Pei Yu Chen

Evaluation of network survivability considering degree of disconnectivity

It is impossible for a system or network to keep completely safe with the possibility of many new threats occurring at any moment. To analyze and solve these kinds of problems, this paper presents a mathematical programming problem, which adopts a novel metric called Degree of Disconnectivity (DOD) to evaluate the damage level and survivability of a network. To evaluate and analyze the robustness of a network for network operators, this problem is modeled as a mathematical programming problem. Here, an attacker applies his limited attack power intelligently to the targeted network. The objective of the attacker is to compromise nodes, resulting in disconnections of O-D pairs, to ensure that the proposed degree of disconnectivity metric reachs a given level. A Lagrangean relaxation-based algorithm is adopted to solve the proposed problem.

Resource Allocation Strategies to Maximize Network Survivability Considering of Average DOD

In this paper, an innovative metric called Average Degree of Disconnectivity (Average DOD) is proposed. The Average DOD combining the concept of the probability calculated by contest success function with the DOD metric would be used to evaluate the damage degree of network. The larger value of the Average DOD, the more damage degree of the network would be. An attack-defense scenario as a mathematical model would be used to support network operators to predict that all the likelihood strategies both cyber attacker and network defender would take. The attacker could use the attack resources to launch attack on the nodes of network. On the other hand, the network defender allocates existed resources of defender to protect survival nodes of network. In the process of problem solving, the “gradient method” and “game theory” would be adopted to find the optimal resource allocation strategies for both cyber attacker and network defender.

Maximization of network survivability considering degree of disconnectivity

The issues of survivability of networks, especially to some open year round services have increased rapidly over the last few years. To address this topic, the effective survivability metric is mandatory for managerial responsibility. In this paper, we provide a survivability mechanism called Degree of Disconnectivity (DOD) for the network operator to detect risks. To evaluate and analyze the robustness of a network for network operators, this problem is modeled as a mathematical programming problem. An attacker applies his limited attack power intelligently to the targeted network. The objective of the attacker is to compromise nodes, which means to disable the connections of O-D pairs, to achieve the goal of reaching a given level of the proposed Degree of Disconnectivity metric. A Lagrangean Relaxation-based algorithm is adopted to solve the proposed problem.

An Evaluation of Network Survivability under the Effect of Accumulated Experience from Sophisticated Attackers

This paper is focused on the resource allocation of network attack and defense with mathematical programming and to optimize the problem. It adopts a concept, discount coupon, to describe the attack behavior of taking advantage of accumulated experience from his previous attack actions of minimizing future attack cost. The attacker obtains free experience before he launch an attack or from a compromised node which could further reduce the cost of an attack. The attacker’s objective is to minimize the total attack cost, while the core node is compromised and the network could not survive. Here, by transforming with node splitting into a generalized shortest path problem and applying the algorithm to optimally solve it.

Resource Allocation Strategies under Attack-Defense Dual-Role and Malicious Attacks

How to efficiently evaluate the network survivability is a critical issue in nowadays. Hence, we develop a multi-round network attack-defense scenario with dual-role players, who can attack and defend, and establish a mathematical model to optimize resource allocation and then predict the network survivability by the Average DOD. In each round, the players could allocate their attack resources on the nodes of their own network and on another player’s network after updating related information about another player’s. Furthermore, they could reallocate existing defense resources and repair compromised nodes. To solve the problem, the gradient method and the game theory would be adopted to find the optimal resource allocation strategies for both players.

Recovery and Resource Allocation Strategies to Maximize Mobile Network Survivability by Using Game Theories and Optimization Techniques

With more and more mobile device users, an increasingly important and critical issue is how to efficiently evaluate mobile network survivability. In this paper, a novel metric called Average Degree of Disconnectivity (Average DOD) is proposed, in which the concept of probability is calculated by the contest success function. The DOD metric is used to evaluate the damage degree of the network, where the larger the value of the Average DOD, the more the damage degree of the network. A multiround network attack-defense scenario as a mathematical model is used to support network operators to predict all the strategies both cyber attacker and network defender would likely take. In addition, the Average DOD would be used to evaluate the damage degree of the network. In each round, the attacker could use the attack resources to launch attacks on the nodes of the target network. Meanwhile, the network defender could reallocate its existing resources to recover compromised nodes and allocate defense resources to protect the survival nodes of the network. In the approach to solving this problem, the “gradient method” and “game theory” are adopted to find the optimal resource allocation strategies for both the cyber attacker and mobile network defender.

Network defense strategies for maximization of network survivability

The Internet has brought about several threats of information security to individuals and cooperates. It is difficult to keep a network completely safe because cyber attackers can launch attacks through networks without limitations of time and space. As a result, it is an important and critical issue be able to efficiently evaluate network survivability. In this paper, an innovative metric called the Degree of Disconnectivity (DOD) is proposed, which is used to evaluate the damage level of the network. A network attack-defense scenario is also considered in this problem, in which the attack and defense actions are composed by many rounds with each round containing two stages. In the first stage, defenders deploy limited resources on the nodes resulting in attackers needing to increase attack costs to compromise the nodes. In the second stage, the attacker uses his limited budget to launch attacks, trying to maximize the damage of the network. The Lagrangean Relaxation Method is applied to obtain optimal solutions for the problem.

Near optimal secret sharing for information leakage maximization

In this paper, we propose a mathematical programming model to describe an offense-defense scenario. In the offense problem, the objective of attackers is to compromise nodes in order to steal information. Therefore, the attackers try to recover secrets through compromising certain nodes and to maximize the information leakage as much as possible. During the attack actions, the attacker must allocate a limited budget to collect a large enough number of shares and decrypted keys through compromising certain nodes. Therefore, we advocate Lagrangean Relaxation algorithms and the proposed heuristics to find a near optimal solution. Through solutions from the perspective of the attacker, we then induce some efficient defense mechanisms for the network operators.