Relevant bibliographies by topics / Honeypots

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Honeypots'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Honeypots"

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Cheng, Kai, Zhan Wu, Dongkun Li, Xin Li, and Mu Ren. "The TaintDroid Based Honeypot Monitoring System for Embedded Device." Journal of Physics: Conference Series 2203, no. 1 (2022): 012077. http://dx.doi.org/10.1088/1742-6596/2203/1/012077.

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Abstract Honeypot is a proactive defense technology introduced by defenders. Through the honeypots, defenders can deceive attackers to illegally take advantage of the honeypots and capture and analyze the attack behaviors to understand the attack tools and methods. To build honeypots, defenders first imitate vulnerable systems to entice the attacker to attack, then deploy monitoring systems that is responsible for monitoring and recording the attacker’s behavior. It is of concern that monitoring system is the key to determine the performance of honeypots, because obtaining attackers’ behavior
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Strogov, Vladimir, and Sergey Ulasen. "Leveraging generative AI for dynamic file honeypots: Insights and implementation." Cyber Security: A Peer-Reviewed Journal 8, no. 4 (2025): 392. https://doi.org/10.69554/ztax4067.

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In the field of cyber security, dynamic file honeypots serve as critical tools for detecting and analysing malicious activities, especially zero-day ransomware attacks. This paper explores the integration of generative AI (GenAI) with file honeypots to enhance their effectiveness. By dynamically generating virtual decoy content, these advanced honeypots deceive attackers and protect real data. The discussion includes technical aspects of implementing file honeypots, focusing on two primary cases: dynamically inserted virtual honeypot files and honeypot files wrapped around real protected files
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Yang, Xingyuan, Jie Yuan, Hao Yang, Ya Kong, Hao Zhang, and Jinyu Zhao. "A Highly Interactive Honeypot-Based Approach to Network Threat Management." Future Internet 15, no. 4 (2023): 127. http://dx.doi.org/10.3390/fi15040127.

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In this paper, considering the problem that the common defensive means in the current cyber confrontation often fall into disadvantage, honeypot technology is adopted to turn reactive into proactive to deal with the increasingly serious cyberspace security problem. We address the issue of common defensive measures in current cyber confrontations that frequently lead to disadvantages. To tackle the progressively severe cyberspace security problem, we propose the adoption of honeypot technology to shift from a reactive to a proactive approach. This system uses honeypot technology for active defe
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Li, Yang, Leyi Shi, and Haijie Feng. "A Game-Theoretic Analysis for Distributed Honeypots." Future Internet 11, no. 3 (2019): 65. http://dx.doi.org/10.3390/fi11030065.

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A honeypot is a decoy tool for luring an attacker and interacting with it, further consuming its resources. Due to its fake property, a honeypot can be recognized by the adversary and loses its value. Honeypots equipped with dynamic characteristics are capable of deceiving intruders. However, most of their dynamic properties are reflected in the system configuration, rather than the location. Dynamic honeypots are faced with the risk of being identified and avoided. In this paper, we focus on the dynamic locations of honeypots and propose a distributed honeypot scheme. By periodically changing
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Lanz, Stefanie, Sarah Lily-Rose Pignol, Patrick Schmitt, et al. "Optimizing Internet of Things Honeypots with Machine Learning: A Review." Applied Sciences 15, no. 10 (2025): 5251. https://doi.org/10.3390/app15105251.

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The increasing use of Internet of Things (IoT) devices has led to growing security concerns, necessitating advanced solutions to address emerging threats. Honeypots enhance IoT security by attracting and analyzing attackers. However, traditional honeypots struggle with adaptability and efficiency. This paper examines how machine learning enhances honeypot capabilities by improving threat detection and response mechanisms. A systematic literature review using the snowballing method explores the application of supervised, unsupervised, and reinforcement learning. Various classifiers for machine
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Morić, Zlatan, Vedran Dakić, and Damir Regvart. "Advancing Cybersecurity with Honeypots and Deception Strategies." Informatics 12, no. 1 (2025): 14. https://doi.org/10.3390/informatics12010014.

