An Architecture A Day Keeps The Hacker Away

System security as it is practiced today is a losing battle. In this paper, we outline a possible comprehensive solution for binary-based attacks, using virtual machines, machine descriptions, and randomization to achieve broad heterogeneity at the machine level. This heterogeneity increases the “cost” of broad-based binary attacks to a sufficiently high level that they cease to become feasible. The convergence of several recent technologies appears to make our approach achievable at a reasonable cost, with only moderate run-time overhead.Engineering and Applied Science

Markov modeling of moving target defense games

We introduce a Markov-model-based framework for Moving Target Defense (MTD) analysis. The framework allows modeling of broad range of MTD strategies, provides general theorems about how the probability of a successful adversary defeating an MTD strategy is related to the amount of time/cost spent by the adversary, and shows how a multi-level composition of MTD strategies can be analyzed by a straightforward combination of the analysis for each one of these strategies. Within the proposed framework we define the concept of security capacity which measures the strength or effectiveness of an MTD strategy: the security capacity depends on MTD specific parameters and more general system parameters. We apply our framework to two concrete MTD strategies

Code renewability for native software protection

Software protection aims at safeguarding assets embedded in software by preventing and delaying reverse engineering and tampering attacks. This article presents an architecture and supporting tool flow to renew parts of native applications dynamically. Renewed and diversified code and data belonging to either the original application or to linked-in protections are delivered from a secure server to a client on demand. This results in frequent changes to the software components when they are under attack, thus making attacks harder. By supporting various forms of diversification and renewability, novel protection combinations become available and existing combinations become stronger. The prototype implementation is evaluated on several industrial use cases

Code Renewability for Native Software Protection

Software protection aims at safeguarding assets embedded in software by preventing and delaying reverse engineering and tampering attacks. This paper presents an architecture and supporting tool flow to renew parts of native applications dynamically. Renewed and diversified code and data belonging to either the original application or to linked-in protections are delivered from a secure server to a client on demand. This results in frequent changes to the software components when they are under attack, thus making attacks harder. By supporting various forms of diversification and renewability, novel protection combinations become available, and existing combinations become stronger. The prototype implementation is evaluated on a number of industrial use cases

Cybersecurity Games: Mathematical Approaches for Cyber Attack and Defense Modeling

Cyber-attacks targeting individuals and enterprises have become a predominant part of the computer/information age. Such attacks are becoming more sophisticated and prevalent on a day-to-day basis. The exponential growth of cyber plays and cyber players necessitate the inauguration of new methods and research for better understanding the cyber kill chain, particularly with the rise of advanced and novel malware and the extraordinary growth in the population of Internet residents, especially connected Internet of Things (IoT) devices. Mathematical modeling could be used to represent real-world cyber-attack situations. Such models play a beneficial role when it comes to the secure design and evaluation of systems/infrastructures by providing a better understanding of the threat itself and the attacker\u27s conduct during the lifetime of a cyber attack. Therefore, the main goal of this dissertation is to construct a proper theoretical framework to be able to model and thus evaluate the defensive strategies/technologies\u27 effectiveness from a security standpoint. To this end, we first present a Markov-based general framework to model the interactions between the two famous players of (network) security games, i.e., a system defender and an attacker taking actions to reach its attack objective(s) in the game. We mainly focus on the most significant and tangible aspects of sophisticated cyber attacks: (1) the amount of time it takes for the adversary to accomplish its mission and (2) the success probabilities of fulfilling the attack objective(s) by translating attacker-defender interactions into well-defined games and providing rigorous cryptographic security guarantees for a system given both players\u27 tactics and strategies. We study various attack-defense scenarios, including Moving Target Defense (MTD) strategies, multi-stage attacks, and Advanced Persistent Threats (APT). We provide general theorems about how the probability of a successful adversary defeating a defender’s strategy is related to the amount of time (or any measure of cost) spent by the adversary in such scenarios. We also introduce the notion of learning in cybersecurity games and describe a general game of consequences meaning that each player\u27s chances of making a progressive move in the game depend on its previous actions. Finally, we walk through a malware propagation and botnet construction game in which we investigate the importance of defense systems\u27 learning rates to fight against the self-propagating class of malware such as worms and bots. We introduce a new propagation modeling and containment strategy called the learning-based model and study the containment criterion for the propagation of the malware based on theoretical and simulation analysis

An Architecture A Day Keeps The Hacker Away

System security as it is practiced today is a losing battle. In this paper, we outline a possible comprehensive solution for binary-based attacks, using virtual machines, machine descriptions, and randomization to achieve broad heterogeneity at the machine level. This heterogeneity increases the “cost” of broad-based binary attacks to a sufficiently high level that they cease to become feasible. The convergence of several recent technologies appears to make our approach achievable at a reasonable cost, with only moderate run-time overhead