Paper2020
Material reviewed: AbstractThe authors present a differentially private game theoretic approach to cyber deception, aiming to overcome limitations of prior approaches that assume a fixed number of systems and simplified attackers. The defender uses differential privacy mechanisms to strategically change the number of systems and obfuscate configurations, while the attacker uses Bayesian inference. According to the authors, experimental results demonstrate the effectiveness of the proposed approach.
NetworkDecoyMoving target defense
Paper2020
Material reviewed: AbstractAccording to the abstract, the authors propose DARCY, a defense framework adapting the honeypot concept from cybersecurity to detect Universal Trigger textual adversarial attacks. DARCY injects multiple trapdoors into a neural network model to bait and detect such attacks, reporting high detection rates in experiments across four public datasets.
ApplicationHoneypotDecoy
Paper2020
Material reviewed: AbstractThe authors propose a formal-methods approach to synthesize reactive defense strategies in networks equipped with decoy systems. They generalize attack graphs to incorporate defender countermeasures in an attack-defend game model, and introduce a class of hypergames to model asymmetric information created by decoys. According to the authors, this framework enables synthesis of effective defense strategies exploiting the attacker's misperception.
NetworkDecoyMoving target defense
Paper2020
Material reviewed: Publisher metadataBibliographic record on an adaptive deception framework. The abstract and findings still require review.
ApplicationDecoy
Paper2020
Material reviewed: AbstractThis paper, according to its authors, presents an adaptive agent that uses active deception to recognize a cyber attacker's intent, modeling the problem as a two-agent sequential decision process via factored I-POMDPs. The authors describe using honeypots and decoys across multiple attack phases to refine predictions about attacker behavior, rather than merely delaying or confusing attackers.
NetworkEndpointHoneypotDecoy
Paper2020
Material reviewed: Full textBibliographic record on adaptive signaling for cyber defense. The abstract and findings still require review.
NetworkDecoy
Paper2020
Material reviewed: AbstractThe study presents an exploratory experiment with 30 human participants acting as attackers to test a masking strategy (compared with a random masking strategy) aimed at reducing attackers' utility during network reconnaissance. The authors observed that attackers appeared more successful in launching attacks in the optimal condition, that the attackers' total score did not differ between masking strategies, and a generalized tendency to act according to certainty bias or risk aversion.
NetworkDecoy
Paper2020
Material reviewed: AbstractThe paper proposes an anti-reconnaissance model for host fingerprints based on virtual nodes. The model constructs periodically reconfigurable virtual nodes to dynamically camouflage host fingerprint information and redirects attack traffic targeting virtual nodes to honeypots; the authors also introduce probabilistic models to examine how parameters such as the number of probes or honeypot mapping rules affect attack success probability, and they describe a prototype using SDN and DPDK intended to verify the model against reconnaissance.
NetworkHoneypotDecoy
Paper2020
Material reviewed: Full textCritical readingSurvey of defensive deception models and techniques in networks, hosts and cryptographic mechanisms.
NetworkEndpointDecoy
Paper2020
Material reviewed: AbstractAccording to the authors, this study proposes a time-expanded random network to model adversarial lateral movement in enterprise networks, along with dynamic cognitive honeypots placed at idle production nodes and honey links disguised as service links. The authors describe an approach aimed at reducing long-term vulnerability through honeypot policies whose location changes randomly.
NetworkHoneypotDecoy
Paper2020
Material reviewed: Publisher metadataBibliographic record on personalized web-application deception. The abstract and findings still require review.
ApplicationDecoy
Paper2020
Material reviewed: AbstractAccording to the authors, this paper introduces 'Primer', a tool for priming and evaluating dynamic honeypots against previously developed measures of effectiveness related to environment fingerprinting, capturing adversary data, deception, and self-monitoring. The authors state they provide quantitative calibration results as a step toward automated effectiveness testing.
