Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks, Fog computing is a term created by Cisco that refers to extending cloud computing to the edge of an enterprise's network. Cisco introduced its fog computing vision in January 2014 as a way of bringing cloud computing capabilities to the edge of the network . As the result, closer to the rapidly growing number of connected devices and applications that consume cloud services and generate increasingly massive amounts of data.

1. Prepared By:
Ankit Ap
www.facebook.com/Ank1tAp
FOG COMPUTING
(INTERNET OF THINGS)

2.  User Behavior Profiling.
 Application of Fog Computing.
 Decoy System.
 Security And Privacy issues.
 Conclusion.
 Future Scope & Prediction.
 References.
 Abstract.
 Introduction.
 Existing System.
 Disadvantage Of Existing System.
 Internet Of Things (IOT).
 Proposed System.
 Characteristics.
CONTENTS

3. • Fog Computing is a paradigm that extends Cloud computing and
services to the edge of the network. Similar to Cloud, Fog provides
data, compute, storage, and application services to end-users. The
motivation of Fog computing lies in a series of real scenarios, such as
Smart Grid, smart traffic lights in vehicular networks and software
defined networks
ABSTRACT

4. • Fog computing is a term created by Cisco that refers to extending cloud
computing to the edge of an enterprise's network.
• Cisco introduced its fog computing vision in January 2014 as a way of
bringing cloud computing capabilities to the edge of the network .
• As the result, closer to the rapidly growing number of connected devices
and applications that consume cloud services and generate increasingly
massive amounts of data.
INTRODUCTION

5. • Cloud computing is a type of
computing that relies on sharing
computing resources rather than
having local servers or personal
devices to handle applications.
Cloud computing is comparable to
grid computing, a type of
computing where unused
processing cycles of all computers in
a network are harnesses to solve
problems too intensive for any
stand-alone machine.
EXISTING SYSTEM

6. DISADVANTAGE OF EXISTING SYSTEM
• ENCRYPTION WAS FAILED IN SECURING THE DATA FROM THE
ATTACKER.
• IT DOES NOT VERIFY WHETHER THE USER IS AUTHORISED OR NOT.
• NO BODY IS IDENTIFIED WHEN THE ATTACK HAPPENS.
• IT IS COMPLEX TO DETECT WHICH USER IS ATTACK.
• WE CAN’T DETECT WHICH FILE IS BEING HACKED.
• LATENCY TOO HIGH.
• RESILIENCY IMPRACTICAL.

7. INTERNET OF THINGS (IOT)
• The Internet of Things (IoT) is
the network of physical
objects—devices, vehicles,
buildings and other items
embedded with electronics,
software, sensors, and network
connectivity—that enables
these objects to collect and
exchange data.

9. • We proposed a completely new technique to secure user’s data in
cloud using user behavior Profiling and Decoy information
technology called as fog computing.
• In this technique when the unauthorized person try to access the
data of the real user the system generates the fake documents in
such a way that the unauthorized person was also not able to
identify the data is fake or real.
PROPOSED SYSTEM

11. • SECURITY
• - STRONG SECURITY (HARDWARE ROOT OF TRUST)
• - RESILIENCY/FAULT TOLERANCE.
• PROGRAMMABILITY
• - MULTIPLE APPLICATION SUPPORT.
• - VERSATILITY IN OPERATING ENVIRONMENT.
CHARACTERISTICS

12. • REAL TIME FEATURES
- DETERMINISTIC TIMING CAPABILITIES.
• SUPPORTS MULTIPLE OPERATING
PLATFORMS:UNIX,WINDOWS,MAC etc.
• EMPLOYS SIMPLE,FAST AND STANDARIZED IOT INTERNET
PROTOCOLS(TCP/IP ,SOCKETS etc.).
• RUNS ON AFFORDABLE,OFF THE SHELF COMPUTING
TECHNOLOGIES.
CHARACTERISTICS

13. • Admin monitor data access in the cloud and notice abnormal data
access patterns User profiling will a well known Technique that can
be applied here to check how, when, and how much a client access
their data in the Cloud.
• This method of behavior based security will regularly used in
scheme uncovering applications.
USER BEHAVIOR PROFILING

14. • IT INCLUDES VOLUMETRIC INFORMATION,HOW MANY
INFORMATIONS ARE TYPICALLY READ AND HOW OFTEN.
• “NORMAL USER ” BEHAVIOR IS CONTINUOUSLY CHECKED TO
DETERMINE ABNORMAL ACCESS .
• THIS SECURITY IS COMMONLY USED IN FRAUD DETECTION
APPLICATION.
USER BEHAVIOR PROFILING

