SlideShare a Scribd company logo
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2863
Easy to Implement Searchable encryption scheme for Cloud-assisted
Wireless Sensor Networks
Mr. Arun Kumar1, Ms. Anondita Guha 2, Mr. Vishnu A 3, Ms. Sneha Shiju 4
Mr. Varchas Shishir 5
1Assistant Professor, CSE Dept. SRM IST, TamilNadu, India,
2,3,4,5Student, Department of CSE. SRM IST , TamilNadu, India,
-----------------------------------------------------------------***-----------------------------------------------------------------
Abstract- Development of Wireless Sensor networks along
with cloud computing’s assistance has unparallely driven
the flourishment of the Industrial Internet of Things. With
the growth in newer technologies ,doors have opened for
newer risks in the field of cyber security specially in cloud-
assisted WSN’s (CWSN) data confidentiality. This problem
can be acknowledged in a reassuring manner through
Searchable Public-key Encryption. Theoretically it let
sensors to send public key cipher texts into cloud and
whoever owns these sensors can perform a search of type
word and gather data that was intended into the cloud
while side by side making sure that data confidentiality is
maintained. However when it comes to generating cipher
texts and keyword search, all the currently present and
substantially secured searchable public key encryption
produce extremely higher costs. Therefore, a lightweight
searchable public key encryption method (LSPE) is being
proposed in this paper along with meaningful security to
CWSNs. A great amount of computation based operations
are reduced through LSPE which have been take as
reference from earlier works. Hence, LSPE provides search
based performance nearly similar to some realistic
searchable symmetric encryption methods. Along with all
this LSPE conserves a healthy amount of time and energy
expense of sensors for the production of cipher texts.
Keywords- CWSNs, cloud computing, LSPE, IoT, Wireless
sensor networks.
1. INTRODUCTION
There is rapid emergence in Industrial Internet Of
Things(IIOT.) in the fourth industrial revolution . The use
of Industrial Internet Of Things mechanisms in
manufacturing is IIOT.There are more generic roles in
various scenarios of WSNs and correlated cloud
computing mechanisms which are one of the most
valuable features of IIOT. example : environmental science,
agriculture, security defence etc. WSNs job is to create a
connection for the sensors to the internet with the use of
gateways, bound to the connection that exists in between
the WSN along with the Internet, A number of sensors are
placed in the auditing place compose a Wireless Sensor
Network ,and produce a quantity of sensor data that will
be forwarded by gateways. In particular, the growing
acquisition of Wireless Sensor Network’s or CWSNs is
believed to provide few different hurdles in using of
energy and data confidentiality.
Sensitive data are in general collected by sensors in
CWSNs generally and are then uploaded in to the cloud.
Thus making both of the passive as well as the active
attackers curious about the mentioned data. It has been
shown in multiple researches that cryptography to CWSNs
is brought into action in order to protect data
confidentiality, along with which multiple cryptographic
algorithms are utilized. The CWSNs sensors are proven to
be energy-intensive as well as computation power being
restricted up to a certain level. Therefore an encryption
schema that is supposedly energy efficient for can be
presented for secure as well as dynamic Wireless Sensor
Networks. Apart from all of this there are a few more
encryption methods that have been introduced in CWSNs,
such as mixed encryption scheme, authentic encryption
scheme, asymmetric encryption scheme and further more.
Data confidentiality is supposed to be maintained by a
cryptographic technique called searchable encryption (SE)
in CWSN. Presently, it is notably intriguing and a tough
task to make the search efficiency better than an
Searchable Public Encryption leaving out compromising
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2864
keywords’ semantic security. Theoretically it can be
attained through two possible methods first being the idea
of lessening the search complexity as in that the resulting
complexity becomes lesser compared to the sub linear.
The other method is to lessen the computation based
operations to a great extent while also making sure of the
sub-linear search complexity.
2. EXISTING SYSTEM
Smart metering , military defence, health care,
environmental monitoring and agriculture are the various
scenarios where a pivotal role is played by WSNs and
related cloud mechanisms which are also one of the most
valuable features of Industrial Internet Of Things.
The connection between sensors and the internet
by the Wireless Sensor Network is done via gateways.A
quantity of sensor message which is to be passed through
by gateways will be generated by a quantity of sensors
present in the auditing area which also contains a Wireless
Sensor Network.Data integrity and energy usage are the
main terms of the problems faced by the expanding
adoption of WSN,s specifically cloud assisted Wireless
Sensor Network.Sensitive data that is uploaded to the
cloud is usually fetched by the sensors in CWSN’s. This is
how potential passive attackers are unaware about all this
data .
The existing system holds a number of disadvantages as
explained below:
 Generally Energy-Intensive - The existing systems
such as the Searchable Symmetric Key Encryption
and Searchable Public Key Encryption for CSWN's
tend to take up a lot of sensor energy however
sensor's for CSWN's are seen to have lower or limited
energy forcing cloud to wrap up the search task as
quickly as possible thus making the existing systems
energy-intensive in general.
 Computing-Power-Limited - As said earlier CSWN
sensors hold a limited amount of energy and while
the cloud is supposed to finish the search task in that
limited amount, the computing power for large data
being limited loads high pressure on keyword search
system in CSWN's.
 High Energy Consumption - Having to complete
keyword search task in a limited amount of time in a
vast cloud sensor data it requires the cloud to run fast
computing algorithms which in return require lots of
energy to work thus making the existing systems
highly energy consuming.
 Less Data Confidentiality - Searchable Symmetric Key
Encryption requires the exact same key for all the
sensors present in it in order to produce a cipher text
thus making a compromise in one of the sensor by
anyone as a leakage of every sensor data present
there.
