marmoteCore: a Markov Modeling Platform

International audienceWe present the marmoteCore software project, an open environment for modeling with Markov chains. This platform aims at providing the general scientific user with tools for creating Markov models and accessing the many solution algorithms available for their analysis. We describe its object-oriented architecture, some of its presently available features, and we discuss through examples how existing software can be interfaced with it

On Formal Methods for Collective Adaptive System Engineering. {Scalable Approximated, Spatial} Analysis Techniques. Extended Abstract

In this extended abstract a view on the role of Formal Methods in System Engineering is briefly presented. Then two examples of useful analysis techniques based on solid mathematical theories are discussed as well as the software tools which have been built for supporting such techniques. The first technique is Scalable Approximated Population DTMC Model-checking. The second one is Spatial Model-checking for Closure Spaces. Both techniques have been developed in the context of the EU funded project QUANTICOL.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

Per Chunk Caching for Video Streaming from a Vehicular Cloud

International audienceCaching content at the edge of mobile networks is considered as a promising way to deal with the data tsunami. In addition to caching at fixed base stations or user devices, it has been recently proposed that an architecture with public or private transportation acting as mobile relays and caches might be a promising middle ground. In previous work, we have assumed users are streaming video files, and analyzed how many replicas of each video file to cache in such a vehicular fleet, towards minimizing the amount of bits per file downloaded from (expensive) infrastructure links. However, this work has been assuming that a vehicle will store the entire content, or none of it. In practice, later chunks have an inherent “delay tolerance” as there is more time to find them before they must be played out. What is more, numerous studies as well as everyday experience suggest that most files (e.g. YouTube) ones are not entirely watched. This makes the previous policies suboptimal, as fewer (or no) replicas could be allocated to late chunks of a file and more to the most popular chunks. In this work, we formulate an optimization problem to compute the optimal allocation per chunk, to minimize the load on the cellular infrastructure, and we show that significant performance gains can be achieved compared to per content allocation policies

Petri Nets Validation of Markovian Models of Emergency Department Arrivals

International audienceModeling of hospital’s Emergency Departments (ED) is vital for optimisation of health services offered to patients that shows up at an ED requiring treatments with different level of emergency. In this paper we present a modeling study whose contribution is twofold: first, based on a dataset relative to the ED of an Italian hospital, we derive different kinds of Markovian models capable to reproduce, at different extents, the statistical character of dataset arrivals; second, we validate the derived arrivals model by interfacing it with a Petri net model of the services an ED patient undergoes. The empirical assessment of a few key performance indicators allowed us to validate some of the derived arrival process model, thus confirming that they can be used for predicting the performance of an ED

On the Edge of Secure Connectivity via Software-Defined Networking

Securing communication in computer networks has been an essential feature ever since the Internet, as we know it today, was started. One of the best known and most common methods for secure communication is to use a Virtual Private Network (VPN) solution, mainly operating with an IP security (IPsec) protocol suite originally published in 1995 (RFC1825). It is clear that the Internet, and networks in general, have changed dramatically since then. In particular, the onset of the Cloud and the Internet-of-Things (IoT) have placed new demands on secure networking. Even though the IPsec suite has been updated over the years, it is starting to reach the limits of its capabilities in its present form. Recent advances in networking have thrown up Software-Defined Networking (SDN), which decouples the control and data planes, and thus centralizes the network control. SDN provides arbitrary network topologies and elastic packet forwarding that have enabled useful innovations at the network level. This thesis studies SDN-powered VPN networking and explains the benefits of this combination. Even though the main context is the Cloud, the approaches described here are also valid for non-Cloud operation and are thus suitable for a variety of other use cases for both SMEs and large corporations. In addition to IPsec, open source TLS-based VPN (e.g. OpenVPN) solutions are often used to establish secure tunnels. Research shows that a full-mesh VPN network between multiple sites can be provided using OpenVPN and it can be utilized by SDN to create a seamless, resilient layer-2 overlay for multiple purposes, including the Cloud. However, such a VPN tunnel suffers from resiliency problems and cannot meet the increasing availability requirements. The network setup proposed here is similar to Software-Defined WAN (SD-WAN) solutions and is extremely useful for applications with strict requirements for resiliency and security, even if best-effort ISP is used. IPsec is still preferred over OpenVPN for some use cases, especially by smaller enterprises. Therefore, this research also examines the possibilities for high availability, load balancing, and faster operational speeds for IPsec. We present a novel approach involving the separation of the Internet Key Exchange (IKE) and the Encapsulation Security Payload (ESP) in SDN fashion to operate from separate devices. This allows central management for the IKE while several separate ESP devices can concentrate on the heavy processing. Initially, our research relied on software solutions for ESP processing. Despite the ingenuity of the architectural concept, and although it provided high availability and good load balancing, there was no anti-replay protection. Since anti-replay protection is vital for secure communication, another approach was required. It thus became clear that the ideal solution for such large IPsec tunneling would be to have a pool of fast ESP devices, but to confine the IKE operation to a single centralized device. This would obviate the need for load balancing but still allow high availability via the device pool. The focus of this research thus turned to the study of pure hardware solutions on an FPGA, and their feasibility and production readiness for application in the Cloud context. Our research shows that FPGA works fluently in an SDN network as a standalone IPsec accelerator for ESP packets. The proposed architecture has 10 Gbps throughput, yet the latency is less than 10 µs, meaning that this architecture is especially efficient for data center use and offers increased performance and latency requirements. The high demands of the network packet processing can be met using several different approaches, so this approach is not just limited to the topics presented in this thesis. Global network traffic is growing all the time, so the development of more efficient methods and devices is inevitable. The increasing number of IoT devices will result in a lot of network traffic utilising the Cloud infrastructures in the near future. Based on the latest research, once SDN and hardware acceleration have become fully integrated into the Cloud, the future for secure networking looks promising. SDN technology will open up a wide range of new possibilities for data forwarding, while hardware acceleration will satisfy the increased performance requirements. Although it still remains to be seen whether SDN can answer all the requirements for performance, high availability and resiliency, this thesis shows that it is a very competent technology, even though we have explored only a minor fraction of its capabilities

Anomaly detection in SCADA systems: a network based approach

Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols. However, modern deployments commonly make use of commercial off-the-shelf devices and standard communication protocols, such as TCP/IP. Furthermore, these networks are becoming increasingly interconnected, allowing communication with corporate networks and even the Internet. As a result, SCADA networks become vulnerable to cyber attacks, being exposed to the same threats that plague traditional IT systems.\ud \ud In our view, measurements play an essential role in validating results in network research; therefore, our first objective is to understand how SCADA networks are utilized in practice. To this end, we provide the first comprehensive analysis of real-world SCADA traffic. We analyze five network packet traces collected at four different critical infrastructures: two water treatment facilities, one gas utility, and one electricity and gas utility. We show, for instance, that exiting network traffic models developed for traditional IT networks cannot be directly applied to SCADA network traffic. \ud \ud We also confirm two SCADA traffic characteristics: the stable connection matrix and the traffic periodicity, and propose two intrusion detection approaches that exploit them. In order to exploit the stable connection matrix, we investigate the use of whitelists at the flow level. We show that flow whitelists have a manageable size, considering the number of hosts in the network, and that it is possible to overcome the main sources of instability in the whitelists. In order to exploit the traffic periodicity, we focus our attention to connections used to retrieve data from devices in the field network. We propose PeriodAnalyzer, an approach that uses deep packet inspection to automatically identify the different messages and the frequency at which they are issued. Once such normal behavior is learned, PeriodAnalyzer can be used to detect data injection and Denial of Service attacks