Consistency: With Docker, developers can create Dockerfiles to define the environment and dependencies required for their applications. This ensures consistent development, testing, and production environments, reducing deployment errors and streamlining workflows.
Scalability: Docker's containerization model facilitates horizontal scaling by replicating containers across multiple nodes or instances. This scalability enables applications to handle varying workload demands and ensures optimal performance during peak usage times.
Speed: Docker containers start up quickly and have faster deployment times compared to traditional deployment methods. This speed is especially beneficial for continuous integration/continuous deployment (CI/CD) pipelines, where rapid iteration and deployment are essential.
Complexity: Docker introduces additional complexity, especially for users who are new to containerization concepts. Understanding Dockerfile syntax, image creation, container orchestration, networking, and storage management can be challenging for beginners.
Security Concerns: While Docker provides isolation at the process level, it is still possible for vulnerabilities or misconfigurations to compromise container security. Shared kernel vulnerabilities, improper container configurations, and insecure container images can pose security risks.
Networking Complexity: Docker's networking capabilities, while powerful, can be complex to configure and manage, especially in distributed or multi-container environments. Issues such as container-to-container communication, network segmentation, and service discovery may require additional expertise
Fake general image detection refers to the process of identifying whether an image has been manipulated or altered in some way to create a deceptive or false representation of reality. This type of detection is commonly used in fields such as forensics, journalism, and social media moderation to identify images that have been doctored or manipulated for malicious purposes, such as spreading fake news, propaganda, or misinformation. Fake general image detection techniques can include analyzing the image's metadata, examining inconsistencies in the lighting and shadows, identifying anomalies in the image's pixel patterns, and comparing the image to known authentic images or reference images. Some algorithms use machine learning techniques to analyze large datasets of both authentic and fake images to improve the accuracy of their detection.
However, it's important to note that no single method or algorithm can detect all types of fake images with 100% accuracy, and as technology advances, so do the techniques for creating convincing fake images. Therefore, it's essential to use a combination of techniques and human expertise to identify fake images and prevent them from spreading.
There are several techniques that can be used to detect fake images on social media. Here are a few examples: Done it
3. ❖ CONTENTS OF THIS SEMINAR
❖ Introduction
❖ Literature Survey
❖ Proposed work
❖ Practical Demonstration
❖ Advantages of Proposed System
❖ Disadvantages of Proposed System
❖ Results and Conclusion
❖ References
4. ❖ CONTENTS OF THIS SEMINAR
❖ Introduction to Docker
❖ What is Docker?
❖ Why use Docker?
❖ Docker's architecture (containers, images,
Docker daemon, Docker client)
❖ Comparison with virtual machines (VMs)
PART-I
5. ❖ CONTENTS OF THIS SEMINAR
❖ Working with Docker Containers
❖ Creating containers from Docker images
❖ Running, stopping, and restarting
containers
❖ Managing container lifecycle (pausing,
removing)
❖ Inspecting container logs and stats
PART-II
8. What is Docker?
❖ Docker is an open-source platform
used for containerization, allowing you
to package an application and its
dependencies into a standardized unit
called a container.
❖ Containers are lightweight, portable,
and isolated environments that ensure
consistent behavior across different
computing environments.
9.
10. Why use Docker?
❖ Docker simplifies the process of
developing, shipping, and deploying
applications by encapsulating them in
containers.
❖ Benefits of Docker include faster
application deployment, resource
efficiency (compared to virtual
machines), improved scalability, and
simplified DevOps workflows.
11. Docker Architecture Overview:
❖ Docker Engine: The core component of Docker that runs
and manages containers.
❖ Docker Client: CLI tool used to interact with Docker Engine.
❖ Docker Daemon: Background service responsible for
managing containers, images, networks, and volumes.
❖ Docker Registry: Stores Docker images (e.g., Docker Hub,
private registries).
14. Portability: Docker containers encapsulate
applications and their dependencies into
portable units, making them highly portable
across different environments, from development
to testing and production. This portability
ensures consistent behavior and eliminates
"works on my machine" issues.