3. PROPOSED SYSTEM
We construct an LSPE based on the concepts of SPCHS.
Just like XW15 this scheme also creates a star like
structure among searchable cipher texts to reach subb-
linear search complexity.
 Leaving out immolating semantic security of tokens
it becomes a fascinating and chalking task to increase
search efficiency of Searchable Public
Encryption.Two ways that can be done to achieve
this can be bydecreasing the search complexity that
the sub-linear complexity is more than resulting
complexity or we can reduce the amount of
computation intensive.
 The proposed system comes up with the following
advantages:
 Not Energy-Intensive - While the existing systems
have been found to be energy intensive in general the
proposed Easy to Implement Searchable encryption
scheme for CWSN’s removed this issue making the
system non- energy intensive one.
 Computing-Power Not Limited - The proposed
system does not limit the computational power like
the currently existing system thus providing the
system to perform computational algorithms that
require higher power and give better results.
 Less energy consumption - As the proposed system is
not energy intensive it allows searchable tasks to be
completed at a lower energy consumption rate when
compared to the existing systems.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2865
High data confidentiality - The proposed system uses the
concept of Searchable Public Key Encryption thus making
only the public key a mandatory element to be stored in the
sensors while the private key stays with the owner thus not
compromising other sensor data on the compromise of a
single sensor.
4. SYSTEM REQUIREMENTS
Searchable Encryption is believed to be a dependable
technique of cryptography in order to maintain the
integrity of data. When SE is pertained into the Cloud
based Wireless sensor networks as shown in the above
figure, cipher texts that can be searched based on
keywords can be produced by the sensors for their
information and then transfer it all into cloud.
Figure 1- System Architecture For Lspe In Cwsn
In order to get desired information, a search operation for
a keyword is performed by the owner in the cloud. All the
similar/ matching cipher texts are determined by the
cloud and send them as a response to the owner. At last
the owner performs decryption over the desired data.
Regarding the security, Searchable Encryption makes sure
that either of the eavesdropper or any cloud that is non
trusted is not able to learn any information regarding the
data present in the sensors in any manner.
Presently, there are two types into which a Searchable
Encryption is categorized into. These are SSE and SPE . It
is necessary for an SSE to have the exact same symmetric
key for every sensor in order to produce in cipher text for
an application of CWSN. Thus a compromise in one of the
sensors by a foe will lead to the leakage of data from every
other sensor too. Luckily, unlike SSE, SPE only makes the
storage of public key into every sensor a necessary task.
Thus making SPE a more secure mechanism compare to
SSE. However it is found that the currently present SPE
schemes are not practical for CWSNs when it comes to
performance.
Sensors usually are seen to have only a certain amount of
energy in CWSNs making it necessary for the cloud to
finish a search job as early as it possibly can. Therefore a
realistic SPE schema is believed to be largely coherent
when comes to producing cipher texts and keyword
search. However the SPE schemes re noted to be
incompetent to achieve the given goals. The search
complexity for the SPE’s pioneering work is linear to the
total amount of cipher texts.
Figure 2- System Architecture Workflow
5. MODULE DESCRIPTION
The proposed LSPE schema is build on the following
modules and phases that have been described below as
follows: -
5.1 MODULE 1- SETUP PHASE
Setup phase is the phase in which the sensors owner is
supposed to select a security related parameter 1k, then
running a algorithm PKE1^k of PKE schema in order to
show a (Public Key”, Searchable Key”). The (Public Key,
Public Key”) keys are then stored into every sensor after
which the owner deploys the above mentioned sensors
into the real world for the purpose of collecting data.
5.2 MODULE 2- DATA COLLECTION
The phase of data collection can be explained through the
following. Assume that a sensor desires to upload into the
cloud all of the data it has collected namely T. For that to
happen it performs algorithm Structure (PK) in order to
initialize a hidden structure (PUBLIC ,PRIVATE) and then
uploads into the cloud the public key. Next it performs
extraction of definite keywords from the data we named
as T. Assuming that the keywords that were extracted are
{ X1,… ,Xm }. After this the algorithm Encryption (PK,Xi,
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2866
PRIVATE) for i Ꞓ [1,m] for generating cipher texts that are
keyword searchable { C1, …,Cm }, selecting a randomly
chosen symmetric key SK and executing the algorithm
Encryption (PKE)(Public Key’,SK) in order to show a
cipher text C(PKE) and executing the algorithm Encryption
(SKE)(SK,T) in order of producing cipher text C(SKE). At
the end it finally performs uploading of all the produced
cipher texts{C1,…, Cm, C(PKE), C(SKE) }.
5.3 MODULE 3- DATA RETRIEVAL
The data retrieval phase can be explained as the following-
Assuming that the sensor’s owner wishes to extract data
from the cloud for a keyword Ni. It executes the Trapdoor
algorithm (SK, Ni) in order to produce the search trapdoor
T(Ni) for the keyword Ni later securely uploading the
search trapdoor T(Ni) into the cloud. Firstly a search
algorithm (Public Key, PUBLIC, T(Ni),C) is performed
every hidden structures’ public areas in the attempt so
that to determine every the similar cipher texts. Next all
the determined cipher texts’ PKE as well as SKE parts are
passed on to the owner by the cloud. At the end the
desired data is attained by the owner through decryption
of the received PKE along with SKE parts.
This can be explained better through the given example.
Assuming that {C1, …, Cm, C(PKE), C(SKE) } are a set of
similar cipher texts, which means that there is a section Ck
Ꞓ {C1, .., Cm} that holds the keyword Ni. The cloud’s next
task is to pass on the C(PKE) and C(SKE) to the authority.
