Secure Fog Computing System using Emoticon Technique

International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169
Volume: 5 Issue: 7 808 – 811
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IJRITCC | July 2017, Available @ http://www.ijritcc.org
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Secure Fog Computing System using Emoticon Technique
Harish Kumar, Sampada Shinde, Pratvina Talele
MIT College of Engineering, Pune
Abstract—Fog computing is a distributed computing infrastructure in whichsome application services are provided at the edge of the network in
smart devices( IoT devices) and some applications are handled in cloud. Fog computing operates on network ends instead of working entirely
from a centralized cloud. It facilitates the operation of storage, compute, analysis and other services between edge devices mostly IoT devices
and cloud computing data centres. The main objective of Fog computing is to process the data close to the edge devices .The problem that occurs
in Fog is confidentiality and security of data . To overcome this problem, we have proposed the Dual-Encryption to data using Emoticon
Technique which is combination of Cryptography and Steganography. In this method, first data is encrypted and then encrypted data is hidden
with the cover text like emoticons. So Dual-Encryption enhances data security and reliability. Even if the covered text is accessed by
unauthorized person, only encrypted data of original data can be viewed not the actual data.
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I. INTRODUCTION
Fog computing is a new technology which extends cloud
computing towards the edge of Network [2]. Fog computing
machines provide services with reduced latency and improved
Quality of Service. In cloud computing concept, all the data
produced from the users/edge devices will be directly stored
into the cloud and this data is analysed by warehouses for
analytical purpose. But in fog computing, the users will be
notified about what the actions are needed to be taken on the
data and stored it into the cloud.In the fog computing process,
applications comes to the data not the data to the applications
[1]. Fog computing enables a new set of applications and
services also it acts as an interface between the cloud and the
fog particularly for data management and analytics.
A. Fog Computing
The Fog acts as an interface between edge devices (IoT) and
the cloud which provides necessary extra functionalities for
application-specific processing like filtering, extracting and
aggregation before transmitting the data to the cloud.
Fog computing is a highly virtualized platform that provides
compute, storage, analysis and networking services between
edge devices [2]. Fog computing has lots of advantages like
widespread geographical distribution of data, information
about the physical location of a device to another application or
user, requires less time(low latency), heterogeneity, mobility
support, the predominant role of wireless access, the strong
presence of streaming and real-time applications, the
orchestration of large scale control systems, hierarchical
networking, and computing structures.
Fig. 1.Fog Computing as an interface between edge devices and cloud
B. Fog Engines
Fog-engine provides real time data analytic as well as
facilitates edge devices (IoT) to communicate with each other
and with the cloud. Fog-engine can be modified according to
the application and agile to heterogeneous platform that is
integrated to an IoT device [2]. It allows data processing in the
cloud and in the distributed grid of connected IoT devices
located at the network edge. It expedite for offloading data and
interacting with the cloud as a gateway [2].

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Fig. 2.Fog Engine in Cloud Based Computing System
C. Data Security
In Fog computing, there are many security issues and even the
encryption of data is not safe method [1].Security and privacy
should be maintained in every layer while designing Fog
computing system [3]. Data theft attacks is major issue in fog
computing. If an unauthorized person is an insider then the
chances of data being misused are more. We have to provide
high level of data security in Fog computing system.
II. LITERATURE SURVEY
A. Big Data
Big data refers to the substantial amounts of unstructured,
semi structured or structured data that flows continuously
through and around consortium, including text, video, data
from sensors, and transactional records [2]. Big data analytics
describes the process of performing complex analytical tasks
on data that typically includes grouping, aggregation, or
iterative processes [2].Data which is generated from Internet of
Things or edge devices will grow exponentially as the number
of connected nodes increases.
Figure.3 provides an overview of a flow of data analytics in
Fog engine. The first step is to perform collection of data from
edge devices or Internet of Things. Data cleaning is the next
step which is used to reduce the data size by removing
redundant information which enhances data analytics and
processing speed. Data cleaning also detects and corrects errors
and any inconsistencies from data to improve its quality of
service[2].Data is analysed depending upon users request or
query and based on the results many decisions or interpretation
could be performed.
Fig. 3.Big Data Analytics in Fog Computing System
In Fog computing system, instead of sending all data received
from edge devices or IoT to the cloud, only summarized result
of a data is sent to the cloud. Fog engine receives all the data
from edge devices or IoT, and it is responsible for performing
local data analytics near the data source itself rather than
sending it to cloud. Fog engine performs all the major
functions of Big data. As the data is pre-processed, filtered and
cleaned in the Fog engine itself before offloading the data to
the cloud, the amount of data which is being carried is lower
than the data produced by edge devices or IoT’s. Fog engines
provides a very limiting enumerating power and storage
capacity as compared with cloud but Fog engine offers high
level of fault tolerance and can be integrated with mobile IoT
nodes or edge devices.
B. Problem Statement
Security is one of the major concerns because there are lots of
sensitive data around us. It could be any company pricing
details, or even it could be national secret. All thedata must be
secured and should make sure that it has all necessary methods
in it, which makes an attacker difficult to crack the key. This
paper primarily concentrates on security and privacy of data as

