Category: Python projects

ABSTRACT:

Data security is the main concern in different types of applications from data storing in clouds to sending messages using chat. In order to provide security for data in the cloud, there are many types of techniques which are already proposed like AES, DES, RSA but in existing methods, most of the time only a single type of encryption was used either AES, OR DES, OR RSA based on user requirement but in this system main problem is each encryption is done using encryption keys if these keys are exposed in any case entire data is lost so we need an effective method which can provide more security so in this project hybrid cryptography is used where existing encryption methods are used but three methods will be used. When the user uploads data will split into three parts and the first part will be encrypted using AES, the second part will be encrypted using DES, the third part will be encrypted using RSA  and these three encrypted files will be stored in the cloud and keys used for AES, DES and RSA are stored in the image using LSB steganography when users want to download total data from cloud-first keys should be retrieved from the image and these keys are used for decrypting data again by using AES, DES and RSA and final data is combined and stored in the file. This method provides more security for data.

OBJECTIVE:

Data security is the main issue in cloud data management there is a chance of developing effective methods like hybrid cryptography for improving security. In this project, AES, DES, RSA is used along with LSB.

INTRODUCTION:

 Cloud is playing important role in data management and another type of service that provides a secure way of data handling and remote data accessing where users from anywhere can use the cloud for data access. As the cloud is a third-party application where data uploaded by users must provide security features to reduce risks from data attacks in order to do that encryption techniques here used like AES, DES, and RSA.

EXISTING SYSTEM:

In the existing system cloud used to use any one of the encryption technique and keys verification is done using the identity of the user. Based on application requirements different encryption techniques are used.

DISADVANTAGES:

Only single encryption techniques are used and keys are not managed effectively there are chances of leakage of keys. 

PROPOSED SYSTEM:

In order to improve security for cloud data compare to existing techniques where keys are shared security between users new hybrid cryptography technique is proposed where three types of encryption are used AES, DES, and RSA and the LSB steganography technique is used for secure key sharing.

ADVANTAGES:

Data is split into three parts and each part is encrypted using one encryption technique and keys are shared securely by embedding in the image.

SOFTWARE REQUIREMENTS: 

• Operating system: Windows 7.
• Coding Language: python
• Tool: anaconda, visual studio code
• Database: SQL lite

Abstract:

Data mining in education institutions is helping to analyze students’ details and provide an effective evaluation system in a short time. With the advancement of new technologies student’s evaluation procedure has changed from manual correction to automate process of correction and analysis. This student coding assignment evaluation system using API is designed to evaluate students coding correction process through the automation process. When a student submits an answer for a student’s question online faculty will evaluate coding by sending data to API and get results or error messages. By checking these messages faculty will give marks to students. This process is done through a web application that is developed in python programming language.  

Problem statement:

            Students assignment evaluation is a time taking process for faculty which required a manual process by checking each line of code and give marks to students. 

Objective:

            The coding evaluation process can be automated by using available code checking API’s which can be integrated into the college assignment assigning website. Using this process evaluation is completed just in a click and faculty can give marks based on result.

Existing system:

• A manual process was used for checking assignments and evaluate results.
• Data mining techniques were used for evaluation which uses previous coding datasets and predicts results that are not accurate.

Disadvantages:

• Faculty must check each line of code to evaluate coding and give grading.
• Time taken for the evaluation process is high.

Proposed system:

                        The student online coding evaluation system provides an automatic coding checking process through which faculty can assign coding assignments and get results from students and compile code in click and check result and give marks.

Advantages:

• The entire process of assigning to evaluation is done online and coding evaluation is done in one click.
• API is used for checking errors in code and give grading.

System requirement: 

Programing language: python

Framework: Flask

Database: MYSQL

API: for compiling code

Abstract:

Cyber bullying is the process of sending wrong messages to a person or community which causes heated debate with users. Cyberbullying is mostly seen in social networking sites where users reply to post with bullying words to threaten or insult other users. Cyberbullying is considered a misuse of technology. According to the latest survey done on all over the world data day by day, cases are increasing on cyberbullying. In order to solve this problem many natural language processing techniques are proposed by various authors which are time taking and not automatic. With the advancement of machine learning and artificial intelligence, models can be created and automatic detection can be implemented. To show this scenario live chat application is developed in python programming with multiple clients and one server and the Naive Bayes algorithm is used to train the model on a Twitter dataset and using this model live detection of cyberbullying is predicted and alert messages are shown on the chat application.

Problem statement:

       Social networking and online chatting application provide a platform for any user to share knowledge and talent but few users take this platform to threaten users with cyberbullying attacks which cause issues in using these platforms.

Objective:

    To provide a better platform for users to share knowledge on social networking sites there is a need for an effective detection system that can automate the process of cyberbullying detections and take decisions.

Existing system:

• Techniques like unsupervised labeling methods which use N-gram, TF-IDF methods to detect cyberbullying are used which use the youtube dataset to detect attacks.
• A support vector classifier is used to train models for detection.

Disadvantages:

         Techniques which are used in the existing system are not automated they need time to process request and update response.

           Social networking and chatting sites require automated detecting and processing methods.

Proposed system:

         Cyberbullying detection is designed using machine learning techniques. Twitter data set is collected with features and labels and mode is trained using the Naive Bayes algorithm and trained model is applied to live chatting application which has multiple clients and a single server. For each message, cyberbullying is detecting using the model and then alert messages are posted on chat boards.

Advantages:

         Cyberbullying detection process is automatic and time taken for detection is less and it works on the live environment. 

            The latest machine learning models are used for training models that are accurate.

Software Requirement:

Programming language: python

Front End GUI : tkinter

Dataset: Twitter cyberbullying dataset

Algorithm                       : Naive bayes