The authority or called (the owner) , then perform
decryption of the part C(PKE) with help of the private key
it has Searchable Key’ in order to improve a symmetric key
K, then performing same action to the SKE part C(SKE)
using produced SK(K) in order to improve the desired
information T.
Figure 3- Use Case Diagram
6. SYSTEM REQUIREMENTS
The elements that build the proposed Lightweight
searchable public key encryption schema constitutes of -
Sensors, gateways and servers that form the base for the
Cloud wireless sensor networks. These components are
run using 5 SPCHS based on which the proposed algorithm
LSPE is being developed. SPCHS defines various different
algorithms, which are algorithms
Setup,Structure,Encryption, ,Trapdoor,Search.
They are :
ALGORITHM SETUP-
The most important and basic of the 5 algorithms is the
Algorithm setup. It generates some kind of system
parameters for the remaining algorithms based on the
requirements of the security degree. These parameters are
majorly made up of 2 parts one master public key and the
other one is master private key.
In case of CWSNs, the authority of the sensors implements
the Algorithm. All the sensors are then used to accumulate
the master public key, whereas the master private key is
securely preserved by owner of the sensors.
ALGORITHM STRUCTURE-
Algorithm structure holds responsibility for initializing a
secured hidden structure which is later used for the
encryption of the algorithm. A hidden structure that has
been initialized constituted of two parts- a private and a
public part. In case of CWSNs, the sensor implements this
algorithms before the 1st time for running the algorithm
encryption.
The sensor uploads the public part produced into the
cloud while securely storing the private part.
ALGORITHM ENCRYPTION-
The action of generating searchable cipher text of a
particular keyword is performed by algorithm Encryption.
This cipher text that has been generated holds a hidden
relationship with cipher texts that had been previously
produced. In case of CWSNs, a sensor implements the
algorithm incase it wishes to cipher texts that are
searchable through keywords for some gained data. The
sensor then uploads the ciphertext produced to the cloud
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2867
and in the end updating the private parts of the hidden
structure for the upcoming cipher texts.
ALGORITHM TRAPDOOR-
The generation of keyword search trapdoor for a
particular keyword is done by Trapdoor algorithm and it
is necessary that the master private key is taken as an
input into it. In case of CWSNs, a sensor's owner runs this
algorithm incase he/she desires to retrieve the particular
keywords data present in the sensor and later this
trapdoor is sent into the cloud as an authorized keyword
search task. As the master private key is only known to the
owner, except the owner no one could perform keyword
search in cloud.
ALGORITHM SEARCH-
For finding every same cipher text to a particular keyword
we use Algorithm search. In case of CWSNs, the clouds
performs this algorithm to determine all similar cipher
text from the owner upon receiving a keyword search
trapdoor.
7. CONCLUSION
An able and easy-to-demonstrate and implement SSE
scheme is provided in his paper, it has one round of
communication, O(n) times of computations over n
documents. Use of hash chaining instead of chain of
encryption makes is suitable for lightweight applications.
Relative positions and frequency of the word searched
cannot be detected, unlike the previous SSE schemes for
string search.
Probabilistic trapdoors have been proposed in Searchable
Symmetric Key Encryption for String search.Proof of non-
adaptive security of our schema against honest-but-
curious server is also provided. A new term of search
pattern privacy is also introduced, which gives a measure
of security against the leakage from trapdoor. It has been
proved that the scheme is more secure under search
pattern indistinguishably definition. Modifications have
been introduced in the scheme so that the, scheme can be
made useful against non-passive adversaries at cost of
more rounds of communication and memory space. We
have validated the scheme against two unique commercial
data sets.
REFERENCES
[1] Generating SPE Ciphertext with Hidden Structures for
Fast Keyword Search published by Qiahong Wu,Wei
Wang,Willy Susilo,Peng Xu,Joseph Domingo Ferrer, Hai Jin
and Ferrer.
[2] LSPE for CWSN’s published by Shuanghong He,Willy
Susil, Hai Jin and Peng Xu.
[3] Data exfiltration from Internet of Things devices: IOS
devices as case studies
[4] Everything you need to know about the Industrial
Internet of Things
[5] Grand View Research, Industrial IoT Market Size
Worth $932.62 Billion By 2025
[6] Evolution of WSN’s towards the IOT: A survey.
[7] A domain-based multi cluster SIP solution for mobile
Ad Hoc network
[8] A secure cross-domain SIP solution for mobile Ad Hoc
network using dynamic clustering
[9] Wireless sensors networks for Internet of Things, pp.
1-6, 2014.
[10] A survey on the privacy preserving data aggregation
in wireless sensor networks pp. 162-180, 2015
[11] Deterministic and Efficiently Searchable Encryption

More Related Content

PDF
IRJET- A Privacy-Preserving Location Monitoring System for Wireless Sensor Ne...
PDF
A-SURVEY SECURITY PROTOCOL FOR WIRELESS SENSOR NETWORK
PDF
Review for Secure Data Aggregation in Wireless Sensor Networks
PPTX
wireless sensor networks & application :forest fire detection
PDF
IMPLEMENTATION OF SECURITY PROTOCOL FOR WIRELESS SENSOR
PPTX
Data aggregation in wireless sensor network , 11751 d5811
PDF
A Survey on Secure Alternate Path Selection for Enhanced Network Lifetime in ...
PDF
IJRET-V1I1P1 - Forest Fire Detection Based on Wireless Image Processing
IRJET- A Privacy-Preserving Location Monitoring System for Wireless Sensor Ne...
