Executive Committee and Organization

General Chair: Sameer Bataineh

JUST, JORDAN

Program Chair: Eyas El-Qawasmeh

JUST, JORDAN

Reviewing Chair: Basheer Al-Duwairi

UST, JORDAN

Proceeding Chair: Ahmad Dalalah

JUST, JORDAN

Proceeding Message This is the first International Conference on Digital Communications and Computer Applications hosted by the Faculty of Computer and Information Technology at Jordan University of Science and Technology. DCCA 2007 is a forum for scientists and engineers to meet and present their latest research results, ideas, and papers in the diverse areas of Digital Communications, Computer Science, and Information Technology. This scientific conference will cover guest lectures, more than 300 papers for presentations, technical session, and oral poster sessions with debates. This meeting will be a great opportunity to exchange knowledge and experience for all the participants who joined us from all over the world to discuss new ideas in the area of computer science and information technology. We are grateful for the effort of Dr. Eyas El-Qawasmeh, the program chair for making this conference possible, and a special thanks to the technical committee and to all external reviewers. Finally we would like to thank all the participant, sponsoring companies, and Jordan University of Science and Technology. Also we would like to extend a warm welcome you to Jordan, and do hope that all participants have a wonderful time to Jordan in the season of beautiful blossoms. General Chair Prof. Sameer Bataineh Dean of the Faculty of Computer & Information Technology Jordan University of Science & Technology

Preface Dear DCCA2007 proceedings reader:

On behalf of the DCCA2007 conference, the program committee and Jordan University of Science and Technology has the pleasure to welcome the attendees to Jordan University of Science and Technology, Irbid, Jordan to participate in the 1st International Conference on Digital Communications and Computer Applications (DCCA2007).

The DCCA2007 conference explores new advances in information technology. It brought together researcher from various areas of computer science and addresses both theoretical and applied aspects of information technology. The fields of computer science and information technology are growing very fast and there are new technologies that are added every day. Jordan does contribute to these advancements and a proof of this contribution is the large number of presented papers in this international conference.

The DCCA2007 conference offers the opportunity for the researchers from all over the world to get together and discuss the new advances in the area of computer science and information technology. The discussion and exchange ideas will contribute to these fields and will help in more advances in the technology in the coming future.

The call for papers resulted in 45% accepted papers and 18 accepted posters from 47 countries covering all areas of information technology. The papers are of top quality papers. Each paper is evaluated by at least two reviewers. The results of reviewing were paper acceptance, poster acceptance, or paper rejection. In addition, four tutorials and two keynote speakers have been accepted in this conference.

Finally, we hope that the conference satisfy your expectations and hope you enjoy time with us and in Jordan University of Science and Technology. The committees worked hard for not just days but months to reach the quality level that do satisfy our guests, and many thanks and appreciation to all of you who are here today.

Dr. Eyas A. El-Qawasmeh Program chair DCCA2007 Computer Science Department Jordan University of Science and Technology

Table of content

AlGORITHMS

A Canonical Genetic Algorithm for Likelihood Estimator of First Order Moving Average Model Parameter Basa’d Ali Hussain , Rawa’a Dawoud Al-Dabbagh

1

A Water-Saving Technique Based on Distributing of Prime Numbers over Integers Ahmad Sharieh , Adel H. Abusitta , Aladdin H. Baarah

11

A New Approach to Data-Driven Modeling in Civil Engineering Akbar A. Javadi , Mohammad Rezania , Mohaddeseh Mousavi Nezhad

17

VDM Specification of an Algorthm for Graph Decomposition Abdul Huq, Naryanan of an Algoritm for Grapj Decomposition

25

Concept Lattice Reduction by Matrix Decompositions Vaclav Snasel, Petr Gajdos, Hussam M. Dahwa Abdulla, Martin Polovincak

35

Automated Generating Test Cases Using Genetic Algorithms Arabi Keshk, Ahmed M. Omira , Nabil A. Ismail

43

An Algorithm for Generating the Design Matrix for Multivariate Polynomial Least Squares Fitting Sami F. Al-Hamdan

50

COMPUTER ALGORITHMS

Text search algorithm based on stacks Abdurazzag Ali Aburas

55

Weighted maximum likelihood algorithm for time and frequency synchronization of DVB-T systems Charbel El Hajjar , Martin Speitel

60

Three Term Backpropagation Algorithm For Classification Problem Siti Mariyam Shamsuddin , Maslina Darus , Fadhlina Izzah Saman

70

A Genetic Algorithm for Distributed Query Processing over Mirror Servers Azzam Talal Sleit ,Wesam Al-Mbaideen , Nawal Alzabin, Hadeel Dawood , Khaled alqarute

81

ClassifyChi2: An Efficient Discretization Algorithm Ahmad M. Odat , Saleh M. Abu-Soud

88

Two-PASS HORIZON LINE ALGORITHM FOR FAST SHADOW GENERATION OF 3D FUNCTION Tian SHEN, You-xing GAO

99

Using theModulus Adaptive Arrays -Reduced Computational Complexity of the Constrained Multi Householder Transformation Said E. El-Khamy, Fellow IEEE , Darwish M. Abd-Elaziz , Roshdy K. Korayem, IEEE student member

106

Non-uniform Randomized Balanced Allocations Ebrahim Malalla¤

112

COMPUTER DESIGN, ARCHITECTURE , & GRIDS

A Combined hardware-Software Approach for CPU Energy Reduction Using Dynamic Voltage Scaling Technique Diary R. Sulaiman

113

A QoS Matching Approach for Grid Service Selection Yang Liu , HuaCan He

120

A Novel Grid Resource Discovery Model Based on Matchmaking Engine Overlay Yang Liu , HuaCan He

126

objective Mapping for NoC Architectures -MultiAbou El Hassan BENYAMINA , Pierre BOULET

132

Design of an ECC Decoder based on Orthogonal Parity-Checksums Dr. Pervez Akhtar , Engr. M. Altaf Mukati

140

A Method of Reduction of the Microinstructions of Synchronous Digital Systems Shehabat I. M. , Al-Dahleh M. Z.

