Development of a Security Methodology for Cooperative Information Systems: The CooPSIS Project

Since networks and computing systems are vital components of today\u27s life, it is of utmost importance to endow them with the capability to survive physical and logical faults, as well as malicious or deliberate attacks. When the information system is obtained by federating pre-existing local systems, a methodology is needed to integrate security policies and mechanisms under a uniform structure. Therefore, in building distributed information systems, a methodology for analysis, design and implementation of security requirements of data and processes is essential for obtaining mutual trust between cooperating organizations. Moreover, when the information system is built as a cooperative set of e-services, security is related to the type of data, to the sensitivity context of the cooperative processes and to the security characteristics of the communication paradigms. The CoopSIS (Cooperative Secure Information Systems) project aims to develop methods and tools for the analysis, design, implementation and evaluation of secure and survivable distributed information systems of cooperative type, in particular with experimentation in the Public Administration Domain. This paper presents the basic issues of a methodology being conceived to build a trusted cooperative environment, where data sensitivity parameters and security requirements of processes are taken into account. The milestones phases of the security development methodology in the context of this project are illustrated

Survivability modeling for cyber-physical systems subject to data corruption

Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart from specifications will affect these dependability attributes. Our focus is on data corruption, which compromises decision support -- the fundamental role played by cyber infrastructure. The first research contribution of this work is a Petri net model for information exchange in cyber-physical systems, which facilitates i) evaluation of the extent of data corruption at a given time, and ii) illuminates the service degradation caused by propagation of corrupt data through the cyber infrastructure. In the second research contribution, we propose metrics and an evaluation method for survivability, which captures the extent of functionality retained by a system after a disruptive event. We illustrate the application of our methods through case studies on smart grids, intelligent water distribution networks, and intelligent transportation systems. Data, cyber infrastructure, and intelligent control are part and parcel of nearly every critical infrastructure that underpins daily life in developed countries. Our work provides means for quantifying and predicting the service degradation caused when cyber infrastructure fails to serve its intended purpose. It can also serve as the foundation for efforts to fortify critical systems and mitigate inevitable failures --Abstract, page iii

Survivability analogy for cloud computing

As cloud computing has become the most popular computing platform, and cloud-based applications a commonplace, the methods and mechanisms used to ensure their survivability is increasingly becoming paramount. One of the prevalent trends in recent times is a turn to nature for inspiration in developing and supporting highly survivable environments. This paper aims to address the problems of survivability in cloud environments through inspiration from nature. In particular, the community metaphor in nature's predator-prey systems where autonomous individuals' local decisions focus on ensuring the global survival of the community. Thus, we develop analogies for survivability in cloud computing based on a range of mechanisms which we view as key determinants of prey's survival against predation. For this purpose we investigate some predator-prey systems that will form the basis for our analogical designs. Furthermore, due to a lack of a standardized definition of survivability, we propose a unified definition for survivability, which emphasizes as imperative, a high level of proactiveness to thwart black swan events, as well as high capacity to respond to insecurity in a timely and appropriate manner, inspired by prey's avoidance and anti-predation approaches. © 2017 IEEE

Algorithms for advance bandwidth reservation in media production networks

Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results

Energy management in communication networks: a journey through modelling and optimization glasses

The widespread proliferation of Internet and wireless applications has produced a significant increase of ICT energy footprint. As a response, in the last five years, significant efforts have been undertaken to include energy-awareness into network management. Several green networking frameworks have been proposed by carefully managing the network routing and the power state of network devices. Even though approaches proposed differ based on network technologies and sleep modes of nodes and interfaces, they all aim at tailoring the active network resources to the varying traffic needs in order to minimize energy consumption. From a modeling point of view, this has several commonalities with classical network design and routing problems, even if with different objectives and in a dynamic context. With most researchers focused on addressing the complex and crucial technological aspects of green networking schemes, there has been so far little attention on understanding the modeling similarities and differences of proposed solutions. This paper fills the gap surveying the literature with optimization modeling glasses, following a tutorial approach that guides through the different components of the models with a unified symbolism. A detailed classification of the previous work based on the modeling issues included is also proposed

Self-organising management of Grid environments

This paper presents basic concepts, architectural principles and algorithms for efficient resource and security management in cluster computing environments and the Grid. The work presented in this paper is funded by BTExacT and the EPSRC project SO-GRM (GR/S21939)