A-SURVEY SECURITY PROTOCOL FOR WIRELESS SENSOR NETWORK
Review for Secure Data Aggregation in Wireless Sensor Networks
wireless sensor networks & application :forest fire detection
IMPLEMENTATION OF SECURITY PROTOCOL FOR WIRELESS SENSOR
Data aggregation in wireless sensor network , 11751 d5811
A Survey on Secure Alternate Path Selection for Enhanced Network Lifetime in ...
IJRET-V1I1P1 - Forest Fire Detection Based on Wireless Image Processing

What's hot (17)

PDF
Security based Clock Synchronization technique in Wireless Sensor Network for...
PDF
S04404116120
PPT
WIRELESS SENSOR NETWORK
PDF
IRJET- An IoT Based Forest Fire Detection and Prevention System using Raspber...
PDF
A Survey on Routing Protocols in Wireless Sensor Networks
PDF
Fire Monitoring System for Fire Detection Using ZigBee and GPRS System
PDF
Secure data dissemination protocol in wireless sensor networks using xor netw...
PDF
Scalable and Robust Hierarchical Group of Data in Wireless Sensor Networks
PDF
Enhancing Data Transmission and Protection in Wireless Sensor Node- A Review
PDF
IRJET- Appraisal of Secure Data Aggregation protocol for Wireless Sensor ...
PPTX
Intrusion Detection in A Smart Forest-Fire Early Warning Sensory System
PDF
Modelling of wireless sensor networks for detection land and forest fire hotspot
PDF
Concealed Data Aggregation with Dynamic Intrusion Detection System to Remove ...
PPTX
Wireless Body Area Networking
PPTX
Wsn protocols
PDF
IRJET- Enhanced ID based Data Aggregation and Detection Against Sybil Attack ...
PDF
A Case Study on Authentication of Wireless Sensor Network based on Virtual Ce...
Security based Clock Synchronization technique in Wireless Sensor Network for...
S04404116120
WIRELESS SENSOR NETWORK
IRJET- An IoT Based Forest Fire Detection and Prevention System using Raspber...
A Survey on Routing Protocols in Wireless Sensor Networks
Fire Monitoring System for Fire Detection Using ZigBee and GPRS System
Secure data dissemination protocol in wireless sensor networks using xor netw...
Scalable and Robust Hierarchical Group of Data in Wireless Sensor Networks
Enhancing Data Transmission and Protection in Wireless Sensor Node- A Review
IRJET- Appraisal of Secure Data Aggregation protocol for Wireless Sensor ...
Intrusion Detection in A Smart Forest-Fire Early Warning Sensory System
Modelling of wireless sensor networks for detection land and forest fire hotspot
Concealed Data Aggregation with Dynamic Intrusion Detection System to Remove ...
Wireless Body Area Networking
Wsn protocols
IRJET- Enhanced ID based Data Aggregation and Detection Against Sybil Attack ...
A Case Study on Authentication of Wireless Sensor Network based on Virtual Ce...
Ad

Similar to IRJET- Easy to Implement Searchable Encryption Scheme for Cloud-Assisted Wireless Sensor Networks (20)

PDF
A PARALLEL AND FORWARD PRIVATE SEARCHABLE PUBLIC KEY ENCRYPTION FOR CLOUD BAS...
PDF
Multi-stage secure clusterhead selection using discrete rule-set against unkn...
PDF
SEAD: Source Encrypted Authentic Data for Wireless Sensor Networks
PDF
A SURVEY ON SECURITY IN WIRELESS SENSOR NETWORKS
PDF
A SURVEY ON SECURITY IN WIRELESS SENSOR NETWORKS
PDF
A SURVEY ON SECURITY IN WIRELESS SENSOR NETWORKS
PDF
Pe2 a public encryption with two ack approach to
PDF
Multilink Routing in Wireless Sensor Networks with Integrated Approach for Hi...
PDF
V 14 15432 8feb 27jan 6sep18 ch
PDF
Tactical approach to identify and quarantine spurious node participation requ...
PDF
CROSS LAYER INTRUSION DETECTION SYSTEM FOR WIRELESS SENSOR NETWORK
PDF
An Intuitionistic Fuzzy Sets Implementation for Key Distribution in Hybrid Me...
PDF
29 6 jul17 29may 7308 ijeecs paper_july_6 edit septian(edit)
PDF
Public encryption with two ack approach to mitigate wormhole attack in wsn
PDF
A condition-based distributed approach for secured privacy preservation of no...
PDF
A N E NERGY -E FFICIENT A ND S CALABLE S LOT - B ASED P RIVACY H OMOMOR...
PDF
AN ENERGY-EFFICIENT AND SCALABLE SLOTBASED PRIVACY HOMOMORPHIC ENCRYPTION SCH...
PDF
n-Tier Modelling of Robust Key management for Secure Data Aggregation in Wire...
PDF
Cluster-based Wireless Sensor Network (WSN) Methods for Secure and Efficient ...
PDF
Security Management in Wireless Sensor Network (WSN)
A PARALLEL AND FORWARD PRIVATE SEARCHABLE PUBLIC KEY ENCRYPTION FOR CLOUD BAS...
Multi-stage secure clusterhead selection using discrete rule-set against unkn...
SEAD: Source Encrypted Authentic Data for Wireless Sensor Networks
A SURVEY ON SECURITY IN WIRELESS SENSOR NETWORKS
A SURVEY ON SECURITY IN WIRELESS SENSOR NETWORKS
A SURVEY ON SECURITY IN WIRELESS SENSOR NETWORKS
Pe2 a public encryption with two ack approach to
Multilink Routing in Wireless Sensor Networks with Integrated Approach for Hi...