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Cybersecurity threats are becoming more intricate, requiring preemptive actions to safeguard digital assets. This paper examines the function of honeypots as critical instruments for threat detection, analysis, and mitigation. A novel methodology for comparative analysis of honeypots is presented, offering a systematic framework to assess their efficacy. Seven honeypot solutions, namely Dionaea, Cowrie, Honeyd, Kippo, Amun, Glastopf, and Thug, are analyzed, encompassing various categories, including SSH and HTTP honeypots. The solutions are assessed via simulated network attacks and comparativ
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Katakwar, Harsh, Shashank Uttrani, Palvi Aggarwal, and Varun Dutt. "Influence of different honeypot proportions on adversarial decisions in a deception game." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (2022): 120–24. http://dx.doi.org/10.1177/1071181322661120.

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Cyberattacks are proliferating, and deception via honeypots may provide efficient strategies for combating cyberattacks. Although prior research has examined deception and network factors using deception-based games, it is still unknown how the proportion of honeypots in a network influences the adversarial decision. This study evaluates the influence of different honeypot proportions on the adversary’s decisions using a deception game (DG). DG has two consecutive stages, probe and attack. In the probe stage, participants may probe a few webservers or not probe the network. In the attack stage
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Čisar, Petar. "The Place and Role of Honeypot Solutions in Network Intrusion Detection Systems." IPSI Transactions on Internet Research Volume 21, Issue 2 (2025): 107. https://doi.org/10.58245/ipsi.tir.2503.11.

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As cyber threats continue to evolve, organizations increasingly rely on advanced security mechanisms to detect and mitigate malicious activities. Honeypots, as deceptionbased security tools, play a crucial role in Network Intrusion Detection Systems (NIDS) by defrauding attackers and collecting intelligence on their tactics. This survey provides a systematic and comprehensive review of honeypot solutions within modern NIDS, offering an in-depth categorization of different types of honeypots, examining their integration with NIDS, and evaluating their effectiveness in detecting sophisticated cy
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Touch, Sereysethy, and Jean-Noël Colin. "A Comparison of an Adaptive Self-Guarded Honeypot with Conventional Honeypots." Applied Sciences 12, no. 10 (2022): 5224. http://dx.doi.org/10.3390/app12105224.

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To proactively defend computer systems against cyber-attacks, a honeypot system—purposely designed to be prone to attacks—is commonly used to detect attacks, discover new vulnerabilities, exploits or malware before they actually do real damage to real systems. Its usefulness lies in being able to operate without being identified as a trap by adversaries; otherwise, its values are significantly reduced. A honeypot is commonly classified by the degree of interactions that they provide to the attacker: low, medium and high-interaction honeypots. However, these systems have some shortcomings of th
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DOSKU, Lediano. "Honeypots, for a more secure network." Ingenious 4, no. 1 (2024): 66–83. http://dx.doi.org/10.58944/zsqz4632.

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The ever-increasing reliance on networked systems has brought about a heightened need for robust network security measures. This diploma thesis aims to explore the effectiveness and practicality of employing honeypots as a means to enhance network security. Honeypots are decoy systems that are strategically deployed to attract potential attackers and gather valuable information about their tactics, techniques, and motives. By analyzing the data collected from honeypots, network administrators can gain crucial insights into emerging threats and vulnerabilities, thereby enabling them to fortify
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Dissertations / Theses on the topic "Honeypots"

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Akkaya, Deniz, and Fabien Thalgott. "Honeypots in network security." Thesis, Linnaeus University, School of Computer Science, Physics and Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-6600.

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<p>Day by day, more and more people are using internet all over the world. It is becoming apart of everyone’s life. People are checking their e-mails, surfing over internet, purchasinggoods, playing online games, paying bills on the internet etc. However, while performingall these things, how many people know about security? Do they know the risk of beingattacked, infecting by malicious software? Even some of the malicious software arespreading over network to create more threats by users. How many users are aware of thattheir computer may be used as zombie computers to target other victim sys
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Yahyaoui, Aymen. "Testing deceptive honeypots." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/44032.

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Approved for public release; distribution is unlimited<br>Deception can be a useful defensive technique against cyber attacks. It has the advantage of unexpectedness to attackers and offers a variety of tactics. Honeypots are a good tool for deception. They act as decoy computers to confuse attackers and exhaust their time and resources. The objective of this thesis was to test the effectiveness of some honeypot tools in real networks by varying their location and virtualization, and by adding more deception to them. We tested both a web honeypot tool and an SSH honeypot tool. We deployed the
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Christoffersen, Dag, and Bengt Jonny Mauland. "Worm Detection Using Honeypots." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9454.

