Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.

1. Artificial Intelligence
Malicious Use System
BY:
VAIBHAV MISHRA
KRITI LABHANIYA
TRUBA INSTITUTE OF ENGINEERING AND
INFORMATION TECHNOLOGY
BHOPAL, MP

2. Content
Definitions
Capabilities
The Problems
Solutions
Some More Solutions
Results

3. What is Artificial Intelligence?
Artificial Intelligence is the study of mental faculties through the use of
computational models.
Artificial Intelligence is a way of making a computer, a computer-
controlled robot, or a software think intelligently, in the similar manner
the intelligent humans think.
Artificial Intelligence is the best field for dreamers to play around. It
must be evolved from the thought that making a human-machine is
possible.

4. Artificial Intelligence Capabilities

5. Why AI is Important?
• AI automates repetitive learning and discovery through data.
• AI adds intelligence to existing products.
• AI analyzes more and deeper data using neural networks that
have many hidden layers.
• AI achieves incredible accuracy though deep neural networks –
which was previously impossible.

6. How AI works?
AI works by combining large amounts of data with fast, iterative
processing and intelligent algorithms, allowing the software to learn
automatically from patterns or features in the data. AI is a broad field
of study that includes many theories, methods and technologies, as
well as the following major subfields:
Machine Learning Neural Network
Deep Learning Cognitive Computing
Computer Vision Neural Language Processing (NLP)

7. Machine Learning
Machine Learning automates analytical model building. It uses
methods from neural networks, statistics, operations research and
physics to find hidden insights in data without explicitly being
programmed for where to look or what to conclude.

8. Neural Network
In information technology (IT), a neural network is a system of
hardware and/or software patterned after the operation of neurons in
the human brain. Neural networks -- also called artificial neural
networks -- are a variety of deep learning technology, which also falls
under the umbrella of artificial intelligence, or AI.

10. Deep Learning
Deep learning (also known as deep structured learning or
hierarchical learning) is part of a broader family of machine learning
methods based on learning data representations, as opposed to
task-specific algorithms. Learning can be supervised, semi-
supervised or unsupervised.

11. Cognitive Computing
In general, the term cognitive computing has been used to refer to
new hardware and/or software that mimics the functioning of the
human brain and helps to improve human decision-making. In this
sense, CC is a new type of computing with the goal of more accurate
models of how the human brain/mind senses, reasons, and responds
to stimulus. CC applications link data analysis and adaptive page
displays (AUI) to adjust content for a particular type of audience. As
such, CC hardware and applications strive to be more affective and
more influential by design.

12. Computer Vision
Computer vision is an interdisciplinary field that deals with how
computers can be made for gaining high-level understanding from
digital images or videos. From the perspective of engineering, it
seeks to automate tasks that the human visual system can do.

13. Neural Language Processing
Natural language processing (NLP) is an area of computer science
and artificial intelligence concerned with the interactions between
computers and human (natural) languages, in particular how to
program computers to process and analyze large amounts of natural
language data.

14. The Problems
Cybersecurity Vulnerability
Cybersecurity, computer security or IT
security is the protection of computer
systems from the theft and damage to their
hardware, software or information, as well
as from disruption or misdirection of the
services they provide.
Vulnerability is a cyber-security term that
refers to a flaw in a system that can leave it
open to attack. A vulnerability may also refer
to any type of weakness in a computer
system itself, in a set of procedures, or in
anything that leaves information security
exposed to a threat.

15. Solutions
 Policy makers should work closely to researchers to
investigate, prevent and mitigate risks malicious uses
of AI.
 Researchers and engineers in artificial intelligence
should take the dual-use nature of their work, allowing
misuse considerations to influence research priorities
and standards, and to proactively reach interested
party’s harmful applications are predictable.

16. Solutions
 Best practices should be identified in research areas
with more than proven methods to solve dual-use of
problems, such as computer security in the of case AI.
 Actively seek to expand the range of stakeholders and
domain experts involved in discussions on these
challenges.

17. Other-Solutions
 Learn from and with the cybersecurity
community
 Explore different opening models (Dual
Purpose nature of AI and ML)
 Promote a culture of responsibility
 Develop technological and political solutions

18. Results
Data Protection
Data protection is the process of safeguarding important
information from corruption, compromise or loss. The
importance of data protection increases as the amount
of data created and stored continues to grow at
unprecedented rates.

19. Results
Vulnerability can be stopped
Vulnerability is the state of being exposed to the possibility
of being attacking or harming the machine. Recently a
processor vulnerability occurred in Intel, AMD and ARM
CPUs and as we know most of the processors are from
these companies. So, if vulnerability occurs again it will be
a global technical crisis.

20. Thank you for
your Patience