V 14 15432 8feb 27jan 6sep18 ch
Tactical approach to identify and quarantine spurious node participation requ...
CROSS LAYER INTRUSION DETECTION SYSTEM FOR WIRELESS SENSOR NETWORK
An Intuitionistic Fuzzy Sets Implementation for Key Distribution in Hybrid Me...
29 6 jul17 29may 7308 ijeecs paper_july_6 edit septian(edit)
Public encryption with two ack approach to mitigate wormhole attack in wsn
A condition-based distributed approach for secured privacy preservation of no...
A N E NERGY -E FFICIENT A ND S CALABLE S LOT - B ASED P RIVACY H OMOMOR...
AN ENERGY-EFFICIENT AND SCALABLE SLOTBASED PRIVACY HOMOMORPHIC ENCRYPTION SCH...
n-Tier Modelling of Robust Key management for Secure Data Aggregation in Wire...
Cluster-based Wireless Sensor Network (WSN) Methods for Secure and Efficient ...
Security Management in Wireless Sensor Network (WSN)
Ad

More from IRJET Journal (20)

PDF
Enhanced heart disease prediction using SKNDGR ensemble Machine Learning Model
PDF
Utilizing Biomedical Waste for Sustainable Brick Manufacturing: A Novel Appro...
PDF
Kiona – A Smart Society Automation Project
PDF
DESIGN AND DEVELOPMENT OF BATTERY THERMAL MANAGEMENT SYSTEM USING PHASE CHANG...
PDF
Invest in Innovation: Empowering Ideas through Blockchain Based Crowdfunding
PDF
SPACE WATCH YOUR REAL-TIME SPACE INFORMATION HUB
PDF
A Review on Influence of Fluid Viscous Damper on The Behaviour of Multi-store...
PDF
Wireless Arduino Control via Mobile: Eliminating the Need for a Dedicated Wir...
PDF
Explainable AI(XAI) using LIME and Disease Detection in Mango Leaf by Transfe...
PDF
BRAIN TUMOUR DETECTION AND CLASSIFICATION
PDF
The Project Manager as an ambassador of the contract. The case of NEC4 ECC co...
PDF
"Enhanced Heat Transfer Performance in Shell and Tube Heat Exchangers: A CFD ...
PDF
Advancements in CFD Analysis of Shell and Tube Heat Exchangers with Nanofluid...
PDF
Breast Cancer Detection using Computer Vision
PDF
Auto-Charging E-Vehicle with its battery Management.
PDF
Analysis of high energy charge particle in the Heliosphere
PDF
A Novel System for Recommending Agricultural Crops Using Machine Learning App...
PDF
Auto-Charging E-Vehicle with its battery Management.
PDF
Analysis of high energy charge particle in the Heliosphere
PDF
Wireless Arduino Control via Mobile: Eliminating the Need for a Dedicated Wir...
Enhanced heart disease prediction using SKNDGR ensemble Machine Learning Model
Utilizing Biomedical Waste for Sustainable Brick Manufacturing: A Novel Appro...
Kiona – A Smart Society Automation Project
DESIGN AND DEVELOPMENT OF BATTERY THERMAL MANAGEMENT SYSTEM USING PHASE CHANG...
Invest in Innovation: Empowering Ideas through Blockchain Based Crowdfunding
SPACE WATCH YOUR REAL-TIME SPACE INFORMATION HUB
A Review on Influence of Fluid Viscous Damper on The Behaviour of Multi-store...
Wireless Arduino Control via Mobile: Eliminating the Need for a Dedicated Wir...
Explainable AI(XAI) using LIME and Disease Detection in Mango Leaf by Transfe...
BRAIN TUMOUR DETECTION AND CLASSIFICATION
The Project Manager as an ambassador of the contract. The case of NEC4 ECC co...
"Enhanced Heat Transfer Performance in Shell and Tube Heat Exchangers: A CFD ...
Advancements in CFD Analysis of Shell and Tube Heat Exchangers with Nanofluid...
Breast Cancer Detection using Computer Vision
Auto-Charging E-Vehicle with its battery Management.
Analysis of high energy charge particle in the Heliosphere
A Novel System for Recommending Agricultural Crops Using Machine Learning App...
Auto-Charging E-Vehicle with its battery Management.
Analysis of high energy charge particle in the Heliosphere
Wireless Arduino Control via Mobile: Eliminating the Need for a Dedicated Wir...

Recently uploaded (20)

PPTX
Welding lecture in detail for understanding
PDF
SM_6th-Sem__Cse_Internet-of-Things.pdf IOT
PPTX
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
PPTX
UNIT 4 Total Quality Management .pptx
PPTX
web development for engineering and engineering
PDF
TFEC-4-2020-Design-Guide-for-Timber-Roof-Trusses.pdf
DOCX
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
PDF
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
PDF
Enhancing Cyber Defense Against Zero-Day Attacks using Ensemble Neural Networks
PPTX
CYBER-CRIMES AND SECURITY A guide to understanding
PDF
Well-logging-methods_new................
PDF
R24 SURVEYING LAB MANUAL for civil enggi
PDF
BMEC211 - INTRODUCTION TO MECHATRONICS-1.pdf
PDF
Model Code of Practice - Construction Work - 21102022 .pdf
PPTX
IOT PPTs Week 10 Lecture Material.pptx of NPTEL Smart Cities contd
PPTX
Sustainable Sites - Green Building Construction
PPTX
Infosys Presentation by1.Riyan Bagwan 2.Samadhan Naiknavare 3.Gaurav Shinde 4...
