Preventing Cyber Attacks using Artificial Intelligence
Exploring Advantages and Challenges of Chatbot Integration in Human-Robot Interaction
Counterfeit Currency Detection using Machine Learning
Artificial Intelligence use in Lung Cancer Screening to Improve Patient Recovery
An Analysis of Various Crypto Coins and their Suitability for Real-Time Applications
Design and Evaluation of Parallel Processing Techniques for 3D Liver Segmentation and Volume Rendering
Ensuring Software Quality in Engineering Environments
New 3D Face Matching Technique for an Automatic 3D Model Based Face Recognition System
Algorithmic Cost Modeling: Statistical Software Engineering Approach
Prevention of DDoS and SQL Injection Attack By Prepared Statement and IP Blocking
The paper is concerned with the design and Implementation of a Social Networking Site (SNS). The proposed system is designed and implemented using PHP(Hypertext Preprocessor), My SQL(My Structured Query Language)and JavaScript and tested using XAMPP server. Users can create their own account in SNS and enjoy the benefit from the services provided by it, like friend request, messages, and comment on any post of friends. The proposed system allows the user to add, remove friends and display their profile. The system enables the user to post on his profile and other network members profile. They can join the friends In groups according to the user's hobbies (sport, art, reading and cars). The friends can share ideas by post and comment features. The proposed system provides the users with Member directory that shows all users that are already registered in SNS and allow them to find and add friends. Administrator has a privilege access to the data base to display update, add, or delete all the content of the database.
Increased Interconnectlon of the power system along with deregulated structure to satisfy growing demand has brought new challenges for power system state estlmatlon. The estlmatlon of power system stofe [1,3] in such interconnected system has become complex due to comp/exity in modelling and uncertalntles. This makes ANN a ideal candldate for state estimation, since if can accurately map the relationshlp between the measured varlable and other state variables of the power system with reduced computational resources as compared to weighted least square approach[2]. Using only load bus parameters for various operating condifions with an ANN other states of the power system can be accurately estimated. This paper dlscusses an approach to estimate the state of power system using ANN in MATLAB.
The popularity of steganography has Increased in private network due to data exfllfrafion of corporate sensitive data and If Is Important to detect such malicious activity. In vi'deo a large amount of data can be hidden which is becoming Increasingly a concern of Interest . If Is very hard to defect the Inside affacker in the organization network who can extract the sensitive Information from organization and fransfer that information In hidden format through the video sfeganography To ensure privacy and security the authors have proposed an effective sfeganalysis method to defect hidden data in video by using the SDN framework pollcy. With the help of the SDN framework administrator of private network can look at the whole network and control the network by programming The main objective of this paper Is to prevent the illegal data transmission from the compromised private network by the mallclous users. Keywords: Steganography, Data Exfiltration, and Software Defined Network.
Web mining related research is getting more important nowadays because of the large amount of data that is managed through the internet. Web usage is increasing in an uncontrollable manner. A specific system is needed for controlling such large amount of data in the web space. Web mining is classified into three major divisions: Web content mining, web usage mining and web structure mining. Tak-Lam Wong and Wai Lam have proposed a web content mining approach in a research with the help of Bayesian networks. In their approach, they discuss on extracting web information and attribute discovery based on the Bayesian approach. Inspired from their research, the authors intend to propose a web content mining approach, based on a deep learning algorithm. The deep learning algorithm provides the advantage over Bayesian networks because Bayesian network is not considered in any learning architecture alike the proposed technique. In the proposed approach, three features are considered for extracting the web content. The features used are: concept feature that deals with the semantic relations on the web, format feature that deals with the format of the content and title feature, which deals with the web title. The above listed features produce some model parameters, which are given as the input to the deep learning algorithm. The process continues according to the deep learning algorithm and finally extracts content according to the input provided. There are a lot of approaches that have been developed in the area of Web Information Extraction (IE), which are concerned with harvesting useful information for any further analysis from web pages. Learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success. In this paper, a method has been proposed for information extraction from the Web using Deep Learning Algorithm.
Mutation testing is a fault-based technique. Mutation testing is performed at the final stage of the software, that is, before the delivery of the software to the customer. Mutation testing is a technique which measures the adequacy of a test case by seeding artificial defects(mutants) into a program. If a test case fails to detect a mutant, it may also fail to detect real faults or defects. A mutation over the original program may not change the semantics of the program; hence it is hard to detect the changes by a test case. This problem should be got rid of. There also exists another type of mutants which keep the program semantics unchanged and thus cannot be detected by any test case, this issue must be considered by generating more number of mutants. To deal with this problem, the authors introduce MUJAVA, by applying various mutations. MUJAVA supports two level mutant operators (Traditional mutation operators and class level mutation operators). For evaluating the effectiveness of the proposed methodology open source system will be considered and experiments will be implemented using MUJAVA testing tool.