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key part. In the system of cloud, though secured data is sent to
the fog from cloud, predicting the security threat in the fog
such as man in the middle attacks, we would like to add a
second layer of security within the level of fog.
C. Existing Solution
In fog at present AES encryption algorithm is considered as
an exemplary Advanced Encryption Standard(AES) algorithm
consisting data encryption in first phase and forwarding
corresponding data to fog engine for further analysis in second
while in third phase it offers decryption of encrypted data using
fog engine to get valid data [1].
For encrypting the data AES algorithm requires more
processing time along with complex security overhead. This
algorithm is efficient but does not provide preservation and
complex privacy of data
III. PROPOSED SOLUTION
To avoid the above problem a solution is introduced by
putting forward Emoticons technique where two layer
encryption is provided. In this approach, the emoticons which
are generally used in chats, short message services and
comments, are used as cover media to deliver the data in a
hidden manner [4]. The emoticon is a type of icons or pictorial
representation of text that interprets a user’s perception and
reflex in text mode as shown in Figure. 4. These are popularly
used icons especially where there is a restriction on the number
of characters.
Fig. 4.Emoticons used for Encryption
Initially the data is collected by edge devices. Before
transmitting the data to the Fog Engine, the data is encrypted
using emoticon technique. In first phase, data is encrypted
using Cryptography, where data is transmitted in particular
form. And these encrypted data will be input to second phase
of emoticon technique. In second phase, encrypted data is
hidden behind the cover media that are the emoticons. Again
these emoticons are put into cover text which finally generates
stego text to be transmitted.
The receiver on the other end receives the stego text then
first extracts the emoticons from the cover text and then maps
the meaning of each emoticon to get the encrypted message.
Then the authorized user can decrypt the message using their
own private key to decrypt the message to finally get the actual
data.
Fig. 5.System architecture using Emoticon Technique for
Encryption
IV. ADVANTAGES AND LIMITATIONS
In this technique, first data is Encrypted and then hiding the
encrypted data with the cover text like emoticons makes nearly
impossible to access the data. So, even if the covered media is
accessed by attacker, only encrypted data of original message
can be viewed. Hence by adding encryption to already
encrypted data ensures confidentiality of the communication
and increases reliability.
The only limitation of proposed method is that, it requires
lots of memory since encrypting the data using cover text
(emoticons) requires additional memory.
V. CONCLUSION
This paper focuses on Data Security. We proposed Emoticon
Technique for Encryption of Data in Fog Computing which is a
combination of Cryptography and Steganography which is in
progress. It adds a second layer of data security and provides
high complex security of data.
VI. REFERENCES
[1] Akhilesh Vishwanath, RamyaPeruri, Jing (Selena) He,
"Security in Fog Computing through Encryption",
International Journal of Information Technology and
Computer Science (IJITCS), Vol.8, No.5, pp.28-36, 2016.
DOI: 10.5815/ijitcs.2016.05.03
[2] F. Mehdipour, B. Javadi and A. Mahanti, "FOG-Engine:
Towards Big Data Analytics in the Fog," 2016 IEEE 14th Intl
Conf on Dependable, Autonomic and Secure Computing, 14th
Intl Conf on Pervasive Intelligence and Computing, 2nd Intl
Conf on Big Data Intelligence and Computing and Cyber

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Science and Technology Congress
(DASC/PiCom/DataCom/CyberSciTech), Auckland, 2016,
pp. 640-646.
[3] Yi S., Qin Z., Li Q. (2015) Security and Privacy Issues of Fog
Computing: A Survey. In: Xu K., Zhu H. (eds) Wireless
Algorithms, Systems, and Applications. WASA 2015. Lecture
Notes in Computer Science, vol 9204. Springer, Cham
[4] Miss. Madhura A. Bhoi, Miss. Barkha V. Budhwani, Miss.
Poonam R. Dhayagode, Miss. Tahurafeeza J. Sayyed, Miss.
PratvinaTalele, “Data Hiding using Emoticons”, December
16,Volume 4 Issue 12 , International Journal on Recent and
Innovation Trends in Computing and Communication
(IJRITCC), ISSN: 2321-8169, PP: 54 – 56

Secure Fog Computing System using Emoticon Technique

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