International Conference on Computer and Knowledge Engineering

Home / 11th International Conference on Computer and Knowledge Engineering

Automatic Generation of XACML Code using Model-Driven Approach

Authors :

Athareh Fatemian¹ Bahman Zamani² Marzieh Masoumi³ Mehran Kamranpour⁴ Behrouz Tork Ladani⁵ Shekoufeh Kolahdouz Rahimi⁶

1- MDSE Research Group, Faculty of Computer Engineering University of Isfahan 2- MDSE Research Group, Faculty of Computer Engineering University of Isfahan 3- MDSE Research Group, Faculty of Computer Engineering University of Isfahan 4- MDSE Research Group, Faculty of Computer Engineering University of Isfahan 5- MDSE Research Group, Faculty of Computer Engineering University of Isfahan 6- MDSE Research Group, Faculty of Computer Engineering University of Isfahan

Keywords :

Access Control Policies, XACML, ABAC, RBAC, MDE, DSML

Abstract :

Precise specification of security requirements of software systems in general, and access control policies in particular, is a critical issue. The eXtensible Access Control Markup Language (XACML) is a well-known standard for defining access control policies. The problem is that using this language and manual formulation of policies requires technical knowledge and is error prone. To address this challenge, we propose a Domain-Specific Modeling Language (DSML), called Dual-XACML that supports both Role Based Access Control (RBAC) and Attribute Based Access Control (ABAC). As the tool support, a graphical editor as well as a transformation engine has been developed in this research. The graphical editor allows the user to create a model of access control policies for the target system. Then, using the transformations, the model is transformed into the corresponding XACML code. To evaluate the proposed approach, the XACML code of a typical system is generated, automatically.

Papers List

List of archived papers

Lightweight Local Transformer for COVID-19 Detection Using Chest CT Scans

Hojat Asgarian Dehkordi - Hossein Kashiani - Amir Abbas Hamidi Imani - Shahriar Baradaran Shokouhi

Forecasting El Niño Six Months in Advance Utilizing Augmented Convolutional Neural Network

Mohammad Naisipour - Iraj Saeedpanah - Arash Adib - Mohammad Hossein Neisi Pour

Enhancing Lighter Neural Network Performance with Layer-wise Knowledge Distillation and Selective Pixel Attention

Siavash Zaravashan - Sajjad Torabi - Hesam Zaravashan

Sports News Summarization Using Ensebmle Learning

Moein Sartakhti.salimi@gmail.com - Mohammad Javad Maleki Kahaki - Ahmad Yoosofan - Seyyed Vahid Moravvej

Practical Implementation of Real-Time Waste Detection and Recycling based on Deep Learning for Delta Parallel Robot

Hasan Jalali - Shaya Garjani - Ahmad Kalhor - Mehdi Tale Masouleh - Parisa Yousefi

Multi-Task Transformer for Stock Market Trend Prediction

Seyed Morteza Mirjebreili - Ata Solouki - Hamidreza Soltanalizadeh - Mohammad Sabokrou

MC-BioCLIPSR: A Mamba-CNN Hybrid Network with BioMedCLIP-Guided Loss for High-Resolution Brain MRI Reconstruction

Amin Kazempour - Jafar Tanha - SeyedEhsan Roshan - Mahdi Zarrin - Haniyeh Nikkhah

ROCT-Net: A new ensemble deep convolutional model with improved spatial resolution learning for detecting common diseases from retinal OCT images

Mohammad Rahimzadeh - Mahmoud Reza Mohammadi

Extracting Major Topics of COVID-19 Related Tweets

Faezeh Azizi - Hamed Vahdat-Nejad - Hamideh Hajiabadi - Mohammad Hossein Khosravi

Simulating Human Visual Cortex and Recall System with Convolutional Neural Networks

Sina Saadati - Abdolah Sepahvand