IJSRED-V2I2P12

International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 1, Mar-Apr 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 78
High Capacity and Optimized Image Steganography
Technique based on Ant Colony Optimization Algorithm
A. Priya
Alagappa University, Tamilnadu, India.
Abstract
The tremendous development of digital technology, it is mandatory to address the security
while transmitting information over network in a way that observer couldn’t depict it.
Measures to be taken to provide the security by establishing hidden communication using
steganography principle which is help to camouflage the secret information in some carrier
file such as text, image, audio and video. In this era of hidden data communication, image
becoming an effective tool on account of their frequency, capability and accuracy. Image
steganography uses an image as a carrier medium to hide the secret data. The main motive of
this article is that the uses the combination of frequency domain and optimization method
inorder to increasing in robustness. In this article, Integer Wavelet transform is performed into
the host image and coefficients have been transformed. ACO optimization algorithm is used
to find the optimal coefficients where to hide the data. Furthermore, sample images and
information having been demonstrated which proved the increased robustness as well as high
level of data embeddingcapacity.
Keywords: Security, Image, steganography, IWT, ACO (Ant Colony Optimization)
algorithm.
1. Introduction
Cryptographic techniques afford the confidentiality and security by reducing the
prospect of adversaries [1]. There are two processes in cryptography such as: a) Encryption
and b) Key management process. Each security system must supply some security process
that guarantees the secrecy of the system [2]. Cryptography is grouped into Symmetric Key
and Asymmetric Key Cryptography [3]. In Symmetric key cryptography, a single key is used
for both encryption and decryption [4]. The Asymmetric Key Cryptography uses different
keys for both processes [5]. In session key; the symmetric key can be changed every time in
communication between two parties. It is randomly generated and valid for only one session
[6-8]. If an attacker gets the session key, he/she can decrypt only the messages for a particular
session.Ifbothpartiesalwaysusedthesamekeyforallsessions,theattackerwouldbeable
to decrypt all messages encrypted with this key [9-12]. The underlying mathematical problem
of a public-key cryptosystem determines the efficiency of the cryptosystem in a way. Because
these problems dictate the sizes of domain parameters and keys, which in turn affect the
performance of the arithmetic operations of the public-key crypto algorithms [13-15].
Steganography is the art and science of secret communication between two
parties over a public medium that is not detectable by an observer. Steganography is a close
cousin of cryptography which is the art and science of secret communication.
Cryptography aims to conceal the content of the message whereas steganography hides
the very existence of secretive communication as well [17]. For example, figure 1 shows that
two users want to sharing information between them. But noticer is examining that
RESEARCH ARTICLE OPEN ACCESS

communication via Internet Service Provider or local server. To protect this communication,
steganography provide a model in which sender A wish to send message M to receiver B.
Sender embed M over the cover media C and obtained stego object S then sent it over the
insecure channel. The terms cover object is defined as various types of multimedia objects are
used to hide the data and stego object is known as which object embedded the secret
information[18].
Effective characteristics of steganography [20];
1. Secrecy : With the allowing of intend users, extracting the hidden
information[34-37]
2. Imperceptions: The ability to be completely undetectable [38-40]
3. Capacity: Maximum length of the hidden information which can be
embedded in cover object.
4. Accuracy: Extracting of the embedded data should beaccurate.
Steganography techniques are classified into two types which are spatial domain and
frequency domain techniques. In spatial domain, processing is data hidden directly on the
pixel values of the image and in frequency domain, image is transformed then data is hidden
on the transformed coefficients [21]. Some of the spatial domain techniques are LSB, PVD,
EBE, RPE, PMM and Pixel intensity based etc. and some of the frequency domain techniques
are DCT, DWT, DFT, IWT and DCVT [22]. Specifically, spatial domain techniques are
susceptible to visual attack and pixel alteration [23]. When comparing to spatial domain,
transform domain techniques are more robustness because of its hiding scheme in significant
areas of cover images [24-28]. Integer wavelet transform (IWT) maps an integer data set into
another integer data set . In discrete wavelet transform, the used wavelet filters have floating
point coefficients so that when we hide data in their coefficients any truncations of the
floating point values of the pixels that should be integers may cause the loss of the hidden
information which may lead to the failure of the data hiding system[29].
