1,347 research outputs found
Game Theory Meets Network Security: A Tutorial at ACM CCS
The increasingly pervasive connectivity of today's information systems brings
up new challenges to security. Traditional security has accomplished a long way
toward protecting well-defined goals such as confidentiality, integrity,
availability, and authenticity. However, with the growing sophistication of the
attacks and the complexity of the system, the protection using traditional
methods could be cost-prohibitive. A new perspective and a new theoretical
foundation are needed to understand security from a strategic and
decision-making perspective. Game theory provides a natural framework to
capture the adversarial and defensive interactions between an attacker and a
defender. It provides a quantitative assessment of security, prediction of
security outcomes, and a mechanism design tool that can enable
security-by-design and reverse the attacker's advantage. This tutorial provides
an overview of diverse methodologies from game theory that includes games of
incomplete information, dynamic games, mechanism design theory to offer a
modern theoretic underpinning of a science of cybersecurity. The tutorial will
also discuss open problems and research challenges that the CCS community can
address and contribute with an objective to build a multidisciplinary bridge
between cybersecurity, economics, game and decision theory
Strategic Learning for Active, Adaptive, and Autonomous Cyber Defense
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 levels of
information restrictions, i.e., from the parameter uncertainty, the payoff
uncertainty, to the environmental uncertainty. To estimate the unknown and
reduce uncertainty, we adopt three different strategic learning schemes that
fit the associated information restrictions. All three learning schemes share
the same feedback structure of sensation, estimation, and actions so that the
most rewarding policies get reinforced and converge to the optimal ones in
autonomous and adaptive fashions. This work aims to shed lights on proactive
defense strategies, lay a solid foundation for strategic learning under
incomplete information, and quantify the tradeoff between the security and
costs.Comment: arXiv admin note: text overlap with arXiv:1906.1218
A Survey of Network Requirements for Enabling Effective Cyber Deception
In the evolving landscape of cybersecurity, the utilization of cyber
deception has gained prominence as a proactive defense strategy against
sophisticated attacks. This paper presents a comprehensive survey that
investigates the crucial network requirements essential for the successful
implementation of effective cyber deception techniques. With a focus on diverse
network architectures and topologies, we delve into the intricate relationship
between network characteristics and the deployment of deception mechanisms.
This survey provides an in-depth analysis of prevailing cyber deception
frameworks, highlighting their strengths and limitations in meeting the
requirements for optimal efficacy. By synthesizing insights from both
theoretical and practical perspectives, we contribute to a comprehensive
understanding of the network prerequisites crucial for enabling robust and
adaptable cyber deception strategies
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
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An Empirical Assessment of the Effectiveness of Deception for Cyber Defense
The threat of cyber attacks is a growing concern across the world, leading to an increasing need for sophisticated cyber defense techniques. The Tularosa Study, was designed and conducted to understand how defensive deception, both cyber and psychological, affects cyber attackers Ferguson-Walter et al. [2019c]. More specifically, for this empirical study, cyber deception refers to a decoy system and psychological deception refers to false information of the presence of defensive deception techniques on the network. Over 130 red teamers participated in a network penetration test over two days in which we controlled both the presence of and explicit mention of deceptive defensive techniques. To our knowledge, this represents the largest study of its kind ever conducted on a skilled red team population. In addition to the abundant host and network data collected, we conducted a battery of questionnaires, e.g., experience, personality; and cognitive tasks, e.g., fluid intelligence, working memory; as well as physiological measures, e.g., galvanic skin response (GSR), heart rate, to be correlated with the cyber events at a later date. The design and execution of this study and the lessons learned are a major contribution of this thesis. I investigate the effectiveness of decoy systems for cyber defense by comparing performance across all experimental conditions. Results support a new finding that the combination of the presence of deception and the true information that deception is present has the greatest effect on cyber attackers, when compared to a control condition in which no deception was used. Evidence of cognitive biases in the red teamers’ behavior is then detailed and explained, to further support our theory of oppositional human factors (OHF). The final chapter discusses how elements of the experimental design contribute to the validity of assessing the effectiveness of cyber deception and reviews trade-offs and lessons learned
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