Deception plays a critical role in the financial industry, online markets, national defense, and countless other areas. Understanding and harnessing deception - especially in cyberspace - is both crucial and difficult. Recent work in this area has used game theory to study the roles of incentives and rational behavior. Building upon this work, we employ a game-theoretic model for the purpose of mechanism design. Specifically, we study a defensive use of deception: implementation of honeypots for network defense. How does the design problem change when an adversary develops the ability to detect honeypots? We analyze two models: cheap-talk games and an augmented version of those games that we call cheap-talk games with evidence, in which the receiver can detect deception with some probability. Our first contribution is this new model for deceptive interactions. We show that the model includes traditional signaling games and complete information games as special cases. We also demonstrate numerically that deception detection sometimes eliminate pure-strategy equilibria. Finally, we present the surprising result that the utility of a deceptive defender can sometimes increase when an adversary develops the ability to detect deception. These results apply concretely to network defense. They are also general enough for the large and critical body of strategic interactions that involve deception.
Deception plays critical roles in economics and technology, especially in emerging interactions in cyberspace. Holistic models of deception are needed in order to analyze interactions and to design mechanisms that improve them. Game theory provides such models. In particular, existing work models deception using signaling games. But signaling games inherently model deception that is undetectable. In this paper, we extend signaling games by including a detector that gives off probabilistic warnings when the sender acts deceptively. Then we derive pooling and partially-separating equilibria of t…
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.…
Deception is a technique to mislead human or computer systems by manipulating beliefs and information. For the applications of cyber deception, non-cooperative games become a natural choice of models to capture the adversarial interactions between the players and quantitatively characterizes the conflicting incentives and strategic responses. In this chapter, we provide an overview of deception games in three different environments and extend the baseline signaling game models to include evidence through side-channel knowledge acquisition to capture the information asymmetry, dynamics, and str…
In the field of network security, with the ongoing arms race between attackers, seeking new vulnerabilities to bypass defense mechanisms and defenders reinforcing their prevention, detection and response strategies, the novel concept of cyber deception has emerged. Starting from the well-known example of honeypots, many other deception strategies have been developed such as honeytokens and moving target defense, all sharing the objective of creating uncertainty for attackers and increasing the chance for the attacker of making mistakes. In this paper a methodology to evaluate the effectiveness…
Cyber deception has recently received increasing attentions as a promising mechanism for proactive cyber defense. Cyber deception strategies aim at injecting intentionally falsified information to sabotage the early stage of attack reconnaissance and planning in order to render the final attack action harmless or ineffective. Motivated by recent advances in cyber deception research, we in this paper provide a formal view of cyber deception, and review high-level deception schemes and actions. We also summarize and classify recent research results of cyber defense techniques built upon the conc…
This study provides a model of cyber deception with asymmetric recognition represented by private beliefs. Signaling games, which are often used in existing works, are built on the implicit premise that the receiver's belief is public information. However, this assumption, which leads to symmetric recognition, is unrealistic in adversarial decision making. For a precise evaluation of risks arising from cognitive gaps, this paper proposes epistemic signaling games based on the Mertens-Zamir model, which explicitly quantifies players' asymmetric recognition. Equilibria of the games are analytica…
The increasing instances of advanced attacks call for a new defense paradigm that is active, autonomous, and adaptive, named as the \texttt{`3A'} defense paradigm. This chapter introduces three defense schemes that actively interact with attackers to increase the attack cost and gather threat information, i.e., defensive deception for detection and counter-deception, feedback-driven Moving Target Defense (MTD), and adaptive honeypot engagement. Due to the cyber deception, external noise, and the absent knowledge of the other players' behaviors and goals, these schemes possess three progressive…
Naval Information Warfare Center Pacific（太平洋海军信息战中心）；Laboratory for Advanced Cybersecurity Research（高级网络安全研究实验室）
Deceptive elements, including honeypots and decoys, were incorporated into the Microsoft CyberBattleSim experimentation and research platform. The defensive capabilities of the deceptive elements were tested using reinforcement learning based attackers in the provided capture the flag environment. The attacker's progress was found to be dependent on the number and location of the deceptive elements. This is a promising step toward reproducibly testing attack and defense algorithms in a simulated enterprise network with deceptive defensive elements.