The remaining of the paper is constructed as below: Relevant works have discussed in
section 2. In section 3, explain the workflow of proposed method include algorithms. In

Section 4, prove the proposed method has increasing in robust and level of capacity by carried
out the experiment on sample image and secret data. Finally, Section 5 concludes the article.
2. Related Work
Discrete Wavelet Transforms are used in JPEG2000 image format and several
methods embed information using Integer Wavelet Transform Coefficients. Lai and
Chang proposed an adaptive data hiding method in the frequency domain [30]. Seyyedi
et al. in [22] proposed a high volume payload and secure steganography technique
based on integer wavelet transform. Ghasemi et al. combined Genetic Algorithm (GA),
OPAP and Integer Wavelet Transforms to reduce distortion while delivering high
embedding capacity in[23].
N. Vinothkumar et al [24] have been suggested to embed the data over image on the
basis of the combination IWT with Optimal pixel Adjustment Process (OPAP). The method
use IWT to transform the coefficients on cover image and OPAP is used to raise the level of
hiding capacity. Result shows that minimize difference error betwixt original and encoded
image.
Ching-Sheng Hsu et al [25] have been proposed method to determined the optimal
LSB substitution using ACO algorithm . This method embeds the data into the last bits of the
cover image. Moreover, generate optimal matrix with the help of ACO algorithm to conceal
the data at the optimal values.
Rafael Lima de Carvalho et al [26] have been used optimization principle to hide the
secret message into the target picture. Optimization done by PSO algorithm and produce
better result than classical GA basedmethod.
Amanjot Kaur et al [27] have been proposed algorithm which finding an optimal
block on image may be the best position to hide the data. The fitness function to be taken
where ratio is maximize of sum of contrast and energy and entropy and homogeneity. Results
prove that this algorithm showing superiority than PSOalgorithm.
3. ProposedMethod
3.1 Overview
The proposed method is splitted into two subsequent parts such as using IWT for
transforming coefficients and ACO to find the best values for embedding. In the first part of
proposed method, input the color image as carrier and extracting three RGB color
components [31]. Integer wavelet transform is applied on these components and results
showing transformed coefficients. Second part concerned the Ant Colony Optimization
algorithm which inspired the behavior of ants. These ants deposited pheromone on the path to
discover shortest best path from nest to food. More pheromone on path increases, that path
followed by every other ants of the colony. Ant Colony Optimization Algorithm work on the
basis of the similar mechanism and used in proposed method. The secret raw data has been
converted into ASCII values and these can be embedding at the optimal coefficients by
applying ACO algorithm. After all secret values were embedded; inverse IWT is processed to
gain the stego object and ready to send it to receiver. At the recipient side, received it and
extract the secret data from it by performing the reverse procedure of embedding method.
With the neat sketch, the entire work of proposed method is described in the following
figure.
3.2 Algorithm
Proposed embedding algorithm is enumerated below to hide the data over the cover image.

2
Extract RGB
bands
8
6
Steganography
7
4
ACO Algorithm
Embed at the
optimal points
Find the optimal
coefficient
Embedded Image
Convert into
ASCII Code
3
Transform
Coefficients
Apply IWT technique
1. Given input as color image and secretdata
2. Extract RGB components from colorimage
3. IWT technique is applied on the bands and makes transformation among the
coefficients.
4. ACO algorithm is used to find the optimalpoints.
5. Data is converting into ASCII values. On each row at every location given by the
ACO, embed values at those optimalpoints.
6. Finally, stego image is obtained by process the inverse IWTmethod.
Whereas the proposed extracting algorithm is explained below;
1. Receive the stegoimage
2. Data is extracting from the stego image by performing the reverse operation of
embeddingmethod.