147

UP-BY TASK SPLITGRID LOCK AVOIDANCE S . Suresh , Ankit Kamal Mehta , C . G . Gayathri

154

Promotion of Local to Global Operation in Train Control System Sher Afzal Khan , Nazir A. Zafar

162

COMPUTER SECURITY

Design and Implementation of 64-bits Advanced Encryption Standard Malik Qasaimeh , Saleem Masaedeh

168

A New Steganographic Technique for Hiding Grayscale Images in Colored-Raw Images Samer Atawneh

175

A New Steganography System Based on a Hybrid Transform Mussawi-Al. Q. Mahmoud , B. A. W. Dr

182

Protection of Cryptographic Implementations using Error Detection Techniques Rodica Tirtea , Mircea Vladutiu

191

Information Security King Saud University Hospitals experience Zahrani-d , Dr Saleh AlImam Mohammad Bin Sau

197

ime NumbersBox Construction Using Arithmetic Modulo Pr-A Real Time S Eltayeb Salih Abuelyman , Mohammed Ahmed El-Affend

207

The Development of Virtual Reality System for Advanced Training Muhammad Shafie Abd Latiff, Imran Ghani , Setyawan Widyarto

217

Network Security Using Chaos and Nonlinear Dynamics Zahid Ali

222

Improved Intrusion Detection/Prevention System Using Fuzzylogic And Data Mining Bharanidharan Shanmugam and Norbik Bashah Idris

228

A Modified Version of the Advanced Encryption Standard Algorithm with Extra Key Size and Block Size Abdurrahman Abdullah Mohammad , Lo’ai Tawalbeh

236

Enhanced Scheme for Group Key Agreement Birahadish, Saravanan. Suresh,P. Poornaselvan , S. J. K

242

Data Base Systems & Applications Data Warehouses & data mining

SIG for the Follow-up and the Management of the Geology Mining Data of the Constantine Region Dr. Mohamed-Khireddine KHOLLADI

254

On Controlling and Prediction of Next Best Sellings through Periodical Mining for {Semi/Non}-interesting Association Rules Asem Omari and Stefan Conrad

271

Data mining based on WaveCluster Yongmin_tang

276

DATA COMMUNICATIONS & NETWORKING

APPLICATION OF NUMERICAL CONTROLLED OSCILLATOR IN DIGITAL RECEIVER USING FPGA Ali Mohammed Hassan

284

Performance Analysis of a Load Distributing Active Anycast RTT-Based Method for Server Selection lail Abd Manan , Jamilin Jais, Mahamod bin Ismail-Habibah binti Hashim , Jamalul

290

quences for FH CDMA systems Hopping seRameshwar Rao. Sudha, FIETE, Dr.L.K

299

thm for mobile networksing algoriAn efficient rout Al Shqeerat, Hassan Mohammed. A. Khalil H

307

New Fast Method for Computing Wavelet Coefficients from 1D up to 3D Walid A. Mahmoud, Hadeel N. Al-Taai, Shereen M. Al-Qasem

313

A novel algorithm for evaluating TCP utilization and modeling TCP reno and tahoe using markovian model in wlan Mohammad mehdi hassani, Reza barangi, ali dorafshan

324

DATA COMMUNICATIONS AND NETWORKING2 zara

Performance Analysis of Multiuser DS-CDMA Linear Receivers under Various Realistic System Specifications Walid. A. Mahmoud, Mansour Abed, Hytham O. Haj Ali, Mahmoud M. Anshas

331

Standard Protocol Using SDR -MA Transmitter for a MultiDigital Design of CD Jamuar, Sabira Khatun. S.Ali, S. Khalid Eltahir Mohamed, Borhanuddin Mohd

340

Speech Synthesis System -To-sed TextConcatenated BaKhalifa. Zakiah Hanim Ahmad, Othman O

347

A Practical Study on Building a Wireless Sensor Network Karaki-Khalil Mustafa Yousef and Jamal Nazzal Al

355

Prosodic knowledge for emotional speech synthesis in Malayalam

Nair,. S, Nimmy Mathew, Achuthsankar S.Gopinath, Sheeba P.Deepa P

362

MT from English to Arabic Handling the Agreement problem in Tengku Mohammed Tenku Sembok, Mohammed Mahmoud Abu Shquier. Prof

370

let Transform The WalidRamahi-Al. Jawher, Nada N-Al. Walid A. Dr. Prof

382

ADAPTIVE TURBO CODED OFDM Sami Ahmed Haider, Khalida Noori

388

DATA COMMUNICATIONS AND NETWORKING nebo

Analytical Model of Grid Location Update Schemes for MANET Khaled Ahmed Abood Omer, D.K. Lobiyal

395

Dominating Set Theory based Semantic Overlay Networks for Efficient and Resilient Content Distribution J. Amutharaj, S. Radhakrishnan

403

New Fast Method for Computing Multiwavelet Coefficients from 1D up to 3D Sallal. Taai, Reema A-Al. Abdulwahab, Hadeel N. Mahmoud, Mutaz S. Walid A

412

A Comparison between Signal Clipping and µ-Law Companding Schemes for the Reduction of Peak-to-Average Power Ratio of OFDM Signals Sulaiman A. Aburakhia, Ehab F. Badran, Darwish A. E. Mohamed

423

Performance modelling of New Congestion Control Mechanism Abdulmonam G. Ali, M.E. Woodward, Mahmud Etbega

432

Middleware Integrated Sensor for Network Energy Utilization: MISNEU protocol Mahmoud Alwan, Ayad Salhieh

438

A LAYERED MIMO OFDM SYSTEM WITH CHANNEL EQUALIZATION Khalida Noori, Sami Ahmed Haider

450

ier, Dovecot, MySQL, Creation of Mail Server Based on Virtual Users and Domains with Postfix, Cour Mailscanner, Spamassassin, Clamav, Postfixadmin and Squirrelmail

Hedaya Alasooly. Dr

455

DATA COMPRESSION

A Modified Compressing Techniques Based On Improved Fast Discrete Fayez Idris, Sameer Bataineh, Ahmed Sawalmeh, Murad Alaqtash

471

A Novel Lossless Data Compression Scheme Based on the Error Correcting Hamming Codes