PPTX
OOP with Java - Java Introduction (Basics)
PPTX
Lecture Notes Electrical Wiring System Components
PPTX
Internet of Things (IOT) - A guide to understanding
Welding lecture in detail for understanding
SM_6th-Sem__Cse_Internet-of-Things.pdf IOT
Recipes for Real Time Voice AI WebRTC, SLMs and Open Source Software.pptx
UNIT 4 Total Quality Management .pptx
web development for engineering and engineering
TFEC-4-2020-Design-Guide-for-Timber-Roof-Trusses.pdf
ASol_English-Language-Literature-Set-1-27-02-2023-converted.docx
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
Enhancing Cyber Defense Against Zero-Day Attacks using Ensemble Neural Networks
CYBER-CRIMES AND SECURITY A guide to understanding
Well-logging-methods_new................
R24 SURVEYING LAB MANUAL for civil enggi
BMEC211 - INTRODUCTION TO MECHATRONICS-1.pdf
Model Code of Practice - Construction Work - 21102022 .pdf
IOT PPTs Week 10 Lecture Material.pptx of NPTEL Smart Cities contd
Sustainable Sites - Green Building Construction
Infosys Presentation by1.Riyan Bagwan 2.Samadhan Naiknavare 3.Gaurav Shinde 4...
OOP with Java - Java Introduction (Basics)
Lecture Notes Electrical Wiring System Components
Internet of Things (IOT) - A guide to understanding

IRJET- Easy to Implement Searchable Encryption Scheme for Cloud-Assisted Wireless Sensor Networks

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2863 Easy to Implement Searchable encryption scheme for Cloud-assisted Wireless Sensor Networks Mr. Arun Kumar1, Ms. Anondita Guha 2, Mr. Vishnu A 3, Ms. Sneha Shiju 4 Mr. Varchas Shishir 5 1Assistant Professor, CSE Dept. SRM IST, TamilNadu, India, 2,3,4,5Student, Department of CSE. SRM IST , TamilNadu, India, -----------------------------------------------------------------***----------------------------------------------------------------- Abstract- Development of Wireless Sensor networks along with cloud computing’s assistance has unparallely driven the flourishment of the Industrial Internet of Things. With the growth in newer technologies ,doors have opened for newer risks in the field of cyber security specially in cloud- assisted WSN’s (CWSN) data confidentiality. This problem can be acknowledged in a reassuring manner through Searchable Public-key Encryption. Theoretically it let sensors to send public key cipher texts into cloud and whoever owns these sensors can perform a search of type word and gather data that was intended into the cloud while side by side making sure that data confidentiality is maintained. However when it comes to generating cipher texts and keyword search, all the currently present and substantially secured searchable public key encryption produce extremely higher costs. Therefore, a lightweight searchable public key encryption method (LSPE) is being proposed in this paper along with meaningful security to CWSNs. A great amount of computation based operations are reduced through LSPE which have been take as reference from earlier works. Hence, LSPE provides search based performance nearly similar to some realistic searchable symmetric encryption methods. Along with all this LSPE conserves a healthy amount of time and energy expense of sensors for the production of cipher texts. Keywords- CWSNs, cloud computing, LSPE, IoT, Wireless sensor networks. 1. INTRODUCTION There is rapid emergence in Industrial Internet Of Things(IIOT.) in the fourth industrial revolution . The use of Industrial Internet Of Things mechanisms in manufacturing is IIOT.There are more generic roles in various scenarios of WSNs and correlated cloud computing mechanisms which are one of the most valuable features of IIOT. example : environmental science, agriculture, security defence etc. WSNs job is to create a connection for the sensors to the internet with the use of gateways, bound to the connection that exists in between the WSN along with the Internet, A number of sensors are placed in the auditing place compose a Wireless Sensor Network ,and produce a quantity of sensor data that will be forwarded by gateways. In particular, the growing acquisition of Wireless Sensor Network’s or CWSNs is believed to provide few different hurdles in using of energy and data confidentiality. Sensitive data are in general collected by sensors in CWSNs generally and are then uploaded in to the cloud. Thus making both of the passive as well as the active attackers curious about the mentioned data. It has been shown in multiple researches that cryptography to CWSNs is brought into action in order to protect data confidentiality, along with which multiple cryptographic algorithms are utilized. The CWSNs sensors are proven to be energy-intensive as well as computation power being restricted up to a certain level. Therefore an encryption schema that is supposedly energy efficient for can be presented for secure as well as dynamic Wireless Sensor Networks. Apart from all of this there are a few more encryption methods that have been introduced in CWSNs, such as mixed encryption scheme, authentic encryption scheme, asymmetric encryption scheme and further more. Data confidentiality is supposed to be maintained by a cryptographic technique called searchable encryption (SE) in CWSN. Presently, it is notably intriguing and a tough task to make the search efficiency better than an Searchable Public Encryption leaving out compromising
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2864 keywords’ semantic security. Theoretically it can be attained through two possible methods first being the idea of lessening the search complexity as in that the resulting complexity becomes lesser compared to the sub linear. The other method is to lessen the computation based operations to a great extent while also making sure of the sub-linear search complexity. 2. EXISTING SYSTEM Smart metering , military defence, health care, environmental monitoring and agriculture are the various scenarios where a pivotal role is played by WSNs and related cloud mechanisms which are also one of the most valuable features of Industrial Internet Of Things. The connection between sensors and the internet by the Wireless Sensor Network is done via gateways.A quantity of sensor message which is to be passed through by gateways will be generated by a quantity of sensors present in the auditing area which also contains a Wireless Sensor Network.Data integrity and energy usage are the main terms of the problems faced by the expanding adoption of WSN,s specifically cloud assisted Wireless Sensor Network.Sensitive data that is uploaded to the cloud is usually fetched by the sensors in CWSN’s. This is how potential passive attackers are unaware about all this data . The existing system holds a number of disadvantages as explained below:  Generally Energy-Intensive - The existing systems such as the Searchable Symmetric Key Encryption and Searchable Public Key Encryption for CSWN's tend to take up a lot of sensor energy however sensor's for CSWN's are seen to have lower or limited energy forcing cloud to wrap up the search task as quickly as possible thus making the existing systems energy-intensive in general.  