The Impact of DDoS Attacks on the Power Usage of Virtual Execution Environments

White, Austin; Galloway, Michael; boyle, Patrick O; Wyllie, Sierra

doi:10.1109/southeastcon45413.2021.9401839

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…In power system environment, with the access of a large number of service terminals, the data information of individual sensitive user nodes is easy to leak, which leads to the control rationality of information authentication instruction decline greatly. Due to the diversity of equipment and applications, power systems are becoming the main targets of cyberattacks such as DDoS [3] attacks, insider attacks [4], ransomware, fraud bureaus, etc. Unauthenticated attackers can pose a great challenge to the security of the power system through illegal access.…”

Section: Introductionmentioning

confidence: 99%

An anonymous authentication mechanism based on zero-knowledge proof for power system

Liu

Zhang

Jiang

et al. 2023

Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023)

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With the application of new technologies such as Internet of things and big data in smart grid industry, new power systems based on new energy sources have emerged in response to the call of "Peak carbon, carbon neutrality". The power grid enterprise concentrates the data assets and business access to the data external service, which needs to connect a large number of data sources. Ensuring the authenticity of the data without tampering becomes a big challenge. The power system adopts the identity authentication mechanism to resist the security attack and protect the sensitive data. However, in the process of user authentication, the sending of real identity information will lead to the reduction of system privacy, which is easy to cause the leakage of sensitive data. This paper proposes an anonymous authentication mechanism based on zero-knowledge proof for power system, which authenticates the server without revealing the identity. This mechanism uses zero-knowledge proof algorithm to design an anonymous authentication protocol framework, which consists of three stages: registration, mutual authentication and revocation. In this method, anonymous certificate and elliptic curve encryption technology are used to realize the anonymity and authenticity of users. The mechanism effectively protects the user's real identity information and maintains the sensitive data in the power system.

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Section: Introductionmentioning

confidence: 99%

An anonymous authentication mechanism based on zero-knowledge proof for power system

Liu

Zhang

Jiang

et al. 2023

Second International Symposium on Computer Applications and Information Systems (ISCAIS 2023)

View full text Add to dashboard Cite

show abstract

A Step Towards Generation of DoS/DDoS Attacks Dataset for Docker-Centric Computing

Tomar

Mishra

Bisht

et al. 2022

Int J Math, Eng, Manag Sci

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Docker provides an effective containerized environment for modern computing. However, the security issues present in Docker provide an edge to the attackers thus resulting in various attacks. Denial of Service (DoS) and Distributed Denial of Service (DDoS) are the common ones. In this paper, DoS and DDoS attack datasets have been generated using realistic testbed environments as older datasets have their own set of limitations, making them insufficient for today’s computing. An architectural framework is provided to depict the process of packet capturing and feature extraction. A total of 45 features are extracted using Flowtbag among which 17 best features are selected using the average correlation coefficient. Six machine learning algorithms namely Logistic Regression (LR), Naïve Bayes (NB), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM) are applied on datasets with full features and selected features to obtain accuracy, precision, recall, and F1 score. NB gave the lowest accuracy of 0.94917 on full features and DT provided the most accurate results with a performance matrix of 0.99254 accuracy, 0.997 precision, 0.998 recall, and 0.997 F1 Score. Whereas on selected features, accuracies of both the algorithms increased to 0.962434 and 0.992703 respectively.

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The Impact of DDoS Attacks on the Power Usage of Virtual Execution Environments

Cited by 2 publications

References 10 publications

An anonymous authentication mechanism based on zero-knowledge proof for power system

An anonymous authentication mechanism based on zero-knowledge proof for power system

A Step Towards Generation of DoS/DDoS Attacks Dataset for Docker-Centric Computing

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