NetworkHoneypotDecoy
Paper2020
Material reviewed: AbstractThe authors propose an integrated defense technique combining cyberdeception via decoy systems with moving target defense through network topology shuffling, applied to SDN-based IoT networks. According to the abstract, they develop and compare several strategies for deciding when and how to reshuffle network topology in the presence of decoys, analytically evaluating effectiveness through a graphical security model. The authors report that their approach prolongs system lifetime, increases attack complexity, and maintains service availability compared to a network without the technique.
IoTNetworkMoving target defenseDecoy
Paper2020
Material reviewed: AbstractThe paper reviews the use of deception technology, specifically honeypot systems, to address threats against IoT devices. The authors compare the most popular existing honeypot systems, identify their strengths and weaknesses, and attempt to adapt them to operate at the level of Internet of things devices.
IoTHoneypotDecoy
Paper2020
Material reviewed: AbstractThis paper addresses the synthesis of active deception strategies in networks using two-player games with asymmetric information and temporal logic objectives, incorporating decoy systems and high-fidelity honeypots. The authors use a level-2 hypergame framework to model the attacker's incomplete perception and assess whether the defender can guarantee security properties.
NetworkDecoyHoneypot
Paper2019
Material reviewed: AbstractAccording to the authors, this work proposes AnonTokens, an approach applying the honeytoken concept to the data privacy domain to trace re-identification attacks. High re-identification-risk decoy records are inserted into anonymized datasets to detect malicious users. The authors evaluate their approach using large-scale population datasets.
ApplicationHoneytokenDecoy
Paper2019
Material reviewed: AbstractThe article discusses how cyber deception can change an attacker's perception of the network environment and lead attackers to false beliefs about which systems contain critical information. The authors introduce game theory models and discuss techniques combining artificial intelligence algorithms with those models to estimate hidden states of the attacker using feedback through payoffs, in order to learn how best to defend the system using cyber deception.
NetworkDecoyAdversary engagement
Paper2019
Material reviewed: AbstractAccording to the abstract, this work develops inference techniques to detect organic click fraud in advertising networks. The authors note that malware detection systems, including honeypots, fail to stop click fraud apps, and propose two defenses: a mimicry defence based on detecting click reuse patterns, and a bait-click defence that injects decoy clicks to trigger fraudulent app behavior.
NetworkApplicationHoneypotDecoy
Paper2019
Material reviewed: AbstractThe authors present an overview of cyber deception games across three environments, extending baseline signaling game models to include evidence via side-channel knowledge acquisition. They analyze deception in binary and continuous information spaces and explore a multi-stage incomplete-information Bayesian game model for defensive deception against advanced persistent threats, using perfect Bayesian Nash equilibrium as the solution concept.
NetworkAdversary engagementDecoy
Paper2019
Material reviewed: AbstractAndrew Bushby's article describes the use of deception technology as a mechanism for active, post-breach defence aimed at luring, detecting and defending against malware and intruders moving laterally within the network. It notes that such approaches come with misconceptions and argues that defences need to move beyond detecting bad activity within an ocean of good activity.
NetworkDecoyAdversary engagement
Paper2019
Material reviewed: AbstractAccording to the authors, this paper presents a user study with 40 participants evaluating HoneyBot, a hybrid-interaction honeypot designed for networked robotic systems that simulates unsafe actions while performing safe physical ones. The authors report that participants could not distinguish simulated sensor values from real ones.
IoTOT/ICSHoneypotDecoy
Paper2019
Material reviewed: AbstractAccording to the authors, this paper proposes an SDN-based in-network honeypot that reroutes traffic from suspicious nodes and intelligently spoofs it with misleading information to confuse attackers in IoT environments, without requiring dedicated hardware. The authors state preliminary evaluations show little impact on network performance.
IoTNetworkHoneypotDecoy
Paper2019
Material reviewed: AbstractThe authors present experimental tests of common attacks on wired IPv6 networks and describe the design and implementation of a Honeynet with different operating systems. They use tools such as 6Guard, Snort and Wireshark to attract, detect and analyze attacker behavior.
NetworkHoneypotDecoy
Paper2018
Material reviewed: Publisher metadataBibliographic record on cyber deception overview and challenges. The abstract and findings still require review.
NetworkDecoy