Deception is a technique to mislead human or computer systems by manipulating beliefs and information. Successful deception is characterized by the information-asymmetric, dynamic, and strategic behaviors of the deceiver and the deceivee. This paper proposes a game-theoretic framework of a deception game to model the strategic behaviors of the deceiver and deceivee and construct strategies for both attacks and defenses over a continuous one-dimensional information space. We use the signaling game model to capture the information-asymmetric, dynamic, and strategic behaviors of deceptions by mod…
With the ever growing networking capabilities and services offered to users, attack surfaces have been increasing exponentially, additionally, the intricacy of network architectures has increased the complexity of cyber-defenses, to this end, the use of deception has recently been trending both in academia and industry. Deception enables to create proactive defense systems, luring attackers in order to better defend the systems at hand. Current applications of deception, only rely on static, or low interactive environments. In this paper we present a platform that combines human-computer-inter…
In this chapter, we present an approach using formal methods to synthesize reactive defense strategy in a cyber network, equipped with a set of decoy systems. We first generalize formal graphical security models--attack graphs--to incorporate defender's countermeasures in a game-theoretic model, called an attack-defend game on graph. This game captures the dynamic interactions between the defender and the attacker and their defense/attack objectives in formal logic. Then, we introduce a class of hypergames to model asymmetric information created by decoys in the attacker-defender interactions.…
Cyberattacks on both databases and critical infrastructure have threatened public and private sectors. Ubiquitous tracking and wearable computing have infringed upon privacy. Advocates and engineers have recently proposed using defensive deception as a means to leverage the information asymmetry typically enjoyed by attackers as a tool for defenders. The term deception, however, has been employed broadly and with a variety of meanings. In this paper, we survey 24 articles from 2008-2018 that use game theory to model defensive deception for cybersecurity and privacy. Then we propose a taxonomy …
Naval Information Warfare Center Pacific（太平洋海军信息战中心）；Laboratory for Advanced Cybersecurity Research（高级网络安全研究实验室）
The performance of artificial intelligence (AI) algorithms in practice depends on the realism and correctness of the data, models, and feedback (labels or rewards) provided to the algorithm. This paper discusses methods for improving the realism and ecological validity of AI used for autonomous cyber defense by exploring the potential to use Inverse Reinforcement Learning (IRL) to gain insight into attacker actions, utilities of those actions, and ultimately decision points which cyber deception could thwart. The Tularosa study, as one example, provides experimental data of real-world techniqu…
We introduce password strength information signaling as a novel, yet counter-intuitive, defense mechanism against password cracking attacks. Recent breaches have exposed billions of user passwords to the dangerous threat of offline password cracking attacks. An offline attacker can quickly check millions (or sometimes billions/trillions) of password guesses by comparing their hash value with the stolen hash from a breached authentication server. The attacker is limited only by the resources he is willing to invest. Our key idea is to have the authentication server store a (noisy) signal about …
Virginia Tech（弗吉尼亚理工大学）；North Carolina State University（北卡罗来纳州立大学）；US Army Research Laboratory（美国陆军研究实验室）
Defensive deception is a promising approach for cyber defense. Via defensive deception, the defender can anticipate attacker actions; it can mislead or lure attacker, or hide real resources. Although defensive deception is increasingly popular in the research community, there has not been a systematic investigation of its key components, the underlying principles, and its tradeoffs in various problem settings. This survey paper focuses on defensive deception research centered on game theory and machine learning, since these are prominent families of artificial intelligence approaches that are …
Deceptive and anti-deceptive technologies have been developed for various specific applications. But there is a significant need for a general, holistic, and quantitative framework of deception. Game theory provides an ideal set of tools to develop such a framework of deception. In particular, game theory captures the strategic and self-interested nature of attackers and defenders in cybersecurity. Additionally, control theory can be used to quantify the physical impact of attack and defense strategies. In this tutorial, we present an overview of game-theoretic models and design mechanisms for…
Recent incidents such as the Colonial Pipeline ransomware attack and the SolarWinds hack have shown that traditional defense techniques are becoming insufficient to deter adversaries of growing sophistication. Proactive and deceptive defenses are an emerging class of methods to defend against zero-day and advanced attacks. This work develops a new game-theoretic framework called the duplicity game to design deception mechanisms that consist of a generator, an incentive modulator, and a trust manipulator, referred to as the GMM mechanism. We formulate a mathematical programming problem to compu…