3. Obtained the secretdata.
3.3 Block Diagram
1
5
3.4 Ant Colony OptimizationAlgorithm
In computer science and engineering, algorithm is very important [41-105]. The ant colony
optimization algorithm (ACO) is a probabilistic technique for solving computational problems
which can be reduced to finding good paths through graphs [33]. The ACO algorithm is one
of the most competent methods that indicate the main aspects of state transition rules and
pheromone modernize devices [103-105]. In each iteration, colonies of ants are sent to a
particular place for solution. Each ant works steadily in their state transition rules [106-130].
Read the secret
data
Read the Color
Image

ij
ij
Suppose, if an ant completes a work, then the pheromone modernized begins to search
another ant with similar strength. But it significantly reduces the opportunities and changes
the search methodology.
Step 1:
Initialize the solution Hi
Step 2:
Find the fitness value (Fi )
Fi =PSNR +CC
Step 3:
Based on the fitness find Probability transition matrix
P
c
= )α
(η)β
ij
∑(τ )α
(η)β
Step 4: Update pheromone and Evaporation pheromone
S
τij =(1−ρ)∗τij +∑∆τijC
=1
Step 6: Find the fitness for
if(Hnew)>
Hnew from pheromone evaporation
f (Hi )
Step 7:
Store the best solution so far attained
Iteration=Iteration+1
Step8:
Where,
Stop until optimal key attained
ij
(τij
C

= pheromone evaporation rate
S = number of ants
ij
c
= is the quantity of pheromone laid on edge (i,j) by c-th ant
ij
c
= Q/Lc; if ant c used connection (i, j) in itstour
0 ; otherwise
4. Results andDiscussion
Our proposed approach has been validated by experimenting with variations of the images. The proposed
system has been implemented in Visual Studio 2010, with .NET Framework Version 4.0 using the
language of C# windows application. The experiment has been conducted several test images by taking
RGB cover images of dimension 512x512. Table 1 shows the original images, secret data and stego
images. From the above defined experimental results, we can observe that after secret data embedded,
there is no visual difference from the original image. Hence, the existence of the embedded message will
not be known to the unauthorized users.
Various performance metrics were also verified from the resultant image such as the Peak- Signal –
Noise – Ratio, between the original image and this can further be proved from the Peak-Signal-to-Noise-
Ratio (PSNR) between final images and originalimages.
TABLE I
EXPERIMENTAL RESULTS OF THE PROPOSED TECHNIQUE
Original Image Sample Secret Data Stego Image

5. PerformanceEvaluation
For comparing stego image with cover results requires a measure of image quality,
commonly used measures Peak Signal-to-Noise Ratio [12]. If SNR and PSNR represent
smaller value, then it indicates there is a large between the original (without noise) and
distorted image. The main advantage of this measure is ease of computation, but it does not
reflect perceptual quality. An important property of PSNR is that a slight spatial shift of an
image can cause a large numerical distortion but, there would be no visual distortion and
conversely, a small average distortion can result in a damaging visual artifact, if all the error
is concentrated in a small important region. The performance values the PSNR calculated
from the output image is compared with the PSNR values provided in the existing techniques,
in the following tables2.
TABLE II
COMPARISON BETWEEN EXISTING AND PROPOSED TECHNIQUE BASED ON PSNR
Cover
Image
Size Proposed Algorithm
Sailboat 256x256 65.6274
Goldhill 300x256 66.0808
Peppers 400x400 69.4901
Lena 512x512 71.6319
6. Conclusion
The proposed method is used to increase high capacity and optimized image steganography
technique based on ant colony optimization algorithm. The ACO algorithm can find good
solutions efficiently even though the search space is so large. Our experimental results show
the proposed method provides acceptable image quality and secret message capacity. In
future, some data encryption technique can be applied along with ABC to increase the
security level. It may also be possible to optimize the fitness function of the current ABC
algorithm. Algorithms like AFS and BFO can also be tried to view their performance with
respect to the proposedmethod.
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Shankar, K., Abadi, S. Muslihudin, M., The Application of Decision Support System
by using Fuzzy SAW Method in Determining the Feasibility of Electrical Installations
in Customer’s House, International Journal of Pure and Applied Mathematics, Vol.
119, No. 16, 2018, pp. 4277-4286.

