{"title":"Deception Through Cloning against Web Site Attacks","authors":"Murat Arslan, Burak Çarıkçı, Y. M. Erten","doi":"10.1109/ISCTURKEY53027.2021.9654384","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654384","url":null,"abstract":"In this study, a deception-based solution to the web site attacks is proposed. No fake entity is created to attract the intruders. The suggested solution involves cloning the web site under attack after the intrusion is detected and diverting the attacker to this cloned web page. Intrusion detection system (IDS) is used for detecting the attacks and Docker is used as the virtualization technology to create the cloned web site. While the intruder is connected to the clone, information is gathered on her/his activities. The system is implemented and tested for different attack types, and performance measurements were carried out. The results show that the system implementation for static pages is feasible and the system performance is not significantly affected.","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126556039","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}
{"title":"Analysis of Encrypted Image Data with Deep Learning Models","authors":"Durmuş Özdemir, Dilek Çelik","doi":"10.1109/ISCTURKEY53027.2021.9654326","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654326","url":null,"abstract":"While various encryption algorithms ensure data security, it is essential to determine the accuracy and loss values and performance status in the analyzes made to determine encrypted data by deep learning. In this research, the analysis steps made by applying deep learning methods to encrypted cifar10 picture data are presented practically. The data was tried to be estimated by training with VGG16, VGG19, ResNet50 deep learning models. During this period, the network’s performance was tried to be measured, and the accuracy and loss values in these calculations were shown graphically.","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134320397","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}
{"title":"Implementation Analysis of Cryptography Toolbox in Hyperledger","authors":"A. Şimşek, Buse Taşci, Oguz Yayla","doi":"10.1109/ISCTURKEY53027.2021.9654413","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654413","url":null,"abstract":"Hyperledger was set up with the aim of being an open-source platform targeted at accelerating industry-wide collaboration hosted by The Linux Foundation for developing robust and dependable blockchain and distributed ledger-based technological platform that may be applied across several industry sectors to improve the efficiency, performance, and transactions of different business operations. For these purpose, various distributed ledger frameworks and libraries have been developed inside the platform. In this paper, the Ursa cryptographic library, which is one of the libraries being developed in this platform to offer its users with dependable, secure, user friendly and plug-able cryptographic applications, has been examined and the performances of both the anonymous identity creation process and the presented cryptographic algorithms are examined.","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124784141","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}
{"title":"The need for a systematic machine-learning process: A proposal via a mobile malware classification case study","authors":"Gürol Canbek","doi":"10.1109/ISCTURKEY53027.2021.9654378","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654378","url":null,"abstract":"Machine learning (ML) seems a highly promising solution for many problems in many domains including healthcare and cyber security. Researchers and practitioners try to make use of ML with high expectations of a return of investment in terms of not only money but also effort and time. Those expectations might become similar to “if your only tool is a hammer, then every problem looks like nails” mood. Conducting anML workflow efficiently and correctly is difficult to achieve in reality considering both ML challenges and domain-specific issues. Hence, the interaction and dependencies between ML and domain should be clearly addressed and the steps should be planned and conducted according to certain requirements. This study provides insights into achieving such goals through a systematic ML process that should be conducted from beginning to end. The systematic process is designed as a cycle with eight sub-processes going through introduced spaces (file, sample, class, feature, dataset, model, and finally metric spaces). The dataset quality analysis/comparison sub-process is specifically formed as a quality control gateway. The proposed process is explained via a case study of the Android mobile malware classification problem domain where practical and research problems, as well as possible solutions, are provided.","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116219715","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}
{"title":"Cyber Security of Internet Connected ICS/SCADA Devices and Services","authors":"Ísmail Erkek, E. Irmak","doi":"10.1109/ISCTURKEY53027.2021.9654285","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654285","url":null,"abstract":"The monitoring and control of automation systems in the most critical infrastructures are provided by industrial control systems (ICS). Because of the importance and criticality of these systems, they are likely to be exposed to some external and internal cyber threats. Especially if they have internet access, the cyber risks increase and these systems cause functional disorders. Within the scope of this study, search engines such as Shodan, Censys, Fofa, which are used to determine industrial control systems facing to internet access, have been examined and analyzed. Among them, an API for the Shodan search engine has been created. With the relevant API, industrial communication protocols and industrial control systems open to internet access have been extracted and usage statistics have been determined. In line with the information obtained, these communication protocols and systems have been analyzed and security recommendations have been made for industrial control systems open to internet access.","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131817088","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}
{"title":"Intrusion Detection and Classification Based on Deep Learning","authors":"Habibe Güler, Özlem Alpay","doi":"10.1109/ISCTURKEY53027.2021.9654280","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654280","url":null,"abstract":"Cyberattacks aiming to disrupt the confidentiality, integrity and availability of systems by penetrating the network infrastructure of organizations are becoming increasingly widespread. These attacks carried out by attackers cause anomalies in normally functioning networks. Detection of these intrusions have of great importance in the protection of networks. Basically, Network Intrusion Detection Systems are tools that prevent and detect malicious activities or policy violations against networks by monitoring network traffic. In the scope of this study, supervised learning classification-based RNN, LSTM and GRU algorithms for intrusion detection on networks are applied comparatively on the UNSW-NB15 dataset. The main objective of the study is to compare the success of deep learning algorithms and reach the most appropriate model for intrusion detection and classification. The accuracy values of the models are 98% and FPR values are 0.014, 0.011 and 0.011 for the RNN, LSTM and GRU models, respectively.","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131001707","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}
{"title":"ISCTURKEY 2021 Index","authors":"","doi":"10.1109/ISCTURKEY53027.2021.9654409","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654409","url":null,"abstract":"","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125924435","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}
{"title":"ISCTURKEY 2021 Committees","authors":"","doi":"10.1109/ISCTURKEY53027.2021.9654300","DOIUrl":"https://doi.org/10.1109/ISCTURKEY53027.2021.9654300","url":null,"abstract":"","PeriodicalId":383915,"journal":{"name":"2021 International Conference on Information Security and Cryptology (ISCTURKEY)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115141593","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}