Bahadili-Hussein Al

478

Bit Level Files Compression Samer Nofal

486

WORD-BASED TEXT COMPRESSION Jan Platoš, Jiří Dvorský

489

E-LEARNING , EDUCATION & ORGANIZATIONS

Recommended Instructional Technology for K-12 Students in Arab Countries Eyas El-Qawasmeh ,Abdallah Tubaishat

496

An Investigation Study Towards Determine Problems, Solutions & Implementation : Learning-E Limitations

i ,Hannan Issa MohsenHawar-Ma'en Al.Dr

501

On Line Course Learning Enhancement Based on Interactive Interface Abdurazzag Ali Aburas and Othman O Khalifa

509

Face and Electronic -to-Face: Productive Qualitative Interviews Choueiri. Rizk ,Elias M. Nouhad J

515

E Learning Vs M Learning in Higher Education D.Balaji, B.Malathi, J.Akbar Ali

532

Modeling and Verification of Community of Practice Using an Actor-based Language Farzad Peyravi, Kaveh Pashaei, Fattaneh Taghiyareh

537

Measurement of E Learning Usability through User Interface Dr.Mudawi Elmusharaf, Abdelrahman Osman Abdelrahman Elfaki, Ahmed Mohammed Elsawi

545

Modern didactic approaches: the case of distant science education in Greece Kalogiannakis Michailsearch\E-LEARNING , EDUCATION & ORGANIZATIONS\p71.doc

550

An Overview on Electronic Institutions Farnaz Derakhshan

557

Knowledge Management and Intellectual Capital at the University Environment Dr. Issa Shehabat, Dr. Saad A._Mahdi, Dr. Kamel Khoualdi

569

E-TECHNOLOGIES & THE WEB

Legal Web Accessibility Natheer Gharaybih

576

E-commerce: Security Enhancement In Internet Banking Dr. Abeer H. Rasheed Al-Sadoon, Miss. Abeer T. Maolood Al-Obaidy

585

inesss Used Books Bus’Platform for a Faculty-E Muhaini Othman, Salimah Mokhtar

591

Mobile-Commerce vs. Internet-Commerce for New Business Opportunities Ahmad Hayajneh, Hamid Mehrvar

601

A Web Audio System Based on Object Deputy Database Fan Liu, Yuan Cheng, Zhiyong Peng

609

e Arab Countries in AfricaAn Analysis of th: Government Service Delivery Capabilities-E & the Middle East Akemi Takeoka Chatfield, Omar Alhujran

615

Quality in Web Interface Input XML Message Generation and Communication Tor Stålhane

625

Improving Web Search Results for Short Queries Using Preserved Query Knowledge Roberto Solis-Oba and Anwar Alhenshiri

634

E-TECHNOLOGIES & THE WEB2

LUP: Least and Unique Price Auction-A New Type of Online Auctions Dr. Mohammed A. Otair

650

ContentRank: a New Content-based Page Ranking Hui Li, Shu Zhang, Xia Wang, Nian Shao

607

An Used O-O-M to Support Web Site Design Hadeel S. Kareem, Abeer Salim Jamil

614

E-Commerce Contract Modeling and the Contract Law Radomir A. Mihajlovic, Michael J. Gregorek, Ayat Jafari, Darko V. Mihajlovic

621

Evolutionary Improving World Wide Web Queries Václav Snášel, Pavel Krömer, Suhail S. J. Owais, H. O. Nyongesa, S. Maleki-dizaji

630

Web Patterns and Web Page Semantics Milos Kudelka, Vaclav Snasel, Ondrej Lehecka, Eyas El-Qawasmeh

641

Guidelines for Constructing Web Engineering Process Models for Developing Based Applications-Scale Web- Large

Omaima Nazar Ahmad AL-Allaf, Asim El-Sheikh

651

pport ASP Using Two MethodsConfiguration of Apache Server to Su Hedaya Alasooly. Dr

667

IMAGE PROCESSING

elet Image Segmentation Applied on Medical Images using Wav Faraheed-ltanny, Mohammad AlAlsu. Yas A

688

Facial Features Extraction Image Segmentation Using HIS Color Applied on Hameed. Stephan, Sundos A. Jane J. Dr

695

entification and Labelingbrid Transformation Based Automatic Image IdHy Ramahi-Al. Ani, Nada N-Al.Laith A. Jawher, Dr-Al. Walid A. Dr. Prof

704

n and Neural NetworknsformatioImage Identification and Labeling using Hybrid Tra Ramahi-Al. Mikhled Alfaouri, Nada N. Jawherand, Dr-Al. Walid A. Dr. Prof

718

Kobasi,-Mahmoud, Sarwa Al. Walid A. Dr Using Walidlet TransformA Proposed Method of Image ReconstructionSakhrie. Mohammad H. Eng

738

ation of Cervical Smear ImageCytoplast and Nucleus Segment 1Chieh Chen-, and Chun1Hong Lin-, Chi2Kuan Chan-, Yung1Horng Lin-Chuen

742

Descriptor Color Clustering and Spatial Relationthe Fast Image Retrieval Based on Chuen-Horng Lin1, Yung-Kuan Chan2, and Kai-Hung Chen1

748

iDTV Player Compatible MPEG4 and MHP Content Momouh Khadraoui (1), Oliver Tjulin (1), Beat Hirsbrunne (1) and Djamel Khadraoui (2) (1): PAI Group

754

IMAGE PROCESSING 2

GE GENERATION AND COLORIZATIONLUMINANCE PYRAMID FOR IMA Bara'a Ali Attea, Mariam A. Ali

763

A Steganographic Approach Based on Spatial Frequency Layering Sarab Majeed Hameed. Dr

771

A NON Reference Fingerprint Image Validity via Statistical Weight Calculation M.S. ALTARAWNEH, L.C.KHOR, W.L.WOO and S.S DLAY

776

using Moments on shapeIMAGE RETRIEVAL Wesam Atef Hatamleh, Rosalina Abdul Salam

780

Color Difference VQ Compression and Data Hiding Ting Chan-Hsiu** Mao-Fan Yang-, and Shys**Yuan Tsai-Tsang, *Husiun Tsai-, Meng*Kuan Chan-Yung