[66] Lydia, E. L., Kumar, P.K., Shankar, K., Lakshmanaprabu, S.K., Vidhyavathi, R.M.,
Maseleno, A., Charismatic Document Clustering through Novel K-Means Non-
negative Matrix Factorization (KNMF) Algorithm using Key Phrase Extraction,
International Journal of Parallel Programming, Springer, 2018, pp. 1-19.
[67] Susilowati, T., Dacholfany, M.I., Amini, S., Ikhwan, A., Nasir, B.M., Huda, M.,
Prasetyo, A., Maseleno, A., Satria, F., Hartati, S., Getting Parents Involved in Child’s
School: Using Attendance Application System Based on SMS Gateway, International
Journal of Engineering and Technology (UAE), Vol. 7, No. 2.27, 2018, pp. 167-174.
[68] Abadi, S., Huda, M., Hehsan, A., Ripin, M.N., Haron, Z., Muhamad, NHN, Rianto,
R., Maseleno, A., Renaldo, R., Syarifudin, A., Design of student score application for
assessing the most outstanding student at vocational high school. International Journal
of Engineering and Technology, Vol. 7, No. 2.27, 2018, pp. 172-177.
[69] Aminudin, N., Sundari, E., Shankar, K., Deepalakshmi, P., Fauzi, Irviani, R.,
Maseleno, A., Weighted Product and Its Application to Measure Employee
Performance, International Journal of Engineering and Technology(UAE), Vol. 7,
No. 2.26, 2018, pp. 102-108.
[70] Abadi, S. Huda, M., Basiron, B, Ihwani, S.S., Jasmi, K.A., Hehsan, A., Safar, J.,
Mohamed, A.K., Embong, W.H.W., Mohamad, A.M., Noor, S.S.M., Novita, D.,
Maseleno, A., Irviani, R., Idris, M., Muslihudin, M., Implementation of Fuzzy
Analytical Hierarchy Process on Notebook Selection, International Journal of
Engineering and Technology(UAE), Vol. 7, No. 2.26, 2018, pp. 102-108.
[71] Anggraeni, E.Y., Huda, M., Maseleno, A., Safar, J., Jasmi, K.A., Mohamed, A.K.,
Hehsan, A., Basiron, B., Ihwani, S.S., Embong, W.H.W., Mohamad, A.M., Noor,
S.S.M., Fauzi, A.N., Wijaya, D.A., Poverty Level Grouping using SAW Method,
International Journal of Engineering and Technology(UAE), Vol. 7, No. 2.27, 2018,
pp. 218-224.
[72] Abadi, S., Huda, M., Jasmi, K.A., Noor, S.S.M., Safar, J., Mohamed, A.K., Embong,
W.H.W., Mohamad, A.M., Hehsan, A., Basiron, B., Ihwani, S.S., Maseleno, A.,
Muslihudin, M., Satria, F., Irawan, D., Hartati, S., Determination of the Best Quail
Eggs using Simple Additive Weighting, International Journal of Engineering and
Technology(UAE), Vol. 7, No. 2.27, 2018, pp. 225-230.
[73] Abadi, S., Huda, M., Hehsan, A., Mohamad, A.M., Basiron, B., Ihwani, S.S., Jasmi,
K.A., Safar, J., Mohamed, A.K., Embong, W.H.W., Noor, S.S.M., Brahmono, B.,
Maseleno, A., Fauzi, A.N., Aminudin, N., Gumanti, M., Design of Online
Transaction Model on Traditional Industry in order to Increase Turnover and
Benefits, International Journal of Engineering and Technology(UAE), Vol. 7, No.
2.27, 2018,pp. 231-237.
[74] Susilowati, T., Teh, K.S.M., Nasir, B.M., Don, A.G., Huda, M., Hensafitri, T.,
Maseleno, A., Oktafianto, Irawan, D., Learning Application of Lampung Language
based on Multimedia Sofware, International Journal of Engineering and
[75] Abadi, S., Nasir, B.M., Huda, M., Ivanova, N.L., Sari, T.I., Maseleno, A., Satria, F.,
Muslihudin, M., Application model of k-means clustering: Insights into promotion
strategy of vocational high school, International Journal of Engineering and
[76] Septiropa, Z., Osman, M.H., Rahman, A.B.A., Arifin, M.A.M., Huda, M., Maseleno,
A., Profile of cold-formed steel for compression member design a basic
combination,International Journal of Engineering and Technology(UAE), Vol. 7, No.
