2022 6th International Conference on Cryptography, Security and Privacy (CSP)最新文献_第3页

Context-based Adblocker using Siamese Neural Network 基于上下文的广告拦截使用暹罗神经网络

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00019

Shawn Collins, Emily Wu, R. Ning

引用次数: 0

The Future Roadmap for Cyber-attack Detection 网络攻击检测的未来路线图

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00021

Raha Soleymanzadeh, R. Kashef

引用次数: 2

IoTProtect: A Machine-Learning Based IoT Intrusion Detection System IoTProtect:基于机器学习的物联网入侵检测系统

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00020

M. Alani

引用次数: 2

CoAP-DoS: An IoT Network Intrusion Data Set CoAP-DoS:物联网网络入侵数据集

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00025

Jared Mathews, Prosenjit Chatterjee, S. Banik

引用次数: 2

Cyber Threat Analysis and Trustworthy Artificial Intelligence 网络威胁分析与可信赖人工智能

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00024

S. Wang, Md Tanvir Arafin, O. Osuagwu, K. Wandji

{"title":"Cyber Threat Analysis and Trustworthy Artificial Intelligence","authors":"S. Wang, Md Tanvir Arafin, O. Osuagwu, K. Wandji","doi":"10.1109/CSP55486.2022.00024","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00024","url":null,"abstract":"Cyber threats can cause severe damage to computing infrastructure and systems as well as data breaches that make sensitive data vulnerable to attackers and adversaries. It is therefore imperative to discover those threats and stop them before bad actors penetrating into the information systems.Threats hunting algorithms based on machine learning have shown great advantage over classical methods. Reinforcement learning models are getting more accurate for identifying not only signature-based but also behavior-based threats. Quantum mechanics brings a new dimension in improving classification speed with exponential advantage. The accuracy of the AI/ML algorithms could be affected by many factors, from algorithm, data, to prejudicial, or even intentional. As a result, AI/ML applications need to be non-biased and trustworthy.In this research, we developed a machine learning-based cyber threat detection and assessment tool. It uses two-stage (both unsupervised and supervised learning) analyzing method on 822,226 log data recorded from a web server on AWS cloud. The results show the algorithm has the ability to identify the threats with high confidence.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128106724","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

Spectrum-based Fingerprint Extraction and Identification Method of 100M Ethernet Card 基于频谱的100M以太网卡指纹提取与识别方法

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00027

Jiaqi Liu, A. Hu, Sheng Li

{"title":"Spectrum-based Fingerprint Extraction and Identification Method of 100M Ethernet Card","authors":"Jiaqi Liu, A. Hu, Sheng Li","doi":"10.1109/CSP55486.2022.00027","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00027","url":null,"abstract":"In the local area network (LAN) system, most terminals are connected to edge switches through fast or gigabit Ethernet connections. The terminal access security problem has always been a key concern. This paper proposes a method of Ethernet card fingerprint extraction and identification based on spectrum characteristics, which solves the problem of illegal terminal access with counterfeit media access control (MAC) addresses. The extracted Ethernet card fingerprint is used as the identity of the terminal, which is unique and difficult to be counterfeited. The frequency-domain features of the signals can be extracted by analyzing the Ethernet card signals of wired terminals received by the switch. The dimension of these features is reduced to obtain their Ethernet card fingerprints, which can be effectively classified and identified. In the classification and recognition experiments on 7 Ethernet cards of 100M produced by the same manufacturer, 26 Ethernet cards by different manufacturers, and 65 Ethernet cards by mixed manufacturers, all Ethernet cards can achieve an accuracy of 100%. This method can be widely used for identity authentication during the access and connection of terminals and provides a secure access control scheme.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129401880","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

Blockchain-based identity dicovery between heterogenous identity management systems 异构身份管理系统之间基于区块链的身份发现

