2021 16th Asia Joint Conference on Information Security (AsiaJCIS)最新文献

Which Packet Did They Catch? Associating NIDS Alerts with Their Communication Sessions 他们抓住了哪个包?将NIDS警报与其通信会话关联

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00012

Ryosuke Ishibashi, Hiroki Goto, Chansu Han, Tao Ban, Takeshi Takahashi, Jun’ichi Takeuchi

{"title":"Which Packet Did They Catch? Associating NIDS Alerts with Their Communication Sessions","authors":"Ryosuke Ishibashi, Hiroki Goto, Chansu Han, Tao Ban, Takeshi Takahashi, Jun’ichi Takeuchi","doi":"10.1109/AsiaJCIS53848.2021.00012","DOIUrl":"https://doi.org/10.1109/AsiaJCIS53848.2021.00012","url":null,"abstract":"Virtually every enterprise network has deployed intrusion detection systems (NIDSes) for security threats detection, prevention, and response. To defend against cyberattacks with increasing diversity and intensity, there is a pressing need to implement artificial intelligence (AI)-powered NIDS system which can unify the strength of existing solutions. In this paper, we explore the feasibility of leveraging existing security solutions to generate labeled datasets that can facilitate the development of such an advanced AI-powered NIDS. Assigning proper labels to communication sessions that are detected as suspicious by NIDSes are carried out in the following steps. First, from the captured packet file, we locate the communication sessions that trigger the detection rules of deployed NIDSes. Second, for each located communication session, we investigate the causal factors in the session packets and assign a unified alert-type label to it by taking account of information presented in multiple NIDS alerts associated with it. Finally, we output the packet data of the investigated communication sessions and their corresponding alert-type labels, which will be taken as input by AI-powered analysis engines. We demonstrate case studies to apply the proposed method to solve tasks such as creating labeled NIDS datasets, performance evaluation between different NIDSes, and automation of the security triage process.","PeriodicalId":134911,"journal":{"name":"2021 16th Asia Joint Conference on Information Security (AsiaJCIS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121495774","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

Improved Proxy Re-encryption Scheme with Equality Test 基于等式检验的改进代理重加密方案

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00016

Chih-Chen Yang, R. Tso, Zi-Yuan Liu, Jen-Chieh Hsu, Yi-Fan Tseng

引用次数: 2

A Privacy-Preserving Enforced Bill Collection System using Smart Contracts 使用智能合约的隐私保护强制账单收集系统

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00018

Tomoki Fujitani, K. Emura, Kazumasa Omote

{"title":"A Privacy-Preserving Enforced Bill Collection System using Smart Contracts","authors":"Tomoki Fujitani, K. Emura, Kazumasa Omote","doi":"10.1109/AsiaJCIS53848.2021.00018","DOIUrl":"https://doi.org/10.1109/AsiaJCIS53848.2021.00018","url":null,"abstract":"Maintaining a balance between anonymity and traceability is a fundamental issue in privacy-preserving systems. Isshiki et al. proposed an identity management system based on group signatures in which a service provider anonymously determines whether or not users of the service are legitimate members, and only a bill collector can identify users for the purposes of sending them invoices. It is particularly worth noting that, under the Isshiki system, the service provider is not required to manage personal information such as user lists, which allows the system to outperform other in terms of preserving user privacy and managing personal information leakage risk. It is also noteworthy that the Isshiki system only considers cases in which the bill collector identifies users who have used the service and that, in fact, identified users who ignore invoices can use the service for free. In this paper, we extended the Isshiki system by adding a smart contract-enabled enforcement bill collection functionality. Under this functionality, deposits made by users who do not pay a service fee are automatically transferred to the bill collector. Because of their centralized structure, group signatures are not suitable to blockchain systems, therefore, the proposed system employs accountable ring signatures as building blocks. The privacy-preserving enforced bill collection system is implemented using the accountable ring signature scheme developed by Bootle et al. and Ethereum smart contracts. To reduce the gas costs associated with running smart contracts, the smart contract is not run unless the user ignores an invoice, and basic procedures are run via an off-chain channel. To avoid the use of heavy cryptographic algorithms in carrying out the accountable ring signature scheme for running smart contracts, we employed standard elliptic curve digital signature algorithm (ECDSA) signatures without especially changing the state to be verified in smart contracts.","PeriodicalId":134911,"journal":{"name":"2021 16th Asia Joint Conference on Information Security (AsiaJCIS)","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121440272","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: 6

