2,588 research outputs found
A Game Theoretic approach based virtual machine migration for cloud environment security
In cloud computing environment, static configurations can provide for the attackers an environment too easy for exploitation and discovering the network vulnerabilities in order to compromise the network and launching intrusions; while dynamic reconfiguration seeks to develop a virtual machine (VM) migration over the cloud by applying unpredictability of network configuration’s change, and thus improving the system security. In this work a novel approach that performs proactive and reactive measures to ensure a high availability and to minimize the attack surface using VM migration is proposed. This interaction between attack and defense systems was formulated as game model. As result, we have calculated the Nash equilibrium and the utilities for the both attacker and defender, evaluate the parameters which can maximize the defender’s utility when the VM migration was planned and identify the potential attack paths. Therefore, the effectiveness of the game model was validated by some numerical results that determine optimal migration strategies in order to ensure the security of the system
A Cost-effective Shuffling Method against DDoS Attacks using Moving Target Defense
Moving Target Defense (MTD) has emerged as a newcomer into the asymmetric
field of attack and defense, and shuffling-based MTD has been regarded as one
of the most effective ways to mitigate DDoS attacks. However, previous work
does not acknowledge that frequent shuffles would significantly intensify the
overhead. MTD requires a quantitative measure to compare the cost and
effectiveness of available adaptations and explore the best trade-off between
them. In this paper, therefore, we propose a new cost-effective shuffling
method against DDoS attacks using MTD. By exploiting Multi-Objective Markov
Decision Processes to model the interaction between the attacker and the
defender, and designing a cost-effective shuffling algorithm, we study the best
trade-off between the effectiveness and cost of shuffling in a given shuffling
scenario. Finally, simulation and experimentation on an experimental software
defined network (SDN) indicate that our approach imposes an acceptable
shuffling overload and is effective in mitigating DDoS attacks
Three Decades of Deception Techniques in Active Cyber Defense -- Retrospect and Outlook
Deception techniques have been widely seen as a game changer in cyber
defense. In this paper, we review representative techniques in honeypots,
honeytokens, and moving target defense, spanning from the late 1980s to the
year 2021. Techniques from these three domains complement with each other and
may be leveraged to build a holistic deception based defense. However, to the
best of our knowledge, there has not been a work that provides a systematic
retrospect of these three domains all together and investigates their
integrated usage for orchestrated deceptions. Our paper aims to fill this gap.
By utilizing a tailored cyber kill chain model which can reflect the current
threat landscape and a four-layer deception stack, a two-dimensional taxonomy
is developed, based on which the deception techniques are classified. The
taxonomy literally answers which phases of a cyber attack campaign the
techniques can disrupt and which layers of the deception stack they belong to.
Cyber defenders may use the taxonomy as a reference to design an organized and
comprehensive deception plan, or to prioritize deception efforts for a budget
conscious solution. We also discuss two important points for achieving active
and resilient cyber defense, namely deception in depth and deception lifecycle,
where several notable proposals are illustrated. Finally, some outlooks on
future research directions are presented, including dynamic integration of
different deception techniques, quantified deception effects and deception
operation cost, hardware-supported deception techniques, as well as techniques
developed based on better understanding of the human element.Comment: 19 page
Game-Theoretic Frameworks and Strategies for Defense Against Network Jamming and Collocation Attacks
Modern networks are becoming increasingly more complex, heterogeneous, and densely connected. While more diverse services are enabled to an ever-increasing number of users through ubiquitous networking and pervasive computing, several important challenges have emerged. For example, densely connected networks are prone to higher levels of interference, which makes them more vulnerable to jamming attacks. Also, the utilization of software-based protocols to perform routing, load balancing and power management functions in Software-Defined Networks gives rise to more vulnerabilities that could be exploited by malicious users and adversaries. Moreover, the increased reliance on cloud computing services due to a growing demand for communication and computation resources poses formidable security challenges due to the shared nature and virtualization of cloud computing. In this thesis, we study two types of attacks: jamming attacks on wireless networks and side-channel attacks on cloud computing servers. The former attacks disrupt the natural network operation by exploiting the static topology and dynamic channel assignment in wireless networks, while the latter attacks seek to gain access to unauthorized data by co-residing with target virtual machines (VMs) on the same physical node in a cloud server. In both attacks, the adversary faces a static attack surface and achieves her illegitimate goal by exploiting a stationary aspect of the network functionality. Hence, this dissertation proposes and develops counter approaches to both attacks using moving target defense strategies. We study the strategic interactions between the adversary and the network administrator within a game-theoretic framework. First, in the context of jamming attacks, we present and analyze a game-theoretic formulation between the adversary and the network defender. In this problem, the attack surface is the network connectivity (the static topology) as the adversary jams a subset of nodes to increase the level of interference in the network. On the other side, the defender makes judicious adjustments of the transmission footprint of the various nodes, thereby continuously adapting the underlying network topology to reduce the impact of the attack. The defender\u27s strategy is based on playing Nash equilibrium strategies securing a worst-case network utility. Moreover, scalable decomposition-based approaches are developed yielding a scalable defense strategy whose performance closely approaches that of the non-decomposed game for large-scale and dense networks. We study a class of games considering discrete as well as continuous power levels. In the second problem, we consider multi-tenant clouds, where a number of VMs are typically collocated on the same physical machine to optimize performance and power consumption and maximize profit. This increases the risk of a malicious virtual machine performing side-channel attacks and leaking sensitive information from neighboring VMs. The attack surface, in this case, is the static residency of VMs on a set of physical nodes, hence we develop a timed migration defense approach. Specifically, we analyze a timing game in which the cloud provider decides when to migrate a VM to a different physical machine to mitigate the risk of being compromised by a collocated malicious VM. The adversary decides the rate at which she launches new VMs to collocate with the victim VMs. Our formulation captures a data leakage model in which the cost incurred by the cloud provider depends on the duration of collocation with malicious VMs. It also captures costs incurred by the adversary in launching new VMs and by the defender in migrating VMs. We establish sufficient conditions for the existence of Nash equilibria for general cost functions, as well as for specific instantiations, and characterize the best response for both players. Furthermore, we extend our model to characterize its impact on the attacker\u27s payoff when the cloud utilizes intrusion detection systems that detect side-channel attacks. Our theoretical findings are corroborated with extensive numerical results in various settings as well as a proof-of-concept implementation in a realistic cloud setting
Metaverse for Wireless Systems: Architecture, Advances, Standardization, and Open Challenges
The growing landscape of emerging wireless applications is a key driver
toward the development of novel wireless system designs. Such a design can be
based on the metaverse that uses a virtual model of the physical world systems
along with other schemes/technologies (e.g., optimization theory, machine
learning, and blockchain). A metaverse using a virtual model performs proactive
intelligent analytics prior to a user request for efficient management of the
wireless system resources. Additionally, a metaverse will enable
self-sustainability to operate wireless systems with the least possible
intervention from network operators. Although the metaverse can offer many
benefits, it faces some challenges as well. Therefore, in this tutorial, we
discuss the role of a metaverse in enabling wireless applications. We present
an overview, key enablers, design aspects (i.e., metaverse for wireless and
wireless for metaverse), and a novel high-level architecture of metaverse-based
wireless systems. We discuss metaverse management, reliability, and security of
the metaverse-based system. Furthermore, we discuss recent advances and
standardization of metaverse-enabled wireless system. Finally, we outline open
challenges and present possible solutions
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