Biblio

The use of Virtual Machine (VM) migration as support for software rejuvenation was introduced more than a decade ago. Since then, several works have validated this approach from experimental and theoretical perspectives. Recently, some works shed light on the possibility of using the same technique as Moving Target Defense (MTD). However, to date, no work evaluated the availability and security levels while applying VM migration for both rejuvenation and MTD (multipurpose VM migration). In this paper, we conduct a comprehensive evaluation using Stochastic Petri Net (SPN) models to tackle this challenge. The evaluation covers the steady-state system availability, expected MTD protection, and related metrics of a system under time-based multipurpose VM migration. Results show that the availability and security improvement due to VM migration deployment surpasses 50% in the best scenarios. However, there is a trade-off between availability and security metrics, meaning that improving one implies compromising the other.

Previous research on internal threats was mostly focused on modeling threat behaviors. These studies have paid little attention to risk measurement. This paper analyzed the internal threat scenarios, introduced the operation related protection model into the firewall-password model, constructed a series of sub models. By analyzing the illegal data out process, the analysis model of target network can be rapidly generated based on four protection sub-models. Then the risk value of an assessment point can be computed dynamically according to the Petri net computing characteristics and the effectiveness of overall network protection can be measured. This method improves the granularity of the model and simplifies the complexity of modeling complex networks and can realize dynamic and real-time risk measurement.

Smart power grid is a perfect model of Cyber Physical System (CPS) which is an important component for a comfortable life. The major concern of the electrical network is safety and reliable operation. A cyber attacker in the operation of power system would create a major damage to the entire power system structure and affect the continuity of the power supply by adversely changing its parameters. A risk assessment method is presented for evaluating the cyber security assessment of power systems taking into consideration the need for protection systems. The paper considers the impact of bus and transmission line protection systems located in substations on the cyber physical performance of power systems. The proposed method is to simulate the response of power systems to sudden attacks on various power system preset value and parameters. This paper focuses on the cyber attacks which occur in a co-ordinated way so that many power system components will be in risk. The risk can be modelled as the combined probability of power system impact due to attacks and of successful interruption into the system. Stochastic Petri Nets is employed for assessing the risks. The effectiveness of the proposed cyber security risk assessment method is simulated for a IEEE39 bus system.

Various aspects of security and privacy in many application domains can be assessed based on proper analysis of successive measurements that are collected on a given system. This work is devoted to such issues in the context of timed stochastic Petri net models. We assume that certain events and part of the marking trajectories are observable to adversaries who aim to determine when the system is performing secret operations, such as time intervals during which the system is executing certain critical sequences of events (as captured, for instance, in language-based opacity formulations). The combined use of the k-step trajectory-observer and the Markov model of the stochastic Petri net leads to probabilistic indicators helpful for evaluating language-based opacity of the given system, related timing aspects, and possible strategies to improve them.

Distributed and parallel applications are critical information technology systems in multiple industries, including academia, military, government, financial, medical, and transportation. These applications present target rich environments for malicious attackers seeking to disrupt the confidentiality, integrity and availability of these systems. Applying the military concept of defense cyber maneuver to these systems can provide protection and defense mechanisms that allow survivability and operational continuity. Understanding the tradeoffs between information systems security and operational performance when applying maneuver principles is of interest to administrators, users, and researchers. To this end, we present a model of a defensive maneuver cyber platform using Stochastic Petri Nets. This model enables the understanding and evaluation of the costs and benefits of maneuverability in a distributed application environment, specifically focusing on moving target defense and deceptive defense strategies.
 

Smart Grid is the trend of next generation power distribution and network management that enable a two -- way interactive communication and operation between consumers and suppliers, so as to achieve intelligent resource management and optimization. The wireless mesh network technology is a promising infrastructure solution to support these smart functionalities, while it has some inherent vulnerabilities and cyber-attack risks to be addressed. As Smart Grid is heavily relying on the underlie communication networks, which makes their security and dependability issues critical to the entire smart grid technology. Several studies have been conducted in the field of Smart Grid security, but few works were focused on the dependability and its associated resource analysis of the control center networks. In this paper, we have investigated the dependability modeling and also resource allocation in redundant communication networks by adopting two mathematical approaches, Reliability Block Diagrams (RBD) and Stochastic Petri Nets (SPNs), to analyze the dependability of control center networks in Smart Grid environment. We have applied our proposed modeling approach in an extensive case study to evaluate the availability of smart gird networks with different redundancy mechanisms. A combination of dependability models and reliability importance are used to analyze the network availability according to the most important components. We also show the variation of network availability in accordance with Mean Time to Failure (MTTF) in different network architectures.