2.27, 2018, pp. 284-290.
[77] Ristiani, Pardimin, Teh, K.S.M., Fauzi, A., Hananto, A.L., Huda, M., Muslihudin, M.,
Shankar, K., Maseleno, A., Decision Support System Model for Selection of Best

Formula Milk for toddlers using Fuzzy Multiple Attribute Decision Making, Journal
of Advanced Research in Dynamical and Control Systems, Vol. 10, 02-Special Issue,
2018.
[78] Hamid, A., Sudrajat, A., Kawangit, R.M., Don, A.G., Huda, M., Jalal, B., Akbar, W.,
Onn, A., Maseleno, A., Determining basic food quality using SAW, International
Journal of Engineering and Technology(UAE), Vol. 7, No. 4, pp. 3548-3555, 2018.
[79] Oktafianto, Kawangit, A.S., Kawangit, R.M., Don, A.G., Huda, M., Saputri, A.D.,
Latif, A.A., Maseleno, A., Determining housing location using weighted product,
International Journal of Engineering and Technology(UAE), Vol. 7, No. 4, pp. 3563-
3568, 2018.
[80] Fauzi, Huda, M., Teh, K.S.M., Haron, Z., Ripin, M.N., Hehsan, A., Abas, H., Rafiq,
M., Irawan, J., Abadi, S., Maseleno, A., The Design of Fuzzy Expert System
Implementation for Analyzing Transmissible Disease of Human, International Journal
of Pharmaceutical Research, Vol. 10, Issue 4, 2018.
[81] Abadi, S., Huda, M., Teh, K.S.M., Haron, Z., Ripin, M.N., Hehsan, A., Sarip, S.,
Hehsan, M.R., Amrullah, M., Maseleno, A., Hazard Level of Vehicle Smoke by Fuzzy
Multiple Attribute Decision Making with Simple Additive Weighting Method,
International Journal of Pharmaceutical Research, Vol. 10, Issue 4, 2018.
[82] Kamenez, N.V., Vaganova, O.I., Smirnova, Z.V., Bulayeva, M.N., Kuznetsova, E.A.,
Maseleno, A., Experience of the use of electronic training in the educational process
of the Russian higher educational institution, International Journal of Engineering and
Technology(UAE), Vol. 7, No. 4, pp. 4085-4089, 2018.
[83] Vaganova, O.I., Zanfir, L.N., Smirnova, Z.V., Chelnokova, E.A., Kaznacheeva, S.N.,
Maseleno, A., On the linguistic training of future teachers of unlike specialties under
the conditions of Russian professional education, International Journal of Engineering
and Technology(UAE), Vol. 7, No. 4, pp. 4090-4095, 2018.
[84] Vaganova, O.I., Kamenez, N.V., Sergeevna, V.I., Vovk, E.V., Smirnova, Z.V.,
Maseleno, A., Possibilities of information technologies to increase quality of
educational services in Russia, International Journal of Engineering and
Technology(UAE), Vol. 7, No. 4, pp. 4096-4102, 2018.
[85] Smirnova, Z.V., Zanfir, L.N., Vaganova, O.I., Bystrova, N.V., Frolova, N.V.,
Maseleno, A., WorldSkills as means of improving quality of pedagogical staff
training, International Journal of Engineering and Technology(UAE), Vol. 7, No. 4,
pp. 4103-4108, 2018.
[86] Aminin, S., Dacholfany, M.I., Mujib, A., Huda, M., Nasir, B.M., Maseleno, A.,
Sundari, E., Masrur, M., Design of library application system,International Journal of
[87] Aminudin, N., Huda, M., Kilani, A., Embong, W.H.W., Mohamed, A.M., Basiron, B.,
Ihwani, S.S., Noor, S.S.M., Jasmi, K.A., Higher education selection using simple
additive weighting,International Journal of Engineering and Technology(UAE), Vol.
