research tools to educate traders and researchers to compare, and statistically evaluate appropriate trading strategies. Current simulating techniques are very much restricted with regards to scope and users functionality. This research study aims to provide an overview of algorithmic trading processes as well as investigates a platform that will provide a domain based service oriented architecture (SOA) in which users can invoke certain functions within the system as services.