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00032

M. Dabrowski, P. Pacyna

{"title":"Blockchain-based identity dicovery between heterogenous identity management systems","authors":"M. Dabrowski, P. Pacyna","doi":"10.1109/CSP55486.2022.00032","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00032","url":null,"abstract":"Identity Management Systems (IdMS) have seemingly evolved in recent years, both in terms of modelling approach and in terms of used technology. The early centralized, later federated and user-centric Identity Management (IdM) was finally replaced by Self-Sovereign Identity (SSI). Solutions based on Distributed Ledger Technology (DLT) appeared, with prominent examples of uPort, Sovrin or ShoCard. In effect, users got more freedom in creation and management of their identities. IdM systems became more distributed, too. However, in the area of interoperability, dynamic and ad-hoc identity management there has been almost no significant progress. Quest for the best IdM system which will be used by all entities and organizations is deemed to fail. The environment of IdM systems is, and in the near future will still be, heterogenous. Therefore a person will have to manage her or his identities in multiple IdM systems. In this article authors argument that future-proof IdM systems should be able to interoperate with each other dynamically, i.e. be able to discover existence of different identities of a person across multiple IdM systems, dynamically build trust relations and be able to translate identity assertions and claims across various IdM domains. Finally, authors introduce identity relationship model and corresponding identity discovery algorithm, propose IdMS-agnostic identity discovery service design and its implementation with use of Ethereum and Smart Contracts.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"28 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120853183","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: 0

The AILA Methodology for Automated and Intelligent Likelihood Assignment 自动智能似然分配的AILA方法

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2022-01-01 DOI: 10.1109/CSP55486.2022.00030

G. Bella, Cristian Daniele, Mario Raciti

{"title":"The AILA Methodology for Automated and Intelligent Likelihood Assignment","authors":"G. Bella, Cristian Daniele, Mario Raciti","doi":"10.1109/CSP55486.2022.00030","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00030","url":null,"abstract":"Risk assessment is core to any institution's evaluation of risk, notably for what concerns people's privacy. The assessment often relies on information stated in a policy shaped as a text document. The risk assessor, or analyst in brief, is called to understand documentation that can be long, unclear or incomplete, hence subjectivity or distraction may strongly influence the process, particularly for identifying each relevant asset and for the assignment of the likelihood value of a given threat to an identified asset. The aim of this paper is to reduce the influence of subjectivity and distraction through risk assessment by means of our methodology for the Automated and Intelligent Likelihood Assignment (AILA). While the analyst's role cannot be emptied, it is facilitated through entities identification and likelihood assignment to threats for assets. The methodology adopts Natural Language Processing for summarisation and entity recognition, it tailors fully-supervised Machine Learning over policy documents and it leverages an existing tool supporting risk assessment, PILAR, in order to gain a more objective likelihood assignment. The paper demonstrates AILA over three real-world case studies from the automotive domain, culminating with the risk assessment exercises over the privacy policies of Toyota, Mercedes and Tesla. The executable components of AILA, the AILA Entity Extractor and the AILA Classifier are released as open source.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132992441","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: 1

Electromagnetic Side-Channel Attack Resilience against PRESENT Lightweight Block Cipher 针对当前轻量级分组密码的电磁侧信道攻击弹性

2022 6th International Conference on Cryptography, Security and Privacy (CSP) Pub Date : 2021-12-22 DOI: 10.1109/CSP55486.2022.00018

N. Gunathilake, A. Al-Dubai, W. Buchanan, O. Lo

{"title":"Electromagnetic Side-Channel Attack Resilience against PRESENT Lightweight Block Cipher","authors":"N. Gunathilake, A. Al-Dubai, W. Buchanan, O. Lo","doi":"10.1109/CSP55486.2022.00018","DOIUrl":"https://doi.org/10.1109/CSP55486.2022.00018","url":null,"abstract":"Lightweight cryptography is a novel diversion from conventional cryptography that targets internet-of-things (IoT) platform due to resource constraints. In comparison, it offers smaller cryptographic primitives such as shorter key sizes, block sizes and lesser energy drainage. The main focus can be seen in algorithm developments in this emerging subject. Thus, verification is carried out based upon theoretical (mathematical) proofs mostly. Among the few available side-channel analysis studies found in literature, the highest percentage is taken by power attacks. PRESENT is a promising lightweight block cipher to be included in IoT devices in the near future. Thus, the emphasis of this paper is on lightweight cryptology, and our investigation shows unavailability of a correlation electromagnetic analysis (CEMA) of it. Hence, in an effort to fill in this research gap, we opted to investigate the capabilities of CEMA against the PRESENT algorithm. This work aims to determine the probability of secret key leakage with a minimum number of electromagnetic (EM) waveforms possible. The process initially started from a simple EM analysis (SEMA) and gradually enhanced up to a CEMA. This paper presents our methodology in attack modelling, current results that indicate a probability of leaking seven bytes of the key and upcoming plans for optimisation. In addition, introductions to lightweight cryptanalysis and theories of EMA are also included.","PeriodicalId":187713,"journal":{"name":"2022 6th International Conference on Cryptography, Security and Privacy (CSP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133858453","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