Computing-Power-Limited - As said earlier CSWN sensors hold a limited amount of energy and while the cloud is supposed to finish the search task in that limited amount, the computing power for large data being limited loads high pressure on keyword search system in CSWN's.  High Energy Consumption - Having to complete keyword search task in a limited amount of time in a vast cloud sensor data it requires the cloud to run fast computing algorithms which in return require lots of energy to work thus making the existing systems highly energy consuming.  Less Data Confidentiality - Searchable Symmetric Key Encryption requires the exact same key for all the sensors present in it in order to produce a cipher text thus making a compromise in one of the sensor by anyone as a leakage of every sensor data present there. 3. PROPOSED SYSTEM We construct an LSPE based on the concepts of SPCHS. Just like XW15 this scheme also creates a star like structure among searchable cipher texts to reach subb- linear search complexity.  Leaving out immolating semantic security of tokens it becomes a fascinating and chalking task to increase search efficiency of Searchable Public Encryption.Two ways that can be done to achieve this can be bydecreasing the search complexity that the sub-linear complexity is more than resulting complexity or we can reduce the amount of computation intensive.  The proposed system comes up with the following advantages:  Not Energy-Intensive - While the existing systems have been found to be energy intensive in general the proposed Easy to Implement Searchable encryption scheme for CWSN’s removed this issue making the system non- energy intensive one.  Computing-Power Not Limited - The proposed system does not limit the computational power like the currently existing system thus providing the system to perform computational algorithms that require higher power and give better results.  Less energy consumption - As the proposed system is not energy intensive it allows searchable tasks to be completed at a lower energy consumption rate when compared to the existing systems.
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2865 High data confidentiality - The proposed system uses the concept of Searchable Public Key Encryption thus making only the public key a mandatory element to be stored in the sensors while the private key stays with the owner thus not compromising other sensor data on the compromise of a single sensor. 4. SYSTEM REQUIREMENTS Searchable Encryption is believed to be a dependable technique of cryptography in order to maintain the integrity of data. When SE is pertained into the Cloud based Wireless sensor networks as shown in the above figure, cipher texts that can be searched based on keywords can be produced by the sensors for their information and then transfer it all into cloud. Figure 1- System Architecture For Lspe In Cwsn In order to get desired information, a search operation for a keyword is performed by the owner in the cloud. All the similar/ matching cipher texts are determined by the cloud and send them as a response to the owner. At last the owner performs decryption over the desired data. Regarding the security, Searchable Encryption makes sure that either of the eavesdropper or any cloud that is non trusted is not able to learn any information regarding the data present in the sensors in any manner. Presently, there are two types into which a Searchable Encryption is categorized into. These are SSE and SPE . It is necessary for an SSE to have the exact same symmetric key for every sensor in order to produce in cipher text for an application of CWSN. Thus a compromise in one of the sensors by a foe will lead to the leakage of data from every other sensor too. Luckily, unlike SSE, SPE only makes the storage of public key into every sensor a necessary task. Thus making SPE a more secure mechanism compare to SSE. However it is found that the currently present SPE schemes are not practical for CWSNs when it comes to performance. Sensors usually are seen to have only a certain amount of energy in CWSNs making it necessary for the cloud to finish a search job as early as it possibly can. Therefore a realistic SPE schema is believed to be largely coherent when comes to producing cipher texts and keyword search. However the SPE schemes re noted to be incompetent to achieve the given goals. The search complexity for the SPE’s pioneering work is linear to the total amount of cipher texts. Figure 2- System Architecture Workflow 5. MODULE DESCRIPTION The proposed LSPE schema is build on the following modules and phases that have been described below as follows: - 5.1 MODULE 1- SETUP PHASE Setup phase is the phase in which the sensors owner is supposed to select a security related parameter 1k, then running a algorithm PKE1^k of PKE schema in order to show a (Public Key”, Searchable Key”). The (Public Key, Public Key”) keys are then stored into every sensor after which the owner deploys the above mentioned sensors into the real world for the purpose of collecting data. 5.2 MODULE 2- DATA COLLECTION The phase of data collection can be explained through the following. Assume that a sensor desires to upload into the cloud all of the data it has collected namely T. For that to happen it performs algorithm Structure (PK) in order to initialize a hidden structure (PUBLIC ,PRIVATE) and then uploads into the cloud the public key. Next it performs extraction of definite keywords from the data we named as T. Assuming that the keywords that were extracted are { X1,… ,Xm }. After this the algorithm Encryption (PK,Xi,
