Proceedings of the 17th International Conference on Availability, Reliability and Security最新文献_第4页

Joint Security-vs-QoS Framework: Optimizing the Selection of Intrusion Detection Mechanisms in 5G networks 联合安全vs qos框架:优化5G网络入侵检测机制选择

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3544480

Arash Bozorgchenani, Charilaos C. Zarakovitis, S. Chien, Heng-Siong Lim, Q. Ni, Antonios Gouglidis, Wissam Mallouli

{"title":"Joint Security-vs-QoS Framework: Optimizing the Selection of Intrusion Detection Mechanisms in 5G networks","authors":"Arash Bozorgchenani, Charilaos C. Zarakovitis, S. Chien, Heng-Siong Lim, Q. Ni, Antonios Gouglidis, Wissam Mallouli","doi":"10.1145/3538969.3544480","DOIUrl":"https://doi.org/10.1145/3538969.3544480","url":null,"abstract":"The advent of 5G technology introduces new - and potentially undiscovered - cybersecurity challenges, with unforeseen impacts on our economy, society, and environment. Interestingly, Intrusion Detection Mechanisms (IDMs) can provide the necessary network monitoring to ensure - to a big extent - the detection of 5G-related cyberattacks. Yet, how to realize the attack surface of 5G networks with respect to the detected risks, and, consequently, how to optimize the cybersecurity levels of the network, remains an open critical challenge. In respect, this work focuses on deploying multiple distributed Security Agents (SAs) that can run different IDMs over various network components and proposes a cybersecurity mechanism for optimizing the network’s attack surface with respect to the Quality of Service (QoS). The proposed approach relies on a new closed-form utility function to describe the trade-off between cybersecurity and QoS and uses multi-objective optimization to improve the selection of each SA detection level. We demonstrate via simulations that before optimization, an increase in the detection level of SAs brings a direct decrease in QoS as more computational, bandwidth and monetary resources are utilized for IDM processing. Thereby, after optimization, we demonstrate that our mechanism can strike a balance between cybersecurity and QoS while showcasing the impact of the importance of different objectives of the joint optimization.","PeriodicalId":306813,"journal":{"name":"Proceedings of the 17th International Conference on Availability, Reliability and Security","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124693534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Rumor and clickbait detection by combining information divergence measures and deep learning techniques 结合信息发散度量和深度学习技术的谣言和标题党检测

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3543791

Christian Oliva, Ignacio Palacio Marín, L. F. Lago-Fernández, David Arroyo

引用次数: 1

Fraudulent Activities in the Cyber Realm: DEFRAUDify Project: Fraudulent Activities in the Cyber Realm: DEFRAUDify Project 网络领域的欺诈活动:DEFRAUDify项目:网络领域的欺诈活动:DEFRAUDify项目

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3544434

Razvan-Alexandru Bratulescu, Robert-Ionut Vatasoiu, Sorina-Andreea Mitroi, G. Suciu, Mari-Anais Sachian, Daniel-Marian Dutu, Serban-Emanuel Calescu

引用次数: 2

BISCUIT - Blockchain Security Incident Reporting based on Human Observations 基于人类观察的区块链安全事件报告

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3538984

B. Putz, Manfred Vielberth, G. Pernul

引用次数: 0

Introducing Quantum Computing in Mobile Malware Detection 量子计算在移动恶意软件检测中的应用

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3543816

Giovanni Ciaramella, Giacomo Iadarola, F. Mercaldo, Marco Storto, A. Santone, Fabio Martinelli

