Virtual Public Cloud Model in Honeypot for Data Security

Saxena, Apurva; Ubnare, Gaurav; Dubey, Anubha

doi:10.1145/3330482.3330516

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…In 2019, Saxena, M.A., et al [19] proposed a cloud-based solution for a high-engagement honeypot with EFS (Elastic File System), VPN (Virtual Private Network), VPC (Virtual Private Cloud), and Kerberos as a service to provide network/data security. It would be easy to operate, safe, and cost-effective.…”

Section: Literature Reviewmentioning

confidence: 99%

R2NET: Storage and Analysis of Attack Behavior Patterns

2023

KSII TIIS

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Cloud computing has evolved significantly, intending to provide users with fast, dependable, and low-cost services. With its development, malicious users have become increasingly capable of attacking both its internal and external security. To ensure the security of cloud services, encryption, authorization, firewalls, and intrusion detection systems have been employed. However, these single monitoring agents, are complex, time-consuming, and they do not detect ransomware and zero-day vulnerabilities on their own. An innovative Record and Replay-based hybrid Honeynet (R2NET) system has been developed to address this issue. Combining honeynet with Record and Replay (RR) technology, the system allows fine-grained analysis by delaying time-consuming analysis to the replay step. In addition, a machine learning algorithm is utilized to cluster the logs of attackers and store them in a database. So, the accessing time for analyzing the attack may be reduced which in turn increases the efficiency of the proposed framework. The R2NET framework is compared with existing methods such as EEHH net, HoneyDoc, Honeynet system, and AHDS. The proposed system achieves 7.60%, 9.78%%, 18.47%, and 31.52% more accuracy than EEHH net, HoneyDoc, Honeynet system, and AHDS methods.

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Section: Literature Reviewmentioning

confidence: 99%

R2NET: Storage and Analysis of Attack Behavior Patterns

2023

KSII TIIS

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“…Since the honeypots are mostly placed inside the firewall program, they are used to secure the system from intruders from corporate organizations. A honeypot is a trap designed to deceive an intruder by disrupting an information system in an organization [92]. It can be used as early warning and advanced security monitoring tools to minimize the risk of attacks on IT systems and networks.…”

Section: Honeypotmentioning

confidence: 99%

Cyberattacks and Security of Cloud Computing: A Complete Guideline

Dawood,

Tu,

Xiao

et al. 2023

Symmetry

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Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, key exposure, auditing, privacy preservability, and cloud-assisted IoT applications. We then propose security attacks and countermeasures specifically for the different cloud models based on the security trends and problems. In the end, we pinpoint some of the futuristic directions and implications relevant to the security of cloud models. The future directions will help researchers in academia and industry work toward cloud computing security.

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“…Accordingly, a few researchers have oriented their analysis and studies towards cloud infrastructures. For instance, the authors of [21] have developed a high interaction system using Kerberos authentication, Virtual Private Cloud, and Elastic File System to understand the malicious nature of attackers; the authors of [13] have developed honeypot as a service model for luring attackers. This honeypot-as-aservice is implemented as a plug-and-play model, which could be hosted on gateways for capturing the malicious attackers; and, a few practitioners have listed the AWS honeypot data that suggested potential hackers, who attempted to maliciously attack AWS cloud services, including AWS IoT services.…”

Section: Honeypot Research -Domains Placements and Cloudsmentioning

confidence: 99%

EA-POT: An Explainable AI Assisted Blockchain Framework for HoneyPot IP Predictions

Benedict¹

2022

Acta Cybern

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The culpable cybersecurity practices that threaten leading organizations are logically prone to establishing countermeasures, including HoneyPots, and bestow research innovations in various dimensions such as ML-enabled threat predictions. This article proposes an explainable AI-assisted permissioned blockchain framework named EA-POT for predicting potential defaulters' IP addresses. EA-POT registers the predicted defaulters based on the suggestions levied by explainable AI and the approval of IP authorizers to blockchain database to enhance immutability. Experiments were carried out at IoT Cloud Research laboratory using three prediction models such as Random Forest Modeling (RFM), Linear Regression Modeling (LRM), and Support Vector Machines (SVM); and, the observed experimental results for predicting the AWS HoneyPots were explored. The proposed EA-POT framework revealed the procedure to include interpretable knowledge while blacklisting IPs that reach HoneyPots.

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Virtual Public Cloud Model in Honeypot for Data Security

Cited by 5 publications

References 16 publications

R2NET: Storage and Analysis of Attack Behavior Patterns

R2NET: Storage and Analysis of Attack Behavior Patterns

Cyberattacks and Security of Cloud Computing: A Complete Guideline

EA-POT: An Explainable AI Assisted Blockchain Framework for HoneyPot IP Predictions

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