787

Self Embedding Robust Watermarking in Discrete Wavelet Transform Domain for Digital Colored Images Abdallah Al-Tahan Al-Nu'aimi, Rami Qahwaji

800

Direction Relations in Spatial Queries Using MBC Maytham Safar

807

INFORMATION SYSTEMS

A Light Weight Stemmer for Bengali and Its Use in Spelling Checker Md. Zahurul Islam ,Md. Nizam Uddin, Mumit Khan

SIG for the Survey of the Evolution of the Distribution of the Population of the Adrar Region Dr. Mohamed-Khireddine KHOLLADI

817

Arabic vowels recognition systemType written Majdi Salameh. Nazlia Omar, Mr. Khairuddin Omar, Dr. Dr

826

A study of Arabic SMS-based classified ads SUBlanguageS DAOUD DAOUD , CHRISTIAN BOITET

835

A User Centered Matchmaking and Ranking System . Ahmad Rawashdeh, Rehab Duwairi

845

Text To Speech for Bangla Language using Festiva Firoj Alam ,Promila Kanti Nath , Dr. Mumit Khan

853

Improving Cluster-Based Malay Text Retrieval System Using Thesaurus

Nurazzah Abd Rahman, Zainab Abu Bakar, Normaly Kamal Ismail , Tengku Mohd Tengku Sembok

860

A Knowledge-Base on Holy Qur’an for Tagging Arabic Verbs Mahmoud Shokrollahi-Far , Ayaz Isazadeh , Isa Barzegar, Rezgar Soltani

869

ota and Schedule Backup Configuration of a Simple Samba File Server, Qu Dr. Hedaya Alasooly

876

A Light Weight Stemmer for Bengali and Its Use in Spelling Checker Md. Zahurul Islam , Md. Nizam Uddin , Mumit Khan

887

INFORMATION SYSTEMS2

Involving cognitive science views on collections to better design our Content management tools Francis Rousseaux , Alain Bonardi

888

Segmentation free Bangla OCR using HMM: Training and Recognition Md. Abul Hasnat , S. M. Murtoza Habib , Mumit Khan

894

Deploying and Aligning Organizational Strategy Using Intranet Based Knowledge Management System Norlida Buniyamin, Zainuddin Mohamad

902

An Agent Mediated Community of Practice Using MAS-CommonKADS Methodology

Farzad Peyravi , Fattaneh Taghiyareh

912

Developing business functions in today’s digital environment Dr Mohamad AlSakka

921

Optimization in in IR System Using GP and Fuzzy Grow Up Precision Recall Relationship Curve QueryOptimizing the User

Suhail Sami Owais , Pavel Kromer , Vaclav Snasel

939

Performance Analysis of Information Retrieval Systems Based on Genetic Algorithms Ibrahim Zedan , Mohamed Nour , Sanaa Abo-Elhamayed

949

A Light Weight Stemmer for Bengali and Its Use in Spelling Checker Md. Zahurul Islam , Md. Nizam Uddin , Mumit Khan

962

INFORMATION SYSTEMS & APPLICATIONS – NEBO

Selecting an Architectural Style Satisfying A banking Organization Requirements Using Simulation Yousef Hasan Jbara , Hussam Al-shorman

963

Autonomic Computing : A Survey M. Al-Zawi , D. Al-Jumeily , A. Hussain , A. Symons , A. Taleb-Bendiab

973

TOWARDS AUTOMATIC TRANSFORMATION FROM COSA SOFTWARE ARCHITECTURE TO CORBA PLATFORM Adel Alti , Tahar Khammaci and Adel Smeda

980

Bus Information, Scheduling, and Control for Amman (Project BiSCA) Ehab Al-Hakawati , Fayez Al-Rafia , Khalid Al-Tahat , Nasim Al-Tamimi

990

Malay Spelling Exchange Rule: A Computational Technique in Information Retrieval for Identification Similar Words in Historical Malay Text Zainab Abu Bakar , Tengku Mohd. Tengku Sembok , Mohammed Yusoff

1003

Arabic Stemming Based on affixes Removal Mohammad Khaleel Qasem , Sari Awwad

1015

Comparison of Information Retrieval Models for Arabic Text Muath Alzghool and Diana Inkpen , Ghassan Kanaan

1023

A New Paradigm of Pervasive Information Systems Dana Amin Al-Kukhun, Florence Sedes

1033

NEURAL NETWORKS AND ARTIFICIAL INTELLIGENCE

Automatic Estimation of Maximum Frequency and Velocity of Liquid Simulating Blood M.D Kedir-Talha , Mohamed Mehenni

1043

uzzy linear regression analysis of job satisfaction of Taiwan college graduates A f Lu Chyu-Chiang Kao and Chin

1051

Damped Vibration Analysis of Extrinsic Fabry-Perot Interferometric Sensors using Artificial Neural Networks Rohit Dua , Ayat Jafari

1058

Review on the Development and Utilization of Artificial Neural Networks Applied to ECG Signals Diagnosis Salama Meghriche , Mohammed Boulemden

1066

An Improved Odor Recognition System Using Learning Vector Quantization with a New Discriminant Analysis Turgay Temel, Bekir Karlik

1075

PARALLEL COMPUTING & DISTRIBUTED COMPUTING

Data base Distribution in Telemedicine Alsultanny , Zeyad Nasro. Yas A

1081

OptorSim SimulatorA Management Protocol of Replications in the

Ghalem Belalem

1090

Architecture of Multi-Agent System for Distributed Systems Prof. Dr. Hilal M. Yousif , Ass. Prof. Dr. Jane J. Stephan , Dr. Ghossoon M.W. Al_Sadoon

1098

Intelligent Agent System for Accessing Remote Energy Meters Padmin.and T. Sankaranarayanan.E.Suriyakala ,P.D.Ci

1104

Multi Installment Scheduling and Allocation of Divisible Jobs on Single Level Tree Networks with Buffering Limitation Sameer M. Bataineh , Abdullah M. Audat

1111

Grid Environment for Password Recovery Jadallah , Amjad Abu Jbara. Dina S

1119

Parallel Implementation of the Finite Difference Time Domain Method Using the Message Passing Interface Omar Ramadan , Oyku Akaydin

