2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP)最新文献_第3页

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2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/isea-isap49340.2020.9079323

引用次数: 0

A secured land registration framework on Blockchain 基于区块链的担保土地注册框架

2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/ISEA-ISAP49340.2020.235011

Meghali Nandi, R. Bhattacharjee, Amrit Kumar Jha, F. Barbhuiya

{"title":"A secured land registration framework on Blockchain","authors":"Meghali Nandi, R. Bhattacharjee, Amrit Kumar Jha, F. Barbhuiya","doi":"10.1109/ISEA-ISAP49340.2020.235011","DOIUrl":"https://doi.org/10.1109/ISEA-ISAP49340.2020.235011","url":null,"abstract":"Land is an immovable and non-liquid asset having high value. The integrity and proper track of ownership/transfer records of land is a highly challenging task. As the ownership of land can constantly change over time and that too sometimes very frequently, it poses a daunting task of keeping elaborate and long ownership transfer records. The problem further escalates due to presence of fraudulent or incomplete registries which are very difficult to trace back through time. Thus ownership disputes in the system, lead to litigation running for years, leading to wastage of valuable time, energy and resource for solving these disputes. Most of the issues root from the problem of the current land registration systems being either having legacy paper document trails or from poorly kept non-transparent centralized systems. Fraudulent users may try to forge paper documents or modify electronic records to change the land ownership record. This paper proposes a secure record keeping mechanism that addresses these issues using a Blockchain based system which can create record for the physical assets into an immutable liquid Blockchain based token asset. This new block chain token asset can now be used to keep a digitally secured and selectively visible record of ownership, solving the mentioned issues. An implementation of this system has been done using Ethereum and the benchmark data shows that the transaction processing time of such a system is reasonably low thereby making it suitable for practical implementation.","PeriodicalId":235855,"journal":{"name":"2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127619173","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: 15

Implementation of AES Using Composite Field Arithmetic for IoT Applications 在物联网应用中使用复合场算法实现AES

2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/ISEA-ISAP49340.2020.235009

Thockchom Birjit Singha, R. P. Palathinkal, S. Ahamed

引用次数: 0

Detection of DDoS Attack and Classification Using a Hybrid Approach 基于混合方法的DDoS攻击检测与分类

2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/ISEA-ISAP49340.2020.234999

Suman Nandi, S. Phadikar, K. Majumder

{"title":"Detection of DDoS Attack and Classification Using a Hybrid Approach","authors":"Suman Nandi, S. Phadikar, K. Majumder","doi":"10.1109/ISEA-ISAP49340.2020.234999","DOIUrl":"https://doi.org/10.1109/ISEA-ISAP49340.2020.234999","url":null,"abstract":"In the area of cloud security, detection of DDoS attack is a challenging task such that legitimate users use the cloud resources properly. So in this paper, detection and classification of the attacking packets and normal packets are done by using various machine learning classifiers. We have selected the most relevant features from NSL KDD dataset using five (Information gain, gain ratio, chi-squared, ReliefF, and symmetrical uncertainty) commonly used feature selection methods. Now from the entire selected feature set, the most important features are selected by applying our hybrid feature selection method. Since all the anomalous instances of the dataset do not belong to DDoS category so we have separated only the DDoS packets from the dataset using the selected features. Finally, the dataset has been prepared and named as KDD DDoS dataset by considering the selected DDoS packets and normal packets. This KDD DDoS dataset has been discretized using discretize tool in weka for getting better performance. Finally, this discretize dataset has been applied on some commonly used (Naive Bayes, Bayes Net, Decision Table, J48 and Random Forest) classifiers for determining the detection rate of the classifiers. 10 fold cross validation has been used here for measuring the robustness of the system. To measure the efficiency of our hybrid feature selection method, we have also applied the same set of classifiers on the NSL KDD dataset, where it gives the best anomaly detection rate of 99.72% and average detection rate 98.47% similarly, we have applied the same set of classifiers on NSL DDoS dataset and obtain the average DDoS detection of 99.01% and the best DDoS detection rate of 99.86%. In order to compare the performance of our proposed hybrid method, we have also applied the existing feature selection methods and measured the detection rate using the same set of classifiers. Finally, we have seen that our hybrid approach for detecting the DDoS attack gives the best detection rate compared to some existing methods.","PeriodicalId":235855,"journal":{"name":"2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130744036","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: 15

ISEA-ISAP 2020 Author Index ISEA-ISAP 2020作者索引

2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/isea-isap49340.2020.9079288

引用次数: 0

Investigating Elliptic Curve Cryptography for Securing Smart Grid Environments 研究椭圆曲线密码保护智能电网环境

2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/ISEA-ISAP49340.2020.234993

D. K., K. Chandrasekaran

引用次数: 4

A Traffic Monitoring and Policy Enforcement Framework for HTTP HTTP的流量监控和策略执行框架

2020 Third ISEA Conference on Security and Privacy (ISEA-ISAP) Pub Date : 2020-02-01 DOI: 10.1109/ISEA-ISAP49340.2020.235004

M. N, Anna Thomas, Indu S, B. Bindhumadhava

引用次数: 0