Performance Comparison on SQL Injection and XSS Detection using Open Source Vulnerability Scanners

2021 ◽  
Author(s):  
Busra Zukran ◽  
Maheyzah Md Siraj
Keyword(s):  
Open Source ◽  
Performance Comparison ◽  
Sql Injection

Performance Comparison of Web Backend And Database: A Case Study Of Node.JS, Golang and MySQL, MongoDB

2019 ◽  
Vol 13 ◽  
Author(s):  
Faried Effendy ◽  
Taufik ◽  
Bramantyo Adhilaksono
Keyword(s):  
Response Time ◽  
Open Source ◽  
Poisson Distribution ◽  
Mobile Application ◽  
Web Applications ◽  
Performance Comparison ◽  
Memory Usage ◽  
Data Traffic ◽  
Cpu Utilization

: Substantial research has been conducted to compare web servers or to compare databases, but very limited research combines the two. Node.js and Golang (Go) are popular platforms for both web and mobile application back-ends, whereas MySQL and Go are among the best open source databases with different characters. Using MySQL and MongoDB as databases, this study aims to compare the performance of Go and Node.js as web applications back-end regarding response time, CPU utilization, and memory usage. To simulate the actual web server workload, the flow of data traffic on the server follows the Poisson distribution. The result shows that the combination of Go and MySQL is superior in CPU utilization and memory usage, while the Node.js and MySQL combination is superior in response time.

scholarly journals Program Analysis For Database Injections

2017 ◽  
Vol 16 (6) ◽  
pp. 6977-6986
Author(s):  
Chelsea Ramsingh ◽  
Paolina Centonze
Keyword(s):  
Open Source ◽  
Private Information ◽  
Program Analysis ◽  
Query Language ◽  
Cyber Attacks ◽  
Test Cases ◽  
Sensitive Data ◽  
Sql Injection ◽  
Testing Tools ◽  
Private Data

Today businesses all around the world use databases in many different ways to store sensitive data. It is important that the data stored stay safe and does not get into the wrong hands. To perform data management in a database, the language SQL (Structured Query Language) can be used. It is extremely crucial to prevent these databases from being attacked to ensure the security of the users’ sensitive and private data. This journal will focus on the most common way hackers exploit data from databases through SQL injection, and it presents dynamic and static code testing to find and prevent these SQL cyber attacks by comparing two testing tools. It will also present a comparative analysis and static/dynamic code testing of two SQL injection detection tools. Burp Suite and Vega will be used to identify possible flaws in test cases dealing with users’ sensitive and private information. Currently, there are no comparisons of these two open-source tools to quantify the number of flaws these two tools are able to detect. Also, there are no detailed papers found fully testing the open-source Burp Suite and Vega for SQL Injection. These two open-source tools are commonly used but have not been tested enough. A static analyzer detecting SQL Injection will be used to test and compare the results of the dynamic analyzer. In addition, this paper will suggest techniques and methods to ensure the security of sensitive data from SQL injection. The prevention of SQL injection is imperative and it is crucial to secure the sensitive data from potential hackers who want to exploit it.

scholarly journals Performance Analysis of Different Embedded Systems and Open-Source Optimization Packages Towards an Impulsive MPC Artificial Pancreas

2021 ◽  
Vol 12 ◽  
Author(s):  
Jhon E. Goez-Mora ◽  
María F. Villa-Tamayo ◽  
Monica Vallejo ◽  
Pablo S. Rivadeneira
Keyword(s):  
Embedded Systems ◽  
Open Source ◽  
Control Strategies ◽  
Artificial Pancreas ◽  
Performance Comparison ◽  
Raspberry Pi ◽  
Portable Devices ◽  
Technological Advances ◽  
Computer Environment ◽  
The Difference

Current technological advances have brought closer to reality the project of a safe, portable, and efficient artificial pancreas for people with type 1 diabetes (T1D). Among the developed control strategies for T1D, model predictive control (MPC) has been emphasized in literature as a promising control for glucose regulation. However, these control strategies are commonly designed in a computer environment, regardless of the limitations of a portable device. In this paper, the performances of six embedded platforms and three open-source optimization solver algorithms are assessed for T1D treatment. Their advantages and limitations are clarified using four MPC formulations of increasing complexity and a hardware-in-the-loop methodology to evaluate glucose control in virtual adult subjects. The performance comparison includes the execution time, the difference concerning the evolution obtained in MATLAB, the processor temperature, energy consumption, time percentage in normoglycemia, and the number of hypo- and hyperglycemic events. Results show that Quadprog is the package that faithfully follows the results obtained with control strategies designed and tuned on a computer with the MATLAB software. In addition, the Raspberry Pi 3 and the Tinker Board S embedded systems present the appropriate characteristics to be implemented as portable devices in the artificial pancreas application according to the criteria set out in this work.

scholarly journals Detecting security vulnerabilities with static analysis – A case study

2021 ◽  
Keyword(s):  
Open Source ◽  
Static Analysis ◽  
Source Code ◽  
Performance Comparison ◽  
Test Suite ◽  
Study Analysis ◽  
Security Vulnerabilities ◽  
Analysis Tools ◽  
A Performance

Abstract Many security vulnerabilities can be detected by static analysis. This paper is a case study and a performance comparison of four open-source static analysis tools and plugins (PMD, SpotBugs, Find Security Bugs, and SonarQube) on Java source code. Experiments have been conducted on the widely used Juliet Test Suite with respect to six selected weaknesses from the official Top 25 list of Common Weakness Enumeration. In this study, analysis metrics have been calculated for helping Java developers decide which tools can be used when checking their programs for security vulnerabilities. It turned out that particular weaknesses are best detected with particular tools.

scholarly journals Accuracy and Efficiency Comparison of Object Detection Open-Source Models

2021 ◽  
Vol 17 (05) ◽  
pp. 165
Author(s):  
Brahim Jabir ◽  
Noureddine Falih ◽  
Khalid Rahmani
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Large Scale ◽  
Performance Comparison ◽  
Yield Potential ◽  
Temperate Climate ◽  
Weed Species ◽  
Weed Detection ◽  
Cloudy Weather

In agriculture, weeds cause direct damage to the crop, and it primarily affects the crop yield potential. Manual and mechanical weeding methods consume a lot of energy and time and do not give efficient results. Chemical weed control is still the best way to control weeds. However, the widespread and large-scale use of herbicides is harmful to the environment. Our study's objective is to propose an efficient model for a smart system to detect weeds in crops in real-time using computer vision. Our experiment dataset contains images of two different weed species well known in our region strained in this region with a temperate climate. The first is the Phalaris Paradoxa. The second is Convolvulus, manually captured with a professional camera from fields under different lighting conditions (from morning to afternoon in sunny and cloudy weather). The detection of weed and crop has experimented with four recent pre-configured open-source computer vision models for object detection: Detectron2, EfficientDet, YOLO, and Faster R-CNN. The performance comparison of weed detection models is executed on the Open CV and Keras platform using python language.

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