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2866 PRIVATE) for i Ꞓ [1,m] for generating cipher texts that are keyword searchable { C1, …,Cm }, selecting a randomly chosen symmetric key SK and executing the algorithm Encryption (PKE)(Public Key’,SK) in order to show a cipher text C(PKE) and executing the algorithm Encryption (SKE)(SK,T) in order of producing cipher text C(SKE). At the end it finally performs uploading of all the produced cipher texts{C1,…, Cm, C(PKE), C(SKE) }. 5.3 MODULE 3- DATA RETRIEVAL The data retrieval phase can be explained as the following- Assuming that the sensor’s owner wishes to extract data from the cloud for a keyword Ni. It executes the Trapdoor algorithm (SK, Ni) in order to produce the search trapdoor T(Ni) for the keyword Ni later securely uploading the search trapdoor T(Ni) into the cloud. Firstly a search algorithm (Public Key, PUBLIC, T(Ni),C) is performed every hidden structures’ public areas in the attempt so that to determine every the similar cipher texts. Next all the determined cipher texts’ PKE as well as SKE parts are passed on to the owner by the cloud. At the end the desired data is attained by the owner through decryption of the received PKE along with SKE parts. This can be explained better through the given example. Assuming that {C1, …, Cm, C(PKE), C(SKE) } are a set of similar cipher texts, which means that there is a section Ck Ꞓ {C1, .., Cm} that holds the keyword Ni. The cloud’s next task is to pass on the C(PKE) and C(SKE) to the authority. The authority or called (the owner) , then perform decryption of the part C(PKE) with help of the private key it has Searchable Key’ in order to improve a symmetric key K, then performing same action to the SKE part C(SKE) using produced SK(K) in order to improve the desired information T. Figure 3- Use Case Diagram 6. SYSTEM REQUIREMENTS The elements that build the proposed Lightweight searchable public key encryption schema constitutes of - Sensors, gateways and servers that form the base for the Cloud wireless sensor networks. These components are run using 5 SPCHS based on which the proposed algorithm LSPE is being developed. SPCHS defines various different algorithms, which are algorithms Setup,Structure,Encryption, ,Trapdoor,Search. They are : ALGORITHM SETUP- The most important and basic of the 5 algorithms is the Algorithm setup. It generates some kind of system parameters for the remaining algorithms based on the requirements of the security degree. These parameters are majorly made up of 2 parts one master public key and the other one is master private key. In case of CWSNs, the authority of the sensors implements the Algorithm. All the sensors are then used to accumulate the master public key, whereas the master private key is securely preserved by owner of the sensors. ALGORITHM STRUCTURE- Algorithm structure holds responsibility for initializing a secured hidden structure which is later used for the encryption of the algorithm. A hidden structure that has been initialized constituted of two parts- a private and a public part. In case of CWSNs, the sensor implements this algorithms before the 1st time for running the algorithm encryption. The sensor uploads the public part produced into the cloud while securely storing the private part. ALGORITHM ENCRYPTION- The action of generating searchable cipher text of a particular keyword is performed by algorithm Encryption. This cipher text that has been generated holds a hidden relationship with cipher texts that had been previously produced. In case of CWSNs, a sensor implements the algorithm incase it wishes to cipher texts that are searchable through keywords for some gained data. The sensor then uploads the ciphertext produced to the cloud
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 2867 and in the end updating the private parts of the hidden structure for the upcoming cipher texts. ALGORITHM TRAPDOOR- The generation of keyword search trapdoor for a particular keyword is done by Trapdoor algorithm and it is necessary that the master private key is taken as an input into it. In case of CWSNs, a sensor's owner runs this algorithm incase he/she desires to retrieve the particular keywords data present in the sensor and later this trapdoor is sent into the cloud as an authorized keyword search task. As the master private key is only known to the owner, except the owner no one could perform keyword search in cloud. ALGORITHM SEARCH- For finding every same cipher text to a particular keyword we use Algorithm search. In case of CWSNs, the clouds performs this algorithm to determine all similar cipher text from the owner upon receiving a keyword search trapdoor. 7. CONCLUSION An able and easy-to-demonstrate and implement SSE scheme is provided in his paper, it has one round of communication, O(n) times of computations over n documents. Use of hash chaining instead of chain of encryption makes is suitable for lightweight applications. Relative positions and frequency of the word searched cannot be detected, unlike the previous SSE schemes for string search. Probabilistic trapdoors have been proposed in Searchable Symmetric Key Encryption for String search.Proof of non- adaptive security of our schema against honest-but- curious server is also provided. A new term of search pattern privacy is also introduced, which gives a measure of security against the leakage from trapdoor. It has been proved that the scheme is more secure under search pattern indistinguishably definition. Modifications have been introduced in the scheme so that the, scheme can be made useful against non-passive adversaries at cost of more rounds of communication and memory space. We have validated the scheme against two unique commercial data sets. REFERENCES [1] Generating SPE Ciphertext with Hidden Structures for Fast Keyword Search published by Qiahong Wu,Wei Wang,Willy Susilo,Peng Xu,Joseph Domingo Ferrer, Hai Jin and Ferrer. [2] LSPE for CWSN’s published by Shuanghong He,Willy Susil, Hai Jin and Peng Xu. [3] Data exfiltration from Internet of Things devices: IOS devices as case studies [4] Everything you need to know about the Industrial Internet of Things [5] Grand View Research, Industrial IoT Market Size Worth $932.62 Billion By 2025 [6] Evolution of WSN’s towards the IOT: A survey. [7] A domain-based multi cluster SIP solution for mobile Ad Hoc network [8] A secure cross-domain SIP solution for mobile Ad Hoc network using dynamic clustering [9] Wireless sensors networks for Internet of Things, pp. 1-6, 2014. [10] A survey on the privacy preserving data aggregation in wireless sensor networks pp. 162-180, 2015 [11] Deterministic and Efficiently Searchable Encryption