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<p>This thesis describes a project that utilizes honeypots to detect worms. A detailed description of existing worm detection techniques using honeypots is given, as well as a study of existing worm propagation models. Simulations using some of these worm propagation models are also conducted. Although the results of the simulations coincide with the collected data from the actual outbreak of a network worm, they also conclude that it is difficult to produce realistic results prior to a worm outbreak. A worm detection mechanism called HoneyComb is incorporated in the honeypot setup installe
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Bergande, Eirik Falk Georg, and Jon Fjeldberg Smedsrud. "Using Honeypots to Analyze Bots and Botnets." Thesis, Norwegian University of Science and Technology, Department of Telematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9566.

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<p>In this Master thesis we will perform honeypot experiments where we allow malicious users access to systems and analyze their behaviour. Our focus will be on botnets, and how attackers progress to infect systems and add them to their botnet. Our experiments will include both high-interaction honeypots where we let attackers manually access our system, and low interaction-honeypots where we receive automated malware. The high-interaction honeypots are normal Linux distributions accessing the internet through a Honeywall that captures and controls the data flow, while the low-interaction hone
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Almotairi, Saleh Ibrahim Bakr. "Using honeypots to analyse anomalous Internet activities." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/31833/1/Saleh_Almotairi_Thesis.pdf.

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Monitoring Internet traffic is critical in order to acquire a good understanding of threats to computer and network security and in designing efficient computer security systems. Researchers and network administrators have applied several approaches to monitoring traffic for malicious content. These techniques include monitoring network components, aggregating IDS alerts, and monitoring unused IP address spaces. Another method for monitoring and analyzing malicious traffic, which has been widely tried and accepted, is the use of honeypots. Honeypots are very valuable security resources for gat
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Lim, Sze Li Harry. "Assessing the effects of honeypots on cyber-attackers." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FLim%5FSze.pdf.

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Alosefer, Yaser. "Analysing web-based malware behaviour through client honeypots." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/29469/.

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With an increase in the use of the internet, there has been a rise in the number of attacks on servers. These attacks can be successfully defended against using security technologies such as firewalls, IDS and anti-virus software, so attackers have developed new methods to spread their malicious code by using web pages, which can affect many more victims than the traditional approach. The attackers now use these websites to threaten users without the user’s knowledge or permission. The defence against such websites is less effective than traditional security products meaning the attackers have
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Wagener, Gérard. "Self-Adaptive Honeypots Coercing and Assessing Attacker Behaviour." Phd thesis, Institut National Polytechnique de Lorraine - INPL, 2011. http://tel.archives-ouvertes.fr/tel-00627981.

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Information security communities are always talking about "attackers" or "blackhats", but in reality very little is known about their skills. The idea of studying attacker behaviors was pioneered in the early nineties. In the last decade the number of attacks has increased exponentially and honeypots were introduced in order to gather information about attackers and to develop early-warning systems. Honeypots come in different flavors with respect to their interaction potential. A honeypot can be very restrictive, but this implies only a few interactions. However, if a honeypot is very toleran
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Wagener, Gérard. "Self-Adaptive Honeypots Coercing and Assessing Attacker Behaviour." Electronic Thesis or Diss., Vandoeuvre-les-Nancy, INPL, 2011. http://www.theses.fr/2011INPL037N.

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Les communautés de la sécurité informatique parlent de "pirates informatiques", mais en réalité, très peu est connu au sujet de leurs compétences. Durant la dernière décennie, le nombre d'attaques a augmenté de façon exponentielle et les pots de miels ont été alors introduits afin de recueillir des informations sur les attaquants. Ces pots de miel viennent en des saveurs différentes en fonction de leur potentiel d'interaction. Cette thèse abordera le paradigme des pots de miel adaptatifs pouvant changer leur comportement dans l’intention de tromper les attaquants en dévoilant le plus de rensei
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Chairetakis, Eleftherios, Bassam Alkudhir, and Panagiotis Mystridis. "Deployment of Low Interaction Honeypots in University Campus Network." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-22141.

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Large scale networks face daily thousands of network attacks. No matter the strength of the existing security defending mechanisms, these networks remain vulnerable, as new tools and techniques are being constantly developed by hackers. A new promising technology that lures the attackers in order to monitor their malicious activities and divulge their intentions is emerging with Virtual Honeypots. In the present thesis, we examine an extensive security mechanism based on three different open source low interaction honeypots. We implement this mechanism at our university campus network in an at
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Books on the topic "Honeypots"

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Thorsten, Holz, ed. Virtual honeypots. Addison-Wesley, 2007.