Multi-Level Privacy Preserving K-Anonymity 多级隐私保护k -匿名

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00019

J. Weng, Po-Wen Chi

引用次数: 1

A framework to protect National Cyber Borders in peace and war 一个在和平与战争中保护国家网络边界的框架

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00013

Nabeel Shakeel, Nadeem Kafi Khan

引用次数: 0

Vulnerability Exploiting SMS Push Notifications 利用SMS推送通知的漏洞

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00014

Rina Shibayama, Hiroaki Kikuchi

引用次数: 0

Identity-Based Signature from Quadratic Residues and Its Extension to ID-Based Multi-Signature 基于二次残数的身份签名及其在基于身份的多重签名中的推广

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00015

Yi-Fan Tseng, Jheng-Jia Huang

引用次数: 0

An Easy-to-use Framework to Build and Operate AI-based Intrusion Detection for In-situ Monitoring 一种易于使用的基于人工智能的现场监控入侵检测构建和操作框架

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00011

Ikje Choi, Jun Lee, Taewoong Kwon, Kyuil Kim, Yoonsu Choi, Jungsuk Song

{"title":"An Easy-to-use Framework to Build and Operate AI-based Intrusion Detection for In-situ Monitoring","authors":"Ikje Choi, Jun Lee, Taewoong Kwon, Kyuil Kim, Yoonsu Choi, Jungsuk Song","doi":"10.1109/AsiaJCIS53848.2021.00011","DOIUrl":"https://doi.org/10.1109/AsiaJCIS53848.2021.00011","url":null,"abstract":"With a paradigm shift to untact environments, security threats on the network also have been significantly increasing all over the world. To monitor and detect intrusion attempts under enormous network traffic, Security Operation Center (SOC) essentially exploits various security devices. Above all, Network Intrusion Detection System (NIDS) has been operated in public/private sectors as a spearhead to fight against cyber threats. In particular, state-of-the-art technologies, especially ML and AI, have been being studied to achieve quick and accurate intrusion detection. Despite much effort to guarantee a secure network, however, SOCs are still struggling for overcoming various types of threats as well as attacks of similar form with benign traffic. Even though the advanced techniques may find out a complex and unknown attack, operating and managing them in real-world situations cause counterproductively more pressure to agents in the SOC. In order to solve these difficulties, this study introduces an easy-to-use framework to build intrusion detection models based on AI techniques, as well as to operate them depending on a situation using a graphical user interface. The framework supports generating various types of AI- and ML-based intrusion detection models with optimized parameters by only a few steps. Furthermore, an interactive graphical interface makes it easier to manage detection models according to different threat situations. Finally, the performance of models made by the framework is evaluated in terms of accuracy, especially under the real-world SOC environment with live network traffic.","PeriodicalId":134911,"journal":{"name":"2021 16th Asia Joint Conference on Information Security (AsiaJCIS)","volume":"276 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129624788","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: 3

[Copyright notice] (版权)

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/asiajcis53848.2021.00003

引用次数: 0

A Privacy Preserving Scheme with Dimensionality Reduction for Distributed Machine Learning 面向分布式机器学习的降维隐私保护方案

2021 16th Asia Joint Conference on Information Security (AsiaJCIS) Pub Date : 2021-08-01 DOI: 10.1109/AsiaJCIS53848.2021.00017

Zhao Chen, Kazumasa Omote

引用次数: 5