{"title":"Introducing Quantum Computing in Mobile Malware Detection","authors":"Giovanni Ciaramella, Giacomo Iadarola, F. Mercaldo, Marco Storto, A. Santone, Fabio Martinelli","doi":"10.1145/3538969.3543816","DOIUrl":"https://doi.org/10.1145/3538969.3543816","url":null,"abstract":"Mobile malware are increasing their complexity to be able to evade the current detection mechanism by gathering our sensitive and private information. For this reason, an active research field is represented by malware detection, with a great effort in the development of deep learning models starting from a set of malicious and legitimate applications. The recent introduction of quantum computing made possible quantum machine learning i.e., the integration of quantum algorithms within machine learning algorithms. In this paper, we propose a comparison between several deep learning models, by taking into account also a hybrid quantum malware detector. We explore the effectiveness of different architectures for malicious family detection in the Android environment: LeNet, AlexNet, a Convolutional Neural Network model designed by authors, VGG16 and a Hybrid Quantum Convolutional Neural Network i.e., a model where the first layer is a quantum convolution that uses transformations in circuits to simulate the behavior of a quantum computer. Experiments performed on a real-world dataset composed of 8446 Android malicious and legitimate applications allow us to compare the various models, with particular regard to the quantum model concerning the other ones.","PeriodicalId":306813,"journal":{"name":"Proceedings of the 17th International Conference on Availability, Reliability and Security","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121501655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Image-based Neural Network Models for Malware Traffic Classification using PCAP to Picture Conversion 基于图像神经网络模型的恶意软件流量分类使用PCAP到图片转换

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3544473

Georgios Agrafiotis, Eftychia Makri, Ioannis Flionis, Antonios Lalas, K. Votis, D. Tzovaras

{"title":"Image-based Neural Network Models for Malware Traffic Classification using PCAP to Picture Conversion","authors":"Georgios Agrafiotis, Eftychia Makri, Ioannis Flionis, Antonios Lalas, K. Votis, D. Tzovaras","doi":"10.1145/3538969.3544473","DOIUrl":"https://doi.org/10.1145/3538969.3544473","url":null,"abstract":"Traffic categorization is considered of paramount importance in the network security sector, as well as the first stage in network anomaly detection, or in a network-based intrusion detection system (IDS). This paper introduces an artificial intelligence (AI) network traffic classification pipeline, including the employment of state-of-the-art image-based neural network models, namely Vision Transformers (ViT) and Convolutional Neural Networks (CNN), whereas the primary element of this pipeline is the transformation of raw traffic data into grayscale pictures introducing a properly developed IDS-Vision Toolkit as well. This approach extracts characteristics from network traffic data without requiring domain expertise and could be easily adapted to new network protocols and technologies (i.e. 5G). Furthermore, the proposed method was tested on the CIC-IDS-2017 dataset and compared to a well-known feature extraction strategy on the same dataset. Finally, it surpasses all suggested binary classification algorithms for the CIC-IDS-2017 dataset to the best of our knowledge, paving the path for further exploitation in the 5G domain to successfully address related cybersecurity challenges.","PeriodicalId":306813,"journal":{"name":"Proceedings of the 17th International Conference on Availability, Reliability and Security","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131469899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Improving Network, Data and Application Security for SMEs 提高中小企业网络、数据和应用安全

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3544426

C. Tselios, Ilias Politis, C.K. Xenakis

引用次数: 0

Improving Security and Scalability in Smart Grids using Blockchain Technologies 使用区块链技术提高智能电网的安全性和可扩展性

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3544441

Mandana Falahi, A. Vasilățeanu, N. Goga, G. Suciu, Mari-Anais Sachian, Robert Florescu, Ștefan-Daniel Stanciu

引用次数: 1

Forensic analysis of Tor in Windows environment: A case study Windows环境下Tor的取证分析:一个案例研究

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3543808

Vaia-Maria Angeli, Ahmad Atamli-Reineh, Erisa Karafili

引用次数: 0

A Quantitative Assessment of the Detection Performance of Web Vulnerability Scanners Web漏洞扫描器检测性能的定量评估

Proceedings of the 17th International Conference on Availability, Reliability and Security Pub Date : 2022-08-23 DOI: 10.1145/3538969.3544416

Emma Lavens, Pieter Philippaerts, W. Joosen

引用次数: 0