Intrusion Detection and Prevention using Honeypot Network for Cloud Security

Negi, Poorvika Singh; Garg, Aditya; Lal, Roshan

doi:10.1109/confluence47617.2020.9057961

Cited by 32 publications

(7 citation statements)

References 7 publications

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“…Because the centralized server is connected to many ids. As presented in [19], A Honeypot detection was presented as a method of caring data and resources in a cloud over Honeypot by applying it over an infrastructure application (Cloud Environment). Honeypot is a detection and security device which is required to be tested, assaulted, or bargained.…”

Section: Related Workmentioning

confidence: 99%

A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

Said¹,

Mostafa²,

Hassan³

et al. 2022

Computers, Materials &Amp; Continua

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User's data is considered as a vital asset of several organizations. Migrating data to the cloud computing is not an easy decision for any organization due to the privacy and security concerns. Service providers must ensure that both data and applications that will be stored on the cloud should be protected in a secure environment. The data stored on the public cloud will be vulnerable to outside and inside attacks. This paper provides interactive multi-layer authentication frameworks for securing user identities on the cloud. Different access control policies are applied for verifying users on the cloud. A security mechanism is applied to the cloud application that includes user registration, granting user privileges, and generating user authentication factor. An intrusion detection system is embedded to the security mechanism to detect malicious users. The multi factor authentication, intrusion detection, and access control techniques can be used for ensuring the identity of the user. Finally, encryption techniques are used for protecting the data from being disclosed. Experimental results are carried out to verify the accuracy and efficiency of the proposed frameworks and mechanism. The results recorded high detection rate with low false positive alarms.

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Section: Related Workmentioning

confidence: 99%

A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

Said¹,

Mostafa²,

Hassan³

et al. 2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Low-interaction Honeypots [25] are limited to the degree of emulation offered by the honeypot; hence, the interaction between the attacker and honeypot system is low. ese honeypots offer few privileges to the intruder who will have a limited scope.…”

Section: Honeypotmentioning

confidence: 99%

A Smart Agent Design for Cyber Security Based on Honeypot and Machine Learning

Kamel

Eddabbah

Lmoumen

et al. 2020

Security and Communication Networks

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The development of Internet and social media contributes to multiplying the data produced on the Internet and the connected nodes, but the default installation and the configuration of variety of software systems represent some security holes and shortcomings, while the majority of Internet users have not really set up safety awareness, leading to huge security risks. With the development of network attack techniques, every host on the Internet has become the target of attacks. Therefore, the network information security cannot be ignored as a problem. To deal with 0-day and future attacks, the honeypot technique can be used not only passively as an information system, but also to reinforce the traditional defense systems against future attacks. In this paper, we present an introduction of machine learning and honeypot systems, and based on these technologies, we design a smart agent for cyber-attack prevention and prediction.

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“…These methods effectively improved the situation and significantly increased the difficulty and cost for attackers to launch their attacks. However, they still have limitations: honeypot technology requires a significant amount of prior knowledge from attackers [8], and MTD possesses time sensitivity and uncontrollability, and the high-frequency variability, particularly, leads to a decline in system performance [7].…”

Section: Introductionmentioning

confidence: 99%

Location-Aware Measurement for Cyber Mimic Defense: You Cannot Improve What You Cannot Measure

Huang,

Yuan,

et al. 2023

Applied Sciences

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Cyber mimic defense is designed to ensure endogenous security, effectively countering unknown vulnerabilities and backdoors, thereby addressing a significant challenge in cyberspace. However, the immense scale of real-world networks and their intricate topology pose challenges for measuring the efficacy of cyber mimic defense. To capture and quantify defense performance within specific segments of these expansive networks, we embrace a partitioning approach that subdivides large networks into smaller regions. Metrics are then established within an objective space constructed on these smaller regions. This approach enables the establishment of several fine-grained metrics that offer a more nuanced measurement of cyber mimic defense deployed in complex networks. For example, the common-mode index is introduced to highlight shared vulnerabilities among diverse nodes, the transfer probability computes the likelihood of risk propagation among nodes, and the failure risk assesses the likelihood of cyber mimic defense technology failure within individual nodes or entire communities. Furthermore, we provide proof of the convergence of the transfer probability. A multitude of simulations are conducted to validate the reliability and applicability of the proposed metrics.

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Intrusion Detection and Prevention using Honeypot Network for Cloud Security

Cited by 32 publications

References 7 publications

A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

A Multi-Factor Authentication-Based Framework for Identity Management in Cloud Applications

A Smart Agent Design for Cyber Security Based on Honeypot and Machine Learning

Location-Aware Measurement for Cyber Mimic Defense: You Cannot Improve What You Cannot Measure

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