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Grimes, Roger A. Honeypots for Windows. Apress, 2005.

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1882-1956, Milne A. A., ed. Disney's Pooh's five little honeypots. Mouse Works, 1998.

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(Firm), LeapFrog, ed. Lots and lots of honeypots. LeapFrog, 2001.

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Chanwai-Earle, Lynda. Honeypants. Auckland University Press, 1994.

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Temple, Honey B. Honeypot: Learning to dodge the bullets. The author, 2004.

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Anjali, Sardana, ed. Honeypot: A new paradigm to information security. Science Publishers, 2011.

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Peter, Avis, and Blackham Stuart, eds. Honeypot: A teacher's guide to primary technology. 2nd ed. Resource, 1994.

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NG, Chee Keong, Lei Pan, and Yang Xiang. Honeypot Frameworks and Their Applications: A New Framework. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7739-5.

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Bodmer, E. The electric honeypot: The profitability of deregulated electric generation companies. American Public Power Association, 2007.

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Book chapters on the topic "Honeypots"

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Ng, Chee Keong, Lei Pan, and Yang Xiang. "Design Honeypots." In Honeypot Frameworks and Their Applications: A New Framework. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7739-5_2.

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Watters, Paul A. "Honeypots and Deception." In Cybercrime and Cybersecurity. CRC Press, 2023. http://dx.doi.org/10.1201/9781003406730-12.

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Rahalkar, Sagar Ajay. "IDSes, Firewalls, and Honeypots." In Certified Ethical Hacker (CEH) Foundation Guide. Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2325-3_13.

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Fernandez, Gerardo, Ana Nieto, and Javier Lopez. "Modeling Malware-driven Honeypots." In Trust, Privacy and Security in Digital Business. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64483-7_9.

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Perkins, Robert C., and C. Jordan Howell. "Honeypots for Cybercrime Research." In Researching Cybercrimes. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74837-1_12.

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Ihanus, Jouni, and Tero Kokkonen. "Modelling Medical Devices with Honeypots." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65726-0_26.

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Simões, Paulo, Tiago Cruz, Jorge Proença, and Edmundo Monteiro. "Specialized Honeypots for SCADA Systems." In Intelligent Systems, Control and Automation: Science and Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18302-2_16.

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Dagon, David, Xinzhou Qin, Guofei Gu, et al. "HoneyStat: Local Worm Detection Using Honeypots." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30143-1_3.

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Dutta, Nitul, Nilesh Jadav, Nirali Dutiya, and Dhara Joshi. "Using Honeypots for ICS Threats Evaluation." In Recent Developments on Industrial Control Systems Resilience. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31328-9_9.

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Bhagat, Neeraj, and Bhavna Arora. "Honeypots and Its Deployment: A Review." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2285-3_59.

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Conference papers on the topic "Honeypots"

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Guan, Chongqi, Guohong Cao, and Sencun Zhu. "HoneyLLM: Enabling Shell Honeypots with Large Language Models." In 2024 IEEE Conference on Communications and Network Security (CNS). IEEE, 2024. http://dx.doi.org/10.1109/cns62487.2024.10735663.

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Aradi, Zoltán, and Anna Bánáti. "The Role of Honeypots in Modern Cybersecurity Strategies." In 2025 IEEE 23rd World Symposium on Applied Machine Intelligence and Informatics (SAMI). IEEE, 2025. https://doi.org/10.1109/sami63904.2025.10883300.

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Hegedüs, Dániel László, Ádám Balogh, Máté Érsok, László Erdődi, Lajos Olcsák, and Anna Bánáti. "Beyond Static Defense: Dynamic Honeypots for Proactive Threat Engagement." In 2024 IEEE 18th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2024. http://dx.doi.org/10.1109/saci60582.2024.10619764.

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Christli, Jason Aljenova, Charles Lim, and Yevonnael Andrew. "AI-Enhanced Honeypots: Leveraging LLM for Adaptive Cybersecurity Responses." In 2024 16th International Conference on Information Technology and Electrical Engineering (ICITEE). IEEE, 2024. https://doi.org/10.1109/icitee62483.2024.10808265.