1127

Bayesian Student Modeling in a Distributed Environment Yaser Nouh, Indumathy.R, Karthikeyani.P, Varunkumar Nagarajan, and R. Nadarajan

1132

A Model for the Estimation of Buffer Requirement in Distributed Networks Saleh A. Khawatreh , Khalid Khanfar

1141

SOFTWARE ENGINEERING

sionalism and ResponsibilitiesCode of Ethics, Profes

Khader Muspah Titi

1146

Case Study of: Evaluating the Role of Concerned Parties in Media Awareness against Software PiracyJordan

Sheikh , Abdullah Rashed , Rawan Nassri Abulail , Moh`d Abdallah Ali Shkoukani , Bashar Alqudah-Asim El

1156

Assessment of System Development Models with Regard to Software Reuse Practice

Adnan Rawashdeh

1164

Identifying Representatives for Interfering Automata Viliam Holub

1178

s Failure ’box Component-kDetermining the Blac

Ibrahim Hilal , Aman Jantan 1186

) UML(Perceptions of the Unified Modeling Language ’ Users Jafar Ali , Bassam Hasan

1190

How quality assured by Extreme How quality assured Exterme Programming (XP )? Sana'a j. Khalaf

1198

Managing Inconsistency in Software Requirements A Systematic Approach for

Randa Ali Numan Khaldi , Dr. Saleh Abu-Soud

1204

Requirement Modeling -Using Ontology to Support Software Development ProcessNisreen Innab , Ahmad Kayed

1216

WIRELESS COMPUTING

Designing and Modeling MEMS Filter for Front-End Wireless Transceivers

Mustafa S. Al_Khusheiny , Burhanuddin Y. Majlis

1223

WEB PERSONALIZATION FOR MOBILE DEVICES Akbar Ali , Ruwi. Malathi , J.Balaji , B.D

1231

Basic notions, energy consumption and MAC protocol layer: Wireless Sensor Networks Ahmed LOUAZANI , Bouabdellah KECHAR , Mohamed Faycal KHELFI

1236

WLAN Based on Location FingerprintingDecision Tree Approach to Estimate User Location in

Osama Mohamed Badawy , Moustafa Ahmed Bani Hasan

1247

An Analytical Model for Short-Lived TCP Flows in Heterogeneous Wireless Networks Sameer Bataineh , Jamal Al-Karaki , Haya Sammaneh

1256

Time Scheduling in Hybrid Wireless Links -Using Link Diversity for RealLiliana Grigoriu

1275

Position Location in Wireless Networks Zahid Ali

1284

Weighted Angular Distance Based Cache Replacement Strategy for Location-Dependent Data in Wireless Environment Mary Magdalene Jane. F, Parameswaran.R, Raghavendra Prasad.R, R.Nadarajan

1290

WIRELESS NETWORKS

Dependable and Secure Data Storage and Retrieval in Ad-Hoc Networks Ali Barati , Ali Movaghar

1299

Development and Performance Analysis of a Probabilistic Flooding in Noisy Mobile Ad Hoc Networks Bahadili , Yousef Jaradat-Hussein Al

1306

World Implementation -rotocol under theRealVector P-Distance-Demand-on-Hoc-Performance of the Ad Yusnani Mohd Yussoff , Habibah Hashim , Mohd Dani Baba

1317

ique for Mobile Adhoc NetworksAn Effective Terminode Routing Techn Balamurugan , Jameer Basha

1327

AND CORRECTION TECHNIQUES USEDAN INVESTIGATION OF ERROR DETECTION IN WIRELESS TRANSMISSION

VIJESH. JAGADEESH KUMAR , K. K.J.S

1336

An Addressing Scheme for Routing and Power Saving in MANET Arwa Zabian

1343

Network ) PRMA(Network and Wireless ) Token Ring(Throughput and Delay Analysis of Integrated Wired Amaal Al_Amawi

1352

١٨٢

A New Steganography System Based on a Hybrid Transform

Dr. W. A. Mahmoud University of Al-Isra, Jordan Profwaleed54@yahoo.com

B. Q. Al-Mussawi

University of Kufa, Iraq bahaamusawi@yahoo.com

ABSTRACT In this paper a secret-key Steganographic system will be illustrated which embeds four

gray-scale secret images of size ( 128128 × ) pixels into a cover image of size ( 512512 × ) pixels. The techniques used in this project to analyze the cover into its frequency components are a Wavelet transform and a new transform that is called Hybrid transform. Hybrid transform overcomes the weakness of Wavelet in higher dimensions; with this transform we own Orthonormality. The Hybrid transform is itself invert- the inverse transform use the same algorithm as the forward transform.

Combinations of Steganography and cryptography have been made in this work to increase the level of security and to make the system more complex to be defeated by attackers.

By both objective and subjective observations, the resultant stego-image that will be transmitted did not draw any suspicion, so the main goal of Steganography is performed. The proposed system can easily be applied by any end user who can provide the system with his key and both the embedded and the cover images, and to get the stego-image. The results obtained from Hybrid transform are better than obtained in Wavelet transform.

The proposed system was built by using (Matlab version 6.5) and run on Pentium-4 computer.

Key words: Fourier Transform, Wavelet Transform, Hybrid Transform, Steganography, Cryptography. 1. Introduction. Steganography is the art and science of hiding. Steganography system is embedding hidden content in unremarkable cover media so as not to arouse an eavesdropper’s suspicion [2][3]. In this paper, the proposed security system is composed of two stages (Cryptography and Steganography) to hide up four grayscale images of size )128128( × pixels inside a grayscale covered-image of size

)523523( × pixels in case of Hybrid transform and )512512( × in case of Wavelet transform. Thus in addition to Steganography, the secret images should be first encrypted to provide additional level of protection.

The cryptographic stage is composed of three sub-stages for the purpose of forming the scrambled image before embedding data into the cover image. These sub-stages are the transposition ciphering and stream ciphering and then transposition ciphering [4][5]. Hybrid transform consists of four stages namely 2-D Fourier transform, data arrangement, 1-D inverse Fourier transform and then Wavelet transform. In Hybrid transform the advantages of Fourier transform and Wavelet transform are obtained where the line discontinuities are represented as lines instead of points. This ability gives the system better representation for line discontinuities than Wavelet transform does.