15. • SOFTWARE DEFINED NETWORKS(SDN):
SDN CONCEPT TOGETHER WITH FOG WILL RESOLVE THE ISSUE IN
VEHICULAR NETWORKS , INTERMITTENT CONNECTIVITY , COLLISION
HIGH PACKET LOSS RATE.
• IoT AND CYBER-PHYSICAL SYSTEMS(CPSs):
INTEGRATE THE ABSTRACTIONS AND PRECISION OF SOFTWARE AND
NETWORKING WITH THE DYNAMICS IN THE PHYSICAL ENVIRONMENT.
• DECENTRALIZED SMART BUILDING CONTROL:
WITH FOG COMPUTING ,SMART BUILDING CAN MAINTAIN THEIR
FABRIC,EXTERNAL AND INTERNAL ENVIRONMENTS.
APPLICATION OF FOG COMPUTING.

16. • The main security issues are authentication at different levels of
gateways as well as (in case of smart grids) at the smart meters
installed in the consumer’s home.
• Each smart meter and smart appliance has an IP address. A
malicious user can either tamper with its own smart meter, report
false readings, or spoof IP addresses.
• In smart grids, privacy issues deal with hiding details, such as what
appliance was used at what time, while allowing correct
summary information for accurate charging.
SECURITY AND PRIVACY ISSUES

17. • Decoy system is a different approach for securing data in the cloud
using nasty decoy technology.
• data access in the cloud and sense irregular data access patterns.
• We use this technology to begin disinformation attacks against
malicious insiders, preventing them from distinguishing the valid
aware customer data from bogus useless.
DECOY SYSTEM

18. DECOY SYSTEM

19. • Extending the cloud closer to the things that generate and act on
data benefits the business in the following ways:
• Greater business agility: With the right tools, developers can quickly
develop fog applications and deploy
them where needed.
• Better security: Protect your fog nodes using the same policy,
controls, and procedures you use in other
parts of your IT environment. Use the same physical security and
ADVANTAGE OF FOG COMPUTING

20. • ● Deeper insights, with privacy control: Analyze sensitive data locally
instead of sending it to the cloud for
analysis.
• ● Lower operating expense: Conserve network bandwidth by
processing selected data locally instead of
sending it to the cloud for analysis.
ADVANTAGE OF FOG COMPUTING

21. CONCLUSION
• Fog computing gives the cloud a companion to handle the two
exabytes of data generated daily from the Internet of
Things.
• Processing data closer to where it is produced and needed solves
the challenges of exploding data volume, variety, and velocity.
•
Fog computing accelerates awareness and response to events by
eliminating a round trip to the cloud for analysis.

22. CONCLUSION
• It avoids the need for costly bandwidth additions by offloading
gigabytes of network traffic from the core network.
• It also protects sensitive IoT data by analyzing it inside company
walls. Ultimately, organizations that adopt fog
computing gain deeper and faster insights, leading to increased
business agility, higher service levels, and
improved safety.

23. • 2010, IBM (describing their Rational software design)
• “A World with 1 Trillion Connected Devices” … by 2015
• 2011, Ericsson CEO Hans Vestberg
• “50 Billion Connected Devices” … by 2020
• 2013, ABI Research report
• “30 Billion” … by 2020
• 2013, Morgan Stanley report
• “75 Billion Devices Connected to the IoT” … by 2020
• 2014, Intel infographic
• “31 billion devices connected to the Internet” … by 2020
• 2014, ABI Research updated report
• “41 billion active wireless connected devices” … by 2020
FUTURE SCOPE & PREDICTIONS

24. FUTURE SCOPE & PREDICTIONS
• Cellular M2M Devices send on average: 2 MBytes / month
• India: 15M cellular devices (8% of all M2M): 30 TBytes / Month
Total cellular M2M data use is increasing
• Number of cellular M2M devices (at 5%): 2.5 Billion
• Data (assuming 4MB / month): 10,000,000 TBytes / month
With 50 Billion Devices by 2020
• Transmissions and total data haystacks are enormous
• Demands “processing at the edge” … at device  Fog Computing
Even with conservative estimates

25. • Sources
• Fog Computing and the Internet of Things: Extend
http://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-
• Cisco Fog Computing Solutions: Unleash the Power of Internet
• http://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf
• A Simple Explanation Of 'The Internet Of Things' – Forbes
• http://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-
understand/#793c56ca6828
• The Internet of Things (IoT) Starts with Intel Inside®
• http://www.intel.com/content/www/us/en/internet-of-things/overview.html
BIBLIOGRAPHY