7, No. 2.27, 2018, pp. 211-217.
[88] Aminudin, N., Huda, M., Hehsan, A., Ripin, M.N., Haron, Z., Junaidi, J., Irviani, R.,
Muslihudin, M., Hidaya, S., Maseleno, A., Gumanti, M., Fauzi, A.N., Application
program learning based on Android for students experiences, International Journal of
[89] Maseleno, A., Huda, M., Jasmi, K.A., Basiron, B., Mustari, I., Don, A.G., and Ahmad,
R. Hau-Kashyap approach for student’s level of expertise. Egyptian Informatics
Journal, 2018.
[90] Huda, M., Maseleno, A., Teh, K.S.M., Don, A.G., Basiron, B., Jasmi, K.A., Mustari,
M.I., Nasir, B.M., Ahmad, R., Understanding Modern Learning Environment (MLE)
in Big Data Era, International Journal of Emerging Technologies in Learning

(iJET),Vol. 13, No. 5, 2018, pp. 71-85.
[91] Maseleno, A., Tang, A.Y.C., Mahmoud, M.A., Othman, M., Shankar, K., Big Data
and E-Learning in Education, International Journal of Computer Science and Network
Security, Vol. 18, No. 5, pp. 171-174.
[92] Shankar, K., Lakshmanaprabu, S.K., Gupta, D., Maseleno, A., De Albuquerque,
V.H.C., Optimal feature-basedmulti-kernel SVM approach for thyroid disease
classification, The Journal of Supercomputing, Springer, Vol. 74, no. 259, 2018, pp. 1-
16.
[93] Amin, M.M., Sutrisman, A., Stiawan, D., Maseleno, A., Design Restful WebService
of National Population Database for supporting E-health interoperability service,
Journal of Theoretical and Applied Information Technology, vol. 96, issue 15, 2018.
[94] Surendar, A., Akhmetov, L.G., Ilyashenko, L.K., Maseleno, A., Samavatian, V.,
Effect of thermal cycle loadings on mechanical properties and thermal conductivity of
a porous lead-free solder joint, IEEE Transactions on Components, Packaging, and
Manufacturing Technology, 2018, pp. 1769-1776.
[95] Surendar, A., Samavatian, V., Maseleno, A., Ibatova, A.Z., Samavatian, M., Effect of
solder layer thickness of thermo-mechanical reliability of a power electronic system,
Journal of Material Science: Materials in Electronics, Springer, September 2018,
Volume 29, Issue 17, pp. 15249-15258.
[96] Samavatian, M., Ilyashenko, L.K., Surendar, A., Maseleno, A., Samavatian, V., Effect
of System Design on Fatigue Life of Solder Joints in BGA Packages Under Vibration
at Random Frequencies, Journal of Electronic Materials, November 2018, Volume 47,
Issue 11, pp. 6781-6790.
[97] Javanshir, I., Maseleno, A., Tasoujian, S., Oveisi, M., Optimization of suspension
system of heavy off-road vehicle for stability enhancement using integrated anti-roll
bar and coiling spring mechanism, Journal of Central South University, September
2018, Volume 25, Issue 9, pp 2289–2298.
[98] Surendar, A., Bozorgian, A., Maseleno, A., Ilyashenko, L.K., Najafi, M., Oxidation of
Toxic Gases via Ge-B36N36 and Ge-C72 Nanocages as Potential Calaysts, Inorganic
Chemistry Communications, Elsevier, Vol. 96, October 2018, pp. 206-210.
[99] Namdarian, A., Tabrizi, A.G., Maseleno, A., Mohammadi, A., Mossavifard, S.E., One
step synthesis of rGO-Ni3S2 nano-cubes composite for high-performance
supercapacitor electrodes, International Journal of Hydrogen Energy, Elsevier, vol. 43,
Issue 37, 13 September 2018, pp.17780-17787.