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Hernandez y Lopez, Miguel, and Carlos Francisco Lerma Reséndez. "Honeypots: Basic Concepts Classification and Educational Use as Resources in Information Security Education and Courses." In InSITE 2008: Informing Science + IT Education Conference. Informing Science Institute, 2008. http://dx.doi.org/10.28945/3186.

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This paper deals with the basic aspects of Honeypots, their use in modem computer networks and their implementation in educational environments. Initially, the implementation of Honeypots solves a common problem of Information Security and Forensics: The dissection of the elements that make up an attack against a computer system. Next, the paper explains the different types and functions of Honeypots once they are implemented in a network in order to make a distinction in terms of what is needed for the Honeypot to do. Finally, the use of Honeypots in educational environments, its benefits and
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Badrul Anuar, Nor, Omar Zakaria, and Chong Wei Yao. "Honeypot through Web (Honeyd@WEB): The Emerging of Security Application Integration." In InSITE 2006: Informing Science + IT Education Conference. Informing Science Institute, 2006. http://dx.doi.org/10.28945/2955.

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This paper discusses on the development of the Honeyd@WEB. Honeyd@WEB is a system that can deploy low-interaction, production, dynamic and manageable virtual honeypots via a web interface. It runs open source programs, such as P0f (a passive fingerprinting tool) and Honeyd (a low-interaction honeypot). Honeyd@WEB can automatically determine; how many honeypots to deploy, how to deploy them, and what they should look like to blend in with the environment. The first part of this paper highlights the basic security concepts of honeypot and honeynet. The second part of this paper explains the Hone
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Mokube, Iyatiti, and Michele Adams. "Honeypots." In the 45th annual southeast regional conference. ACM Press, 2007. http://dx.doi.org/10.1145/1233341.1233399.

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Katakwar, Harsh, Palvi Aggarwal, and Varun Dutt. "Modeling the effects of different honeypot proportions in a deception-based security game." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003727.

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Cyber-attacks, an intentional effort to steal information or interrupt the network, are growing dramatically. It is of great importance to understand how an adversary’s behavior might impact the detection of threats. Prior research in adversarial cybersecurity has investigated the effect of different honeypot variations on adversarial decisions in a deception-based game experimentally. However, it is unknown how different honeypot variation affects adversarial decisions using cognitive models. The primary objective of this research is to develop the cognitive model using Instance-based learnin
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Al-Gharabally, Noor, Nosayba El-Sayed, Sara Al-Mulla, and Imtiaz Ahmad. "Wireless honeypots." In the 2009 conference. ACM Press, 2009. http://dx.doi.org/10.1145/1551950.1551969.

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Gonçalves, Pamela Moura, Fabiano da Silva Santos, Fernando Guerreiro Chemello, and Roben Castagna Lunardi. "Avaliação e comparação de honeypots: auxiliando administradores de rede na escolha e adoção." In Escola Regional de Redes de Computadores. Sociedade Brasileira de Computação - SBC, 2024. https://doi.org/10.5753/errc.2024.4683.

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Honeypots podem simular vulnerabilidades em hosts para atrair e detectar possíveis atacantes, possibilitando a análise e estudo de comportamentos maliciosos. Este trabalho tem como objetivo apresentar um trabalho em andamento onde avaliamos diferentes honeypots. Neste trabalho, consideramos diversos aspectos dos honeypots, desde seu funcionamento até sua adequação para uso. Para isso, utilizaremos uma honeynet chamada T-pot para facilitar o uso e comparação destes honeypots. Desta forma, demonstraremos alguns de pontos fortes e fracos dos honeypots e o quanto eles podem ser eficientes para sup
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Reports on the topic "Honeypots"

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Acosta, Jaime, and Valeria Duron. Hands-on Cybersecurity Studies: Network Diversification with Honeypots. DEVCOM Army Research Laboratory, 2022. http://dx.doi.org/10.21236/ad1180067.

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Johnson, Jay, Louis Jencka, Timothy Ortiz, et al. Design Considerations for Distributed Energy Resource Honeypots and Canaries. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1821540.

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Acosta, Jaime. Hands-on Cybersecurity Studies: Network Diversification Through Dynamic Honeypots. DEVCOM Army Research Laboratory, 2023. http://dx.doi.org/10.21236/ad1203864.

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