Dynamic Distributed Honeypot Based on Blockchain

Shi, Leyi; Li, Yang; Liu, Lihua; Jia, Litao; Shan, Baoying; Chen, Honglong

doi:10.1109/access.2019.2920239

Cited by 36 publications

(25 citation statements)

References 35 publications

(34 reference statements)

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“…Based on our literature review, we found that there are not too many studies in this field; however, there are some rather promising achievements. 4,[16][17][18][19][20]…”

Section: • Firewallmentioning

confidence: 99%

A survey of new orientations in the field of vehicular cybersecurity, applying artificial intelligence based methods

Pethö

Török

Szalay

2021

Trans Emerging Tel Tech

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Nowadays, cybersecurity is an emerging research area in the automotive industry, and it is investigated by many different perspectives. Our article is a review of existing vehicular security solutions that covers the state-of-the-art and future research directions. This article is a new contribution to tutorials/surveys related to the vehicular cybersecurity domain with the latest details. We developed a database from 140 articles from the field of automotive security. In the database, we assigned specific attributes to every article (such as Web of Science Impact Factor or the number of citations). The data set was analyzed by the K-means clustering and decision tree analysis methods to identify and characterize the generated groups of papers. Following this, the article highlights the research areas that might receive more attention in the future.

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“…Based on our literature review, we found that there are not too many studies in this field; however, there are some rather promising achievements. 4,[16][17][18][19][20]…”

Section: • Firewallmentioning

confidence: 99%

A survey of new orientations in the field of vehicular cybersecurity, applying artificial intelligence based methods

Pethö

Török

Szalay

2021

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…HoneyDOC consists of collaborative modules such as decoy, captor, and orchestrator. Shi et al [6] proposed a blockchain-based Honeypot, which uses a dynamic mechanism of combining the functionalities of Low and High interaction Honeypot. Their work consists of a real system in time architecture that is widely used to capture real-time attacks.…”

Section: A Honeypotmentioning

confidence: 99%

Design of Intrusion Detection Honeypot Using Social Leopard Algorithm to Detect IoT Ransomware Attacks

et al. 2020

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In recent times, ransomware has become the most significant cyber-attack targeting individuals, enterprises, healthcare industries, and the Internet of Things (IoT). Existing security systems like Intrusion Detection and Prevention System (IDPS) and Anti-virus (AV) as a single monitoring agent is complicated and timeconsuming, thus fails in ransomware detection. A robust Intrusion Detection Honeypot (IDH) is proposed to address the issues mentioned above. IDH consists of i) Honeyfolder, ii) Audit Watch, and iii) Complex Event Processing (CEP). Honeyfolder is a decoy folder modeled using Social Leopard Algorithm (SoLA), especially for getting attacked and acting as an early warning system to alert the user during the suspicious file activities. AuditWatch is an Entropy module that verifies the entropy of the files and folders. CEP engine is used to aggregate data from different security systems to confirm the ransomware behavior, attack pattern, and promptly respond to them. The proposed IDH is experimentally tested in a secured testbed using more than 20 variants of recent ransomware of all types. The experimental result confirms that the proposed IDH significantly improves the ransomware detection time, rate, and accuracy compared with the existing state of the art ransomware detection model.

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“…To reduce the false alarm rate of the detection system, Meng et al [37] designed a hierarchical framework to mine high-threat alerts from a large number of alarm logs, to provide available information for the management system to modify the judgment policy. In [38], the authors developed a dynamic distributed honeypot and combined it with the Blockchain platform, to discover attacks and resist anti-honeypot technology in time. This scheme achieved high reliability, high security, and low response time.…”

Section: Security Monitoring and Surveillance Technologymentioning

confidence: 99%

A Smart Collaborative Authentication Framework for Multi-Dimensional Fine-Grained Control

Liu

et al. 2020

IEEE Access

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The emergence of the 5G network has brought broad prospects for the massive terminal access and ubiquitous Internet of Things (IoTs). Potential attacking opportunities triggered by this progress are severely impacting the security fortress of current networks, especially in the edge access part. However, due to the unitary protection and inferior isolation, available security schemes are incapable of effectively eliminating these hidden perils. Motivated by these facts, we propose a Multi-dimensional Fine-grained Control (MFC) framework to strengthen safety and reliability in Radio Access Networks (RANs). First, we comprehensively survey and summarize the existing security schemes to grasp respective effects and limitations. Second, the MFC framework is established to describe the model structure and implementation processes. An identifier mapping mechanism is designed to achieve network isolation. We perform the security analysis of MFC by theoretically comparing diversified policies. Third, an integrated set of the authentication prototype system is created with wireless environment parameters settings. Specific verification scenarios are illustrated. Finally, we test the performances of the MFC framework. Validation results demonstrate that the proposed scheme can accomplish reliable security control at the access side. Comparing to multiple schemes, the performances, in terms of time and concurrency, are optimized. Therefore, the MFC framework is feasible for applications in 5G or IoT.

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Dynamic Distributed Honeypot Based on Blockchain

Cited by 36 publications

References 35 publications

A survey of new orientations in the field of vehicular cybersecurity, applying artificial intelligence based methods

A survey of new orientations in the field of vehicular cybersecurity, applying artificial intelligence based methods

Design of Intrusion Detection Honeypot Using Social Leopard Algorithm to Detect IoT Ransomware Attacks

A Smart Collaborative Authentication Framework for Multi-Dimensional Fine-Grained Control

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