[100] Motlagh, A.H., Klyuev, S.V., Surendar, A., Ibatova, A.Z., Maseleno, A., Catalytic
Gasification of Oil Sludge with Calcined Dolomite, Petroleum Science and
Technology, Taylor and Francis, pp. 1-5, 2018.
[101] Elhoseny, M., Elleithy, K., Elminir, H., Yuan, X., & Riad, A. (2015). Dynamic
clustering of heterogeneous wireless sensor networks using a genetic algorithm
towards balancing energy exhaustion. International Journal of Scientific &
Engineering Research, 6(8),1243-1252.
[102] Elhoseny, M., Yuan, X., Yu, Z., Mao, C., El-Minir, H. K., & Riad, A. M. (2015).
Balancing energy consumption in heterogeneous wireless sensor networks using
genetic algorithm. IEEE Communications Letters, 19(12),2194-2197.
[103] Fang, B., Guo, X., Wang, Z., Li, Y., Elhoseny, M., & Yuan, X. (2019). Collaborative
task assignment of interconnected, affective robots towards autonomous healthcare
assistant. Future Generation Computer Systems, 92,241-251.
[104] Sivaram, M., B. DurgaDevi, and J. Anne Steffi. "Steganography of two LSB bits." International
Journal of Communications and Engineering 1.1 (2012): 2231-2307.
[105] Manikandan, v., v. Porkodi, amin salih mohammed, and m. Sivaram. "Privacy Preserving Data

Mining Using Threshold Based Fuzzy Cmeans Clustering." ICTACT Journal on Soft
Computing 9, no. 1 (2018).
[106] Malathi, N., and M.Sivaram. "An Enhanced Scheme to Pinpoint Malicious Behavior of Nodes In
Manet’s." (2015).
[107] Mohammed, Amin Salih, D. Yuvaraj, M. Sivaram, and V. Porkodi. "Detection And Removal Of
Black Hole Attack In Mobile Ad Hoc Networks Using Grp Protocol." International Journal of
Advanced Research in Computer Science 10, no. 6 (2018).
[108] Sivaram, M., D. Yuvaraj, Amin Salih Mohammed, V. Porkodi, and V. Manikandan. "The Real
Problem Through a Selection Making an Algorithm that Minimizes the Computational
Complexity."
[109] Porkodi, V., M. Sivaram, Amin Salih Mohammed, and V. Manikandan. "Survey on White-Box
Attacks and Solutions." Asian Journal of Computer Science and Technology 7, no. 3 (2018): 28-
32.
[110] Sivaram, M. "Odd And Even Point Crossover Based Tabu Ga For Data Fusion In Information
Retrieval." (2014).
[111] Dhivakar, B., S. V. Saravanan, M. Sivaram, and R. Abirama Krishnan. "Statistical Score
Calculation of Information Retrieval Systems using Data Fusion Technique." Computer Science
and Engineering 2, no. 5 (2012): 43-45.
[112] Punidha, R., avithra K, Swathika R, and Sivaram M, “ Preserving DDoS Attacks sing Node
Blocking Algorithm.” International Journalof Pure and Applied Mathematics, Vol.119, o. 15,
2018, pp 633-640. https://acadpubl.eu/hub/2018-119-15/3/473.pdf
[113] M, Sivaram, et al. “Securing the Sensor Networks Along With Secured Routing Protocols for
Data Transfer in Wireless Sensor Networks.” Journal of Emerging Technologies and Innovative
Research, vol. 5, no. 10, Oct. 2018, pp. 316–321., doi:http://doi.one/10.1729/Journal.18612.
[114] Steffin Abraham , Tana Luciya Joji , Sivaram M, D.Yuvaraj, “Enhancing Vehicle Safety With
Drowsiness Detection Andcollision Avoidance” International Journal of Pure and Applied
Mathematics, Volume 118 No. 22 2018, 921-927. https://acadpubl.eu/hub/2018-118-
22/articles/22b/39.pdf
[115] Mahalakshmi.K, Sivaram.M, Shantha Kumari.K, Yuvaraj.D, Keerthika.R, “Healthcare Visible
Light Communication”, International Journal of Pure and Applied Mathematics, Volume 118 No.
