Connectivity in mobile device-to-device networks in urban environments

In this article we setup a dynamic device-to-device communication system where devices, given as a Poisson point process, move in an environment, given by a street system of random planar-tessellation type, via a random-waypoint model. Every device independently picks a target location on the street system using a general waypoint kernel, and travels to the target along the shortest path on the streets with an individual velocity. Then, any pair of devices becomes connected whenever they are on the same street in sufficiently close proximity, for a sufficiently long time. After presenting some general properties of the multi-parameter system, we focus on an analysis of the clustering behavior of the random connectivity graph. In our main results we isolate regimes for the almost-sure absence of percolation if, for example, the device intensity is too small, or the connectivity time is too large. On the other hand, we exhibit parameter regimes of sufficiently large intensities of devices, under favorable choices of the other parameters, such that percolation is possible with positive probability. Most interestingly, we also show an in-and-out of percolation as the velocity increases. The rigorous analysis of the system mainly rests on comparison arguments with simplified models via spatial coarse graining and thinning approaches. Here we also make contact to geostatistical percolation models with infinite-range dependencies

Malware propagation in urban D2D networks

We introduce and analyze models for the propagation of malware in pure D2D networks given via stationary Cox--Gilbert graphs. Here, the devices form a Poisson point process with random intensity measure λ, Λ where Λ is stationary and given, for example, by the edge-length measure of a realization of a Poisson--Voronoi tessellation that represents an urban street system. We assume that, at initial time, a typical device at the center of the network carries a malware and starts to infect neighboring devices after random waiting times. Here we focus on Markovian models, where the waiting times are exponential random variables, and non-Markovian models, where the waiting times feature strictly positive minimal and finite maximal waiting times. We present numerical results for the speed of propagation depending on the system parameters. In a second step, we introduce and analyze a counter measure for the malware propagation given by special devices called white knights, which have the ability, once attacked, to eliminate the malware from infected devices and turn them into white knights. Based on simulations, we isolate parameter regimes in which the malware survives or is eliminated, both in the Markovian and non-Markovian setting

Chase-escape in dynamic device-to-device networks

The present paper features results on global survival and extinction of an infection in a multi-layer network of mobile agents. Expanding on a model first presented in CHJW22, we consider an urban environment, represented by line-segments in the plane, in which agents move according to a random waypoint model based on a Poisson point process. Whenever two agents are at sufficiently close proximity for a sufficiently long time the infection can be transmitted and then propagates into the system according to the same rule starting from a typical device. Inspired by wireless network architectures, the network is additionally equipped with a second class of agents that is able to transmit a patch to neighboring infected agents that in turn can further distribute the patch, leading to a chase-escape dynamics. We give conditions for parameter configurations that guarantee existence and absence of global survival as well as an in-and-out of the survival regime, depending on the speed of the devices. We also provide complementary results for the setting in which the chase-escape dynamics is defined as an independent process on the connectivity graph. The proofs mainly rest on percolation arguments via discretization and multiscale analysis

Phase transitions for chase-escape models on Gilbert graphs

We present results on phase transitions of local and global survival in a two-species model on Gilbert graphs. At initial time there is an infection at the origin that propagates on the Gilbert graph according to a continuous-time nearest-neighbor interacting particle system. The Gilbert graph consists of susceptible nodes and nodes of a second type, which we call white knights. The infection can spread on susceptible nodes without restriction. If the infection reaches a white knight, this white knight starts to spread on the set of infected nodes according to the same mechanism, with a potentially different rate, giving rise to a competition of chase and escape. We show well-definedness of the model, isolate regimes of global survival and extinction of the infection and present estimates on local survival. The proofs rest on comparisons to the process on trees, percolation arguments and finite-degree approximations of the underlying random graphs.Comment: 13 pages, 3 figure

Phase transitions for chase-escape models on Poisson–Gilbert graphs

We present results on phase transitions of local and global survival in a two-species model on Poisson–Gilbert graphs. Initially, there is an infection at the origin that propagates on the graph according to a continuous-time nearest-neighbor interacting particle system. The graph consists of susceptible nodes and nodes of a second type, which we call white knights. The infection can spread on susceptible nodes without restriction. If the infection reaches a white knight, this white knight starts to spread on the set of infected nodes according to the same mechanism, with a potentially different rate, giving rise to a competition of chase and escape. We show well-definedness of the model, isolate regimes of global survival and extinction of the infection and present estimates on local survival. The proofs rest on comparisons to the process on trees, percolation arguments and finite-degree approximations of the underlying random graphs