Cyber Deception for Mission Surveillance via Hypergame-Theoretic Deep Reinforcement Learning
Department of Computer Science, Virginia Tech（弗吉尼亚理工大学计算机科学系）；Computer Network Information Center, Chinese Academy of Sciences（中国科学院计算机网络信息中心）；Department of Computer Science, North Carolina State University（北卡罗来纳州立大学计算机科学系）；US Army Research Laboratory（美国陆军研究实验室）
Resource constrained Internet-of-Things (IoT) devices are highly likely to be compromised by attackers because strong security protections may not be suitable to be deployed. This requires an alternative approach to protect vulnerable components in IoT networks. In this paper, we propose an integrated defense technique to achieve intrusion prevention by leveraging cyberdeception (i.e., a decoy system) and moving target defense (i.e., network topology shuffling). We verify the effectiveness and efficiency of our proposed technique analytically based on a graphical security model in a software d…
Security challenges accompany the efficiency. The pervasive integration of information and communications technologies (ICTs) makes cyber-physical systems vulnerable to targeted attacks that are deceptive, persistent, adaptive and strategic. Attack instances such as Stuxnet, Dyn, and WannaCry ransomware have shown the insufficiency of off-the-shelf defensive methods including the firewall and intrusion detection systems. Hence, it is essential to design up-to-date security mechanisms that can mitigate the risks despite the successful infiltration and the strategic response of sophisticated att…
We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. As a consequence, online social deception (OSD) in SNSs has emerged as a serious threat in cyberspace, particularly for users vulnerable to such cyberattacks. Cyber attackers have exploited the sophisticated features of SNSs to carry out harmful OSD activities, such as financial fraud, privacy threat, or sexual/labor exploitation. Therefore, it is critical to understand OSD and develop effective countermeasures against OSD for building a trustworth…
Advanced persistent threats (APTs) are stealthy attacks which make use of social engineering and deception to give adversaries insider access to networked systems. Against APTs, active defense technologies aim to create and exploit information asymmetry for defenders. In this paper, we study a scenario in which a powerful defender uses honeynets for active defense in order to observe an attacker who has penetrated the network. Rather than immediately eject the attacker, the defender may elect to gather information. We introduce an undiscounted, infinite-horizon Markov decision process on a con…
Abuse of zero-permission sensors on-board mobile and wearable devices to infer users' personal context and information is a well-known privacy threat that has received significant attention. Efforts towards protection mechanisms that prevent or limit the success of such threats, however, have been ad-hoc so far and have primarily focused on designing threat-specific customized defense mechanisms. Such approaches are not very practical, as evident from their limited adoption within major mobile/wearable operating systems. In the end, it is clear that all privacy threats that take advantage of u…
Internet of Things (IoT) devices can be exploited by the attackers as entry points to break into the IoT networks without early detection. Little work has taken hybrid approaches that combine different defense mechanisms in an optimal way to increase the security of the IoT against sophisticated attacks. In this work, we propose a novel approach to generate the strategic deployment of adaptive deception technology and the patch management solution for the IoT under a budget constraint. We use a graphical security model along with three evaluation metrics to measure the effectiveness and effici…
Choice architecture describes the design by which choices are presented to people. Nudges are an aspect intended to make "good" outcomes easy, such as using password meters to encourage strong passwords. Sludge, on the contrary, is friction that raises the transaction cost and is often seen as a negative to users. Turning this concept around, we propose applying sludge for positive cybersecurity outcomes by using it offensively to consume attackers' time and other resources. To date, most cyber defenses have been designed to be optimally strong and effective and prohibit or eliminate attackers…
Airbus Defence & Space Cybersecurity（空客防务与航天网络安全部门）
Recent advancements in Artificial Intelligence (AI) have brought new capabilities to behavioural analysis (UEBA) for cyber-security consisting in the detection of hostile action based on the unusual nature of events observed on the Information System.In our previous work (presented at C\&ESAR 2018 and FIC 2019), we have associated deep neural networks auto-encoders for anomaly detection and graph-based events correlation to address major limitations in UEBA systems. This resulted in reduced false positive and false negative rates, improved alert explainability, while maintaining real-time perf…