11 2018, 345-348, https://acadpubl.eu/jsi/2018-118-10-11/articles/11/41.pdf.
[116] Punidha.R, Sivaram.M, “Integer Wavelet Transform Based Approach For High Robustness Of
Audio Signal Transmission”, International Journal of Pure and Applied Mathematics, Volume 116
No. 23 2017, 295-304, https://acadpubl.eu/jsi/2017-116-23-24/articles/23/40.pdf
[117] Deepa.S, Sivaram.M, “Enabling Anonymous Endorsement In Clouds With Decentralized Access
Control”, International Journal of Scientific Engineering and Applied Science (IJSEAS) -
Volume-1, Issue-3, June 2015, 397-401.
[118] Sivaram.M, Obulatha.O, “ Position Privacy Using LocX”, International Journal of Innovative
Research in Engineering Science and Technology, Vol. III,Issue 01,Pp 206-212.
[119] M. Sivaram, K. Batri, Amin Salih Mohammed and V. Porkodi, “Exploiting the Local Optima in
Genetic Algorithm using Tabu Search”, Indian Journal of Science and Technology, Vol 12(1),
DOI: 10.17485/ijst/2018/v12i1/139577, January 2019.
[120] Sivaram M, Batri K, “ Odd and Even Point Crossover Based Tabu GA for Data Fusion in
InformationRetrieval”, http://hdl.handle.net/10603/38935,10-Apr-2015.
[121] Sivaram.M, Yuvaraj.D, Amin Salih Mohammed, Porkodi.V “Estimating the Secret Message in the
Digital Image” International Journal of Computer Applications, 181(36):26-28, January 2019.
[122] Mrs.V.Porkodi, Dr.D.Yuvaraj, Dr.Amin Salih Mohammed,V.Manikandan and M.Sivaram, “Prolong
the Network Lifespan of Wireless Sensor Network by Using Hpsm”, International Journal of
Mechanical Engineering and Technology, 10(01), 2019, pp.2039–
2045.http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&Type=01
[123] Porkodi.V, Yuvaraj.D., Mohammed,A.S, Sivaram.M and Manikandan.V,”IoT in Agriculture”

Journal of Advanced Research in Dynamical and Control Systems, Pages: 1986-1991,14-Special
Issue, Pages: 1986-1991,2018.
[124] Manikandan.V, Mohammed, A.S, Yuvaraj,D., Sivaram.M and Porkod.V, “An Energy Efficient
EDM-RAEED Protocol for IoT Based Wireless Sensor Networks” Journal of Advanced Research
in Dynamical and Control Systems, Pages: 1992-2004,14-Special Issue,Pages: 1992-2004, 2018.
[125] Mohammed, A.S., Kareem, S.W., Al Azzawi, A.K., Sivaram, M. “Time series prediction using
SRE-NAR and SRE-ADALINE”, Journal of Advanced Research in Dynamical and Control
Systems, Pages:1716-1726, 2018.
[126] Sivaram, M., Yuvaraj, D., Porkodi, V., Manikandan, V. “Emergent news event detection from
facebook using clustering” Journal of Advanced Research in Dynamical and Control Systems,
Pages:1941-1947, 2018.
[127] Nithya, S., Sundara Vadivel, P., Yuvaraj, D., Sivaram, M. “Intelligent based IoT smart city on traffic
control system using raspberry Pi and robust waste management”, Journal of Advanced Research in
Dynamical and Control Systems, Pages: 765-770, 2018.
[128] Viswanathan, M., Sivaram, M., Yuvaraj, D., Mohammed, A.S. “Security and privacy protection in
cloud computing”, Journal of Advanced Research in Dynamical and Control Systems, Pages 1704-
1710, 2018
[129] Batri, K., Sivaram, M. “Testing the impact of odd and even point crossover of genetic algorithm over
the data fusion in information retrieval”, European Journal of Scientific Research, 2012.
[130] Sivaram Yuvaraj Amin Salih Mohamme M D V Porkodi. Estimating the Secret Message in the
Digital Image. International Journal of Computer Applications 181(36):26-28, January 2019

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