Evaluation of the Ability to Transform SIM Applications into Hostile Applications

Part 1: Smart Cards System SecurityInternational audienceThe ability of Java Cards to withstand attacks is based on software and hardware countermeasures, and on the ability of the Java platform to check the correct behavior of Java code (by using byte code verification). Recently, the idea of combining logical attacks with a physical attack in order to bypass byte code verification has emerged. For instance, correct and legitimate Java Card applications can be dynamically modified on-card using a laser beam. Such applications become mutant applications, with a different control flow from the original expected behaviour. This internal change could lead to bypass controls and protections and thus offer illegal access to secret data and operations inside the chip. This paper presents an evaluation of the application ability to become mutant and a new countermeasure based on the runtime checks of the application control flow to detect the deviant mutations

Malware propagation in urban D2D networks

We introduce and analyze models for the propagation of malware in pure D2D networks given via stationary Cox-Gilbert graphs. Here, the devices form a Poisson point process with random intensity measure $\lambda\Lambda$, where $\Lambda$ is stationary and given, for example, by the edge-length measure of a realization of a Poisson-Voronoi tessellation that represents an urban street system. We assume that, at initial time, a typical device at the center of the network carries a malware and starts to infect neighboring devices after random waiting times. Here we focus on Markovian models, where the waiting times are exponential random variables, and non-Markovian models, where the waiting times feature strictly positive minimal and finite maximal waiting times. We present numerical results for the speed of propagation depending on the system parameters. In a second step, we introduce and analyze a counter measure for the malware propagation given by special devices called white knights, which have the ability, once attacked, to eliminate the malware from infected devices and turn them into white knights. Based on simulations, we isolate parameter regimes in which the malware survives or is eliminated, both in the Markovian and non-Markovian setting.Comment: 8 pages, 10 figure

Liability-aware security management for 5G

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Multi-party and multi-layer nature of 5G networks implies the inherent distribution of management and orchestration decisions across multiple entities. Therefore, responsibility for management decisions concerning end-to-end services become blurred if no efficient liability and accountability mechanism is used. In this paper, we present the design, building blocks and challenges of a Liability-Aware Security Management (LASM) system for 5G. We describe how existing security concepts such as manifests and Security-by-Contract, root cause analysis, remote attestation, proof of transit, and trust and reputation models can be composed and enhanced to take risk and responsibilities into account for security and liability management

Demonstrating liability and trust metrics for multi-actor, dynamic edge and cloud microservices

Transitioning edge and cloud computing in 5G networks towards service-based architecture increases their complexity as they become even more dynamic and intertwine more actors or delegation levels. In this paper, we demonstrate the Liability-aware security manager Analysis Service (LAS), a framework that uses machine learning techniques to compute liability and trust indicators for service-based architectures such as cloud microservices. Based on the commitments of Service Providers (SPs) and real-time observations collected by a Root Cause Analysis (RCA) tool GRALAF, the LAS computes three categories of liability and trust indicators, specifically, a Commitment Trust Score, Financial Exposure, and Commitment Trends

The owner, the provider and the subcontractors : how to handle accountability and liability management for 5G end to end service

The adoption of 5G services depends on the capacity to provide high-value services. In addition to enhanced performance, the capacity to deliver Security Service Level Agreements (SSLAs) and demonstrate their fulfillment would be a great incentive for the adoption of 5G services for critical 5G Verticals (e.g., service suppliers like Energy or Intelligent Transportation Systems) subject to specific industrial safety, security or service level rules and regulations (e.g., NIS or SEVESO Directives). Yet, responsibilities may be difficult to track and demonstrate because 5G infrastructures are interconnected and complex, which is a challenge anticipated to be exacerbated in future 6G networks. This paper describes a demonstrator and a use case that shows how 5G Service Providers can deliver SSLAs to their customers (Service Owners) by leveraging a set of network enablers developed in the INSPIRE-5Gplus project to manage their accountability, liability and trust placed in subcomponents of a service (subcontractors). The elaborated enablers are in particular a novel sTakeholder Responsibility, AccountabIity and Liability deScriptor (TRAILS), a Liability-Aware Service Management Referencing Service (LASM-RS), an anomaly detection tool (IoT-MMT), a Root Cause Analysis tool (IoT-RCA), two Remote Attestation mechanisms (Systemic and Deep Attestation), and two Security-by-Orchestration enablers (one for the 5G Core and one for the MEC)