١٨٣

2. Transforms Technique 2.1 Fourier Transform In 19th century, the French mathematician, J. Fourier, showed that periodic function can be expressed as an infinite sum of periodic complex exponential functions. Many years after this remarkable property of periodic functions was discovered. The ideas were generalized to non-periodic functions, and then to periodic or non-periodic discrete time signals. After this, Fourier transform became a very famous tool for computer calculations. The equation

is generally called the Fourier Transform, while the equation

is called the inverse Fourier Transform. Note that in the Fourier Transform equation, the integration is from minus infinity to plus infinity over time. So, no matter when the component with frequency ω appears in time, it will effect the result of the integration equally as well [2][3].For many signals, Fourier analysis is extremely useful because the signal’s frequency content is of great importance. So, why do we need other techniques, like wavelet analysis are needed? Fourier analysis has a serious drawback. In transforming to the frequency domain, time information is lost. When looking at a Fourier transform of a signal, it is impossible to tell when a particular event took place [4].

In an effort to correct this deficiency, Dennis Gabor (1946) adapted the Fourier transform to analyze only a small section of the signal at a time-a technique called windowing the signal. Gabor’s adaptation, called the Short-Time Fourier Transform (STFT), maps a signal into a two-dimensional function of time and frequency [4]. The basic idea is to divide the signal into small enough segments, where these segments can be assumed to be stationary. The width of this window must be equal to

the segment of the signal where this assumption is valid. The Windowed Fourier Transform has several problems. If we use a window of infinite length is used, the Fourier Transform, which gives perfect frequency resolution, but no time information will be obtained. On the other hand, in order to obtain a stationary sample, we must have a small enough window in which the signal is stationary. The narrower we make the window, the better the time resolution, and better the assumption of stationary, but poorer the frequency resolution. However, the Wavelet transform solves the dilemma of resolution to a certain extent, as will be described in the next part [3].

2.2 Wavelet Transform The fundamental idea behind wavelets is to analyze the signal at different scales or resolutions, which is called multiresolution. Wavelets are a class of functions used to localize a given signal in both space and scaling domains. A family of wavelets can be constructed from a mother wavelet. Compared to Windowed Fourier analysis, a mother wavelet is stretched or compressed to change the size of the window. In this way, big wavelets give an approximate image of the signal, while smaller and smaller wavelets zoom in on details [5]. Therefore, wavelets automatically adapt to both the high-frequency and the low-frequency components of a signal by different sizes of windows. Any small change in the wavelet representation produces a correspondingly small change in the original signal, which means local mistakes will not influence the entire transform. The wavelet transform is suited for non-stationary signals, such as very brief signals and signals with interesting components at different scales [4][6], figure (1) illustrates the comparison between the output of wavelet transform and other transforms.

dte)t(f)w(F jwt−∞

∞−∫= ………. (1)

dwe)w(F21)t(f jwt∫

∞

∞−

=π

..……. (2)

١٨٤

2.3 The Proposed Hybrid Transform Hybrid transformation is proposed here combining four stages namely: the 2-D Fourier transform, Data arrangement, the 1-D inverse Fourier transform and the1-D wavelet transform. The following procedure shows the computation steps that are used in this hybrid transform: Step 1:

The size of the input data should be square and prime number. Here, a size of

)523523( × pixels is used; this size is selected experimentally after several tests. Note that this transformation will be applied only to the cover image.

To simplify this procedure in detail the image X will be considered of size )77( × as an input to this transformation.

X =

0000000000000000111000011100001110000000000000000

………. (3)

Step 2: The 2-D Fourier transform (F) to the input image data X is calculated. Hence F will be equal to:

−+−+−−−−++−

+−−−−−+++−−+−−−−+−+−−−−+−+−+−−+

−−−−+−+−−−+−+−+−−−−+−−+−−−++−−

94.314.321.127.075.140.040.112.154.012.100.004.592.207.621.127.030.006.034.027.0193.040.000.030.054.012.130.12.1

75.140.030.027.027.057.000.064.019340.054.012.134.253.040.112.119.040.000.064.027.057.034.027.075.140.034.253.054.012.100.030.019.040.034.027.030.006.021.1277.03.103.100.0048.554.012.140.112.175.140.021.127.094.314.392.207.692.207.630.104.134.253.075.253.030.104.192.207.600.9

iiiiiiiiiiiiii

iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii

……………………… (4) Before applying data arrangement, the dc component will be saved and replaced by zero so that the reconstruction process can be more resistant against noise.

m = F(1,1) / p ………………. (5) F(1,1) = 0 ………………….. (6)

−+−+−−−−++−+−−−−−+++−−

+−−−−+−+−−−−+−+−+−−+−−−−+−+−−−+−+−+−−−−+−−+−−−++−−

94.3i14.321.1i27.075.1i40.040.1i12.154.0i12.100.0i04.592.2i07.621.1i27.030.0i06.034.0i27.0193.0i40.000.0i30.054.0i12.130.1i2.1

75.1i40.030.027.027.0i57.000.0i64.0193i40.054.0i12.134.2i53.040.1i12.119.0i40.000.0i64.027.0i57.034.0i27.075.1i40.034.2i53.054.0i12.100.0i30.019.0i40.034.0i27.030.0i06.021.1i277.03.1i03.100.0i048.554.0i12.140.1i12.175.1i40.021.1i27.094.3i14.392.2i07.692.2i07.630.1i04.134.2i53.075.2i53.030.1i04.192.2i07.600.0

…………….….. (7) Step 3: In this step, the data arrangement will be performed. The important point that should be taken into account is the size of the input image which must be a prime number and a square matrix. The benefit from this arrangement is to transform from Cartesian coordinate to polar coordinate. For the 77 × matrix, a

Figure (1) Comparison between wavelet output transform and others output transform

١٨٥

matrix of (K,L) dimension that belong to slices without including the point (0,0) is constructed as given below, p=7 (where p represent the number of rows or columns).