Efficiency: Docker containers are lightweight and
share the host OS kernel, leading to efficient
resource utilization. They have minimal overhead
compared to virtual machines (VMs), allowing for
higher density deployments and reduced
infrastructure costs.
Isolation: Docker provides process-level
isolation, ensuring that applications run
independently of each other. This isolation
prevents conflicts between applications and
enables safer experimentation with different
software versions or configurations.
15. Consistency: With Docker, developers can
create Dockerfiles to define the environment and
dependencies required for their applications.
This ensures consistent development, testing,
and production environments, reducing
deployment errors and streamlining workflows.
Scalability: Docker's containerization model
facilitates horizontal scaling by replicating
containers across multiple nodes or instances.
This scalability enables applications to handle
varying workload demands and ensures optimal
performance during peak usage times.
Speed: Docker containers start up quickly and
have faster deployment times compared to
traditional deployment methods. This speed is
especially beneficial for continuous
integration/continuous deployment (CI/CD)
pipelines, where rapid iteration and deployment
are essential.
DOCKER
17. Complexity: Docker introduces additional
complexity, especially for users who are new to
containerization concepts. Understanding
Dockerfile syntax, image creation, container
orchestration, networking, and storage
management can be challenging for beginners.
Security Concerns: While Docker provides
isolation at the process level, it is still possible
for vulnerabilities or misconfigurations to
compromise container security. Shared kernel
vulnerabilities, improper container
configurations, and insecure container images
can pose security risks.
Networking Complexity: Docker's networking
capabilities, while powerful, can be complex to
configure and manage, especially in distributed
or multi-container environments. Issues such as
container-to-container communication, network
segmentation, and service discovery may
require additional expertise
19. Results and Conclusion
❖ In conclusion, the adoption of Docker
containers has significantly transformed
our software development and
deployment practices, leading to tangible
benefits and improvements across various
aspects of our projects.
❖ Docker's portability, scalability,
streamlined workflows, resource efficiency,
consistent environments, security features,
and deployment flexibility have made it an
invaluable tool in our development toolkit.
21. 1) Base Systems for Docker Containers - Security Analysis ( September
2022):
Docker based containerization is currently one of the most popular methods
of delivering and creating of a software. It allow multiple teams to standarize
their work, but also to reduce disadvantages of virtual machines that can
impact performance and usability. This work concerns security of base
systems, focusing on distroless. Base container images are one of the critical
parts of a cloud environment. The results of analysis presented here allow for
independent and objective comparison of advantages and disadvantages of
various containers' base systems which are widely used in orchestration
platforms such as Kubernetes and OpenShift
22. 2) Research on Using Docker Container Technology to Realize Rapid
Deployment Environment on Virtual Machine ( September 2022):
At present, with the rapid development of IT technology, the traditional
computing mode has become more and more difficult to meet the processing
and various engineering or scientific computing tasks. In fact, with the
gradual popularization of computers and the continuous progress of
semiconductor technology, the computing model has experienced several
major changes. These changes can be summarized into four stages:
character dumb terminal host, client server, cluster computing and cloud
computing. Virtual machine services account for a large proportion of cloud
computing services. The implementation of virtual machine can enable users
to improve use efficiency, reduce use cost, facilitate migration and backup,
and reduce maintenance cost. Docker container technology has the above
advantages at the same time. How to combine the two to improve the
operation and maintenance efficiency and deploy the project environment
faster.
25. o 1.Arkadiusz Maruszczak,Michal WalkowskiSlawomir Sujecki, “Base Systems
for Docker Containers - Security Analysis” (September 2022)
o 2.Wei Wang,”Research on Using Docker Container Technology to Realize
Rapid Deployment Environment on Virtual Machine”(September 2022)
o 3.Li You1and Hui Sun,“Research and Design of Docker Technology Based
Authority Management System”(2022)
https://docs.docker.com/