Posts

Showing posts from February, 2021

APPROACH TOWARDS CLUSTER COMPUTING

Image
  Cluster computing is the software or tool which is used to presenting  the latest research and technology in computer systems and networks.   It is a single logical unit that are linked through LAN. It provides faster processing speed larger speed larger storage capacity and better data integrity. It need good data integrity in cost.  It presents research and applications in parallel processing Disadvantages Of Cluster Computing Difficult to organize a large number of computers. poor performance in case of non –parallelizable applications. It increases power consumption. Advantages Of Cluster Clustering It enables data recovery in the event of disaster in data processing Need Of Cluster Computing Clustering is used to explore data.it is used to find natural groupings.  It is used for data -preprocessing . it finds cluster of data that are similar in sense to one another.  It is also used to segment the data which is also previously defined. PRIYANSHI VASHISTHA (2019-2023) Computer Sc

COMPUTER VISION

Image
  Computer vision is one of the main technologies in the world that enables the digital world to the physical world. It enables self-driving cars to make sense of the physical world. It plays  very important role in facial applications to see the real identity of people’s face. It has nuanced applications. It is an in disciplinary scientific field so it gains high level understanding. Use of Computer Vision Computer vision begins with the acquisition of images. It is the use of information presents I visual images. Using a computer to analyze images also called machine vision. It is an integralpartof artificial intelligence. It is not only one technology but after combined with others it creates intelligence. Computer vision describes the process of using digital images and videos to gain stronger insights from users. Information from data sources is extracted automatically and understands. Goal of Computer Vision The goal of computer vision is to understand the content of digital imag

SPOOFING

Image
  Spoofing means to provide false information about your idea gain unauthorized identity to gain unauthorized access to others computer systems. In a spoofing attack one person or program successfully pretends as another falsifying data thereby gaining as illegal advantage. IP spoofing are the most popular spoofing attacks. The objective of IP spoofing is to make the data look as if it has come from trusted host as it. Spoofing is always done with an intention. Types of Spoofing IP Spoofing:  It do not provide mechanisms for authenticating the source or destination of a message ad they are thus vulnerable to spoofing attacks to verify the identify the sending or receiving post.  Content spoofing: It includes the caller’s number and sometimes  Caller ID spoofing:  It includes the caller’s name and caller’s number., it allows to hack the caller’s id information. E-mail spoofing: The sender information shown in emails. It is commonly used by spammers to hide the origin information   Concl

VPN NETWORKING

Image
  VPN is an online privacy and creating a private network from a public internet connection. When the internet was first designed the packets(chunk of data) as really possible. It creates the virtual tunnel through which data travels from one computer to another over the network. Due to this an attacker gets the way to use the client to relay attack through the VPN tunnel. VPN fingerprinting. username enumeration vulnerabilities offline password cracking lack of account lockout offline password cracking Insecure Storage of Authentication Credentials by VPN Clients storing the username unencrypted in a file or registry storing the password in a scrambled form storing the permission s credentials. Types of VPN PPTP: This is the most commonly and widely used VPN protocol SITE TO SITE VPN: This is similar to PPTP but there is no dedicated line for transmission for  this.it worked with hardware and software based firewall devices. L2TP: It provides not only data confidentiality but also

ROBOTICS

Image
Robotics is the intersection of science and technology. It is an interdisciplinary field of computer science. It is not easy to define what robots are and it is not easy to categorize them. Each robot has its own feature .we can classify robots into 15 types. Some of them are fully explained here.’ The main era of robotic research and development was mid the 20th century, primarily within an industrial environment where repetitive movements and lifting of heavy objects… Joseph F.  Engel Berger and George Devol developed the first industrially used robots in 1961. 1. Aerospace: This is a category in which all sorts of flying robots come. Like smart bird robotic seagull and the raven surveillance drone .but these robots can operate only in space such as mars, rovers, and NASA’s Robonut. 2. Consumer: These types of robots you can buy and can use just for fun too. Examples of these types of robots are robot dog Aibo, Roomba vacuum, AI powers robot assistants, and these have also come in

SPAM DETECTION – Natural Language Processing – in web

Image
Ever wondered how are your emails and messages classified as spam or inbox? Of course, if you’ve come to go through this article you know it, right! It is done by training the machine on the basis of the collected data set. This is what is Natural Language Processing (NLP), programming computers to understand, interpret, and manipulate human language. After studying this article you’ll definitely be able to create your own program to classify your messages. Classifier Algorithm: Naive Bayes Algorithm Interface:  Google Colabs  Language Used: Python So, without wasting much of our time let us head directly into spam detection.  Spam is any kind of unwanted, unsolicited digital communication, that gets sent out in bulk. It is a huge waste of time and resources. Opposite of spam is ‘Ham’, which is a more technical term and will be used throughout the content. Let’s have a look at the flow chart for the same. Step 1: First of all we need to have data set for training the model, you cou