K =

−−−

321123

……………….. (8)

Where K represent the transpose of the value of [-p2 :-1,1:p2], where p2 represent the floor of (p/2). Next, the following modification should be followed to achieve this arrangement:

[1] Add horizontal and vertical slices later. m=1 2 3 4 5 6

G = K(:,ones(1:p-1)) …...……… (9)

G =

−−−−−−−−−−−−−−−−−−

333333222222111111111111222222333333

…….... (10)

[2] Centralize L mod P by employing the

matrix notation L & P matrices of the form :

L =

−−−−−−−−−

−−−−−−−−−−−−

312213231132321321654321231132312213

…….... (11) ……………...… (11)

Then, put it in polar coordinate:

P =

−+−+−+−++−−+−−−++++−+−+−−−−−−−+−−−−−+−+−−−+−−−+−−−+−−−

iiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii

331323231333223212123222112131312111112131312111223212123222331323231333

. .……….(12) Where each real value in matrix P represents its corresponding value of matrix G and each imaginary value in matrix P represent its corresponding value of matrix L.

[3] Compute the angles of all these elements of the matrix in radian and consider all positive angles and replace the negative angles by NaN.

D =

NaNNaNNaNNaNNaNNaNNaNNaNNaN

NaNNaNNaNNaNNaNNaNNaNNaNNaN

333322

321123223333

….…(13)

[4] In case of equal D favor min ABS(P) and min ABS(G), then[ ] ( ) ( )kabsepsilon)p(absepsilonDminI,Y 2 ×+×+= where epsilon= e -6

Y = [ ]122221 I = [ ]335244 ..….. (14)

[ ]2p:0J −= ................ (15) [5] Retrieve these points and put them in a

set of directions

( )( ) ( )( )[ ]J1pIL;JpIKM ×−+×+= ...(16) M =

[ ]112211 −−− [ ]121121 ………… (17)

[6] Add horizontal and vertical slices. M = [ ]01112211 −−− [ ]10121121 . ………. .. (18)

[7] Sort out these directions in ascending order of angles and the result will be as follows: Y = [0 0.46365 0.7854 1.1071 1.5708 2.0344 . 2.3562 2.6779] I = [7 4 1 2 8 5 6 3 ] ……………… (19)

M =

−−−1121211021101121

………….. (20) Step 4: Computing Fourier slices these are represented by (K , L) Where

( )( )p,:,1MtmodK ×= ....…… (21)

( )( )p,:,2MtmodL ×= ……... (22) And [ ]1p,0t −= ........ (23)

١٨٦

K =

21106656422055356330441414403363355022425660112100000000

…………(24) ……..….... (24)

L =

66565660553535504414144033636330224242201121211000000000

………... (25)

t =

6543210

............ (26)

Where the instruction mod return the output of mod (x,y) as follows : If the sign of x & y is similar then it returns ynx ×− where n =floor(x,y). If the sign between them is different then it returns rem(-x,y)+y. After these computations one can find the projection of Fourier transform

( )Lpkfxfy ×++= 1 ………….. (27)

fy=

−−

−−+−+−

+−

−+−+−+−−+−+−

−+−−+−−+−−−−+−−−+−−+++−−+−−−++−−+−+−−+

+−−−−−−+−−−−

54.012.134.027.0

75.140.075.140.034.027.054.012.1

00.0

00.004.554.012.192.207.621.127.094.314.321.127.092.207.600.030.034.027.03.103.119.040.030.006.019.040.030.103.100.064.075.140.034.253.040.112.127.057.040.112.134.253.000.064.075.140.034.253.040.112.127.057.040.112.134.253.000.030.034.027.030.103.119.040.030.006.0193.040.030.103.100.004.554.012.192.207.621.1277.094.314.321.1277.092.207.6

00.000.000.000.000.000.000.0

iiiii

iiiiiiiiiiiiiiiiiiiii

iiiiiiiiiiiiiiiiiiiii

. .………… (28)

Step 5: Take the 1-D inverse Fourier transform for the output of the step 3. y real ( inverse Fourier transform for yf ) yf =

−−−−−−−−−−−−

−−−−−−−−−−−−−−−−−−−−−−−−−

28.071.028.028.128.071.128.028.171.028.028.028.128.071.028.028.128.028.171.071.128.028.028.071.171.028.128.071.171.028.171.071.128.028.071.071.128.028.128.071.128.071.028.028.171.028.071.028.128.071.128.028.128.071.028.028.1

… (29)

after taking the 1-D inverse Fourier transform one makes normalization to the output of the inverse Fourier and as follows:

pyy /= =

−−−−−−−−−−−−

−−−−−−−−

−−−−−−−−−−−−−−−−

10.027.010.048.010.164.010.048.027.010.010.048.010.027.010.048.010.048.010.164.010.010.110.064.0

27.048.010.064.027.048.027.064.010.010.027.064.010.048.010.064.018.027.018.048.027.010.027.048.018.064.010.048.018.027.010.048.0

…..(30)

Step 6: Before applying 1-D Wavelet transform a row of zeros must be added to the output of step 4 to satisfy the condition of the input image matrix; then the input image matrix of wavelet transform will equal to:

X =

−−−−−−−−−−−−

−−−−−−−−

−−−−−−−−−−−−−−−−

00.000.000.000.000.000.000.000.010.027.010.048.010.164.010.048.0

27.010.010.048.010.027.010.048.010.048.010.164.010.010.110.064.0

27.048.010.064.027.048.027.064.010.010.027.064.010.048.010.064.018.027.018.048.027.010.027.048.018.064.010.048.018.027.010.048.0

..(31)

After adding the row of zeros, the following procedure is applied:

1- For an 88× matrix input 2-D signal, construct a D4 transformation matrix, W.

W=

−−

−−

−−

−−

230000311000002131230000

3210000000312300003210000000312300003210

CCCCCCCCCCCC

CCCCCCCC

CCCCCCCC

CCCC ........(32)

Where C0= ( ) 24/31+ , C1= ( ) 24/33 + ,C2= ( ) 24/33 − and C3= ( ) 24/31− . 2- Apply row transformation as follows:

i) Z=W*A; Z=

−−−−−−−−−−−−−−−−−−

−−−−−−−−

−−−−−−−−−−−−

09.054.009.040.004.012.004.040.006.024.006.028.011.038.011.028.013.031.010.038.005.049.005.038.0

14.023.001.020.016.031.016.020.010.029.020.025.015.011.015.025.0

11.055.011.006.116.070.016.006.101.029.025.079.010.048.010.079.020.057.006.057.011.000.011.057.0

..... (33)

ii) permute [Z] to get P

P=

−−−−−−−−−−−−−−−−−−−−−−−−−−−

−−−−−−−

−−−−−

09.054.009.040.004.012.004.040.013.031.010.038.005.049.005.038.010.029.020.025.015.011.015.025.001.029.025.079.010.048.010.079.006.024.006.028.011.038.011.028.0

14.023.001.020.016.031.016.020.011.055.011.006.116.070.016.006.120.057.006.057.011.000.011.057.0

. ........ (34)

١٨٧

3. Conversion of the Hybrid Transform as a Vector At this stage the output of the Hybrid transform will be arranged as a vector. Here only 65536 pixels from 273529 pixels are selected; this vector is arranged in matrix of size 102464 × . Next, the coefficients are coded to 24 bit. The secret message will be embedded in these formed coefficient matrix of 102464 × following certain rules. 4. Encryption Process The four secret images of size )128128( × pixel are encrypted in such a way to form one encrypted image of size )256256( × pixel. The resultant image encompasses all secret images but in scrambled form. The encryption that has been taken in this thesis is composed of three stages: transposition ciphering, stream ciphering and transposition ciphering. 4.1 Transposition Ciphering: First, each secret image is divided into blocks usually of fixed size. The proposed system suppose that each secret image

system suppose that each secret image will be divided into a set of blocks of size

)44( × pixel, then sequentially reordering the blocks in a manner to form a vector.

After one gets four vectors corresponding to four secret images, the first ciphered image will be created by transposition. This can be achieved by taking the first block of each vector to form the first super block of the ciphered image, and so on. The size of super block is )88( × pixel. Since the four original secret images are of size )128128( × pixel each, then the first ciphered image will be of size )256256( × pixel. Applying the transposition ciphering to the four secret images will mix the properties of all images; therefore it is so difficult to recognize them.

4.2 Stream Ciphering: Stream ciphering is the second level of ciphering technique. The stage of stream ciphering is applied to the final resultant image from the transposition cipher. Eight pixels are taken from this image and then each pixel is converted into 8-bits. Since the image is a gray scale of 256 -level then the 8-bits is sufficient for all image. After this conversion, the result is arranged to form a matrix. This matrix is of size

)88( × bits because there are 8-pixels and they are converted into 8-bits, hence there are 64 -bits. The stage of stream ciphering is applied to this matrix by scrambling the streams of bits. The scrambling is made by taking the last column of this matrix as the first row in the scrambled matrix and so on. This means that each row in the scrambled matrix represents the new pixel after it is converted into decimal mode. This new pixel has one bit from each original 8 pixels. In other words, each time 8 pixels are taken from the image and converted into binary mode. This result will be translated into matrix form of 8 pixels. Each row in this matrix represents one pixel from the 8 pixels. The scrambling is converting the columns-starting from the last one as the first row into the new matrix and so on. Each row in the scrambled matrix is translated into decimal mode to form the new 8 pixels into the stream ciphered image. This process is done on the whole size of transposition-ciphered image. At this point, the stage of stream ciphering is completed. 4.3 Transposition Ciphering: This stage is to make the security system more robust and secure. This additional stage redistributes the pixels of stream-ciphered image according to a secret algorithm. The above algorithm divides the stream-ciphered image into four blocks of equal size. As the stream ciphered image is of size )256256( × pixels then the blocks will be of size )128128( × pixels each.

١٨٨

Figure (2) Algorithm used for final ciphered image. A- Stream-Ciphered Image. B- Final-Ciphered Image The first pixel in block 1 and the corresponding pixels in the other blocks are combined to form matrix of size

)22( × pixels. This matrix is the first block of the final ciphered image. Doing this operation to the whole pixels of the stream ciphered image we will get the final ciphered image. Figure (3) shows typical encryption process.

5. Embedding Process After getting the final ciphered image, the cryptography technique has been completed; after that, the embedding process will be started. The coefficients obtained in the Hybrid transform are randomly selected from the vector of Hybrid transform according to a pseudorandom [7], which is named

)1PN( .Therefore, if 5)I(PN = , then coefficient number 5 will be used as a host to the 8-bits from the final ciphered image. Each element in the vectors consists of 24 bits; the 24th bit represents the sign of the related coefficient while the 1st bit represents the most significant bit )MSB( of the coefficient. The embedding process will place the 8- bits of final ciphered image instead of 8- bits from the 23 bits of the coefficient; the selection of which 8-bits will be taken from the 23 bits depends on another pseudorandom named )2PN( . By experiment, four best locations could

be used to embed secret message; these locations are taken between (bit 12-19, bit 13-20, bit 14-21, and bit15-22). So, according the PN2, which has four decimal values, the location where the 8-bit will be embedded can be identified. Keeping on this process till all bits of final ciphered image are completely embedded in the coefficients.

6. The Proposed Steganography System for Recipient The recipient will certainly get the stego-objcet. But he could not extract the secret information out of the cover without knowledge of which keys )2PN&1PN( have been used in the embedding process.

88878685848382817877767574737271686766656463626158575655545352514847464544434241383736353433323128272625242322211817161514131211

AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA

(A)

88848783868285814844474346424541787477737672757138343733363235316864676366626561282427232622252158545753565255511814171316121511

AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA

(B)

Secret image 1

Secret image 3

Secret image2

Secret image 4

First-ciphered image

50 100 150 200 250

50

100

150

200

250

Stream-ciphered

Final-ciphered

50 100 150 200 250

50

100

150

200

250

Figure (2) typical encryption process

١٨٩

The recipient also should know the manner used in the encryption process. For hybrid based stego, when the requirements are present then the extracting process will be started. This can be done by handling the stego-object by hybrid decomposition using the same procedure that is used in the proposed Steganography system for sender, the coefficients results are rearranged in a manner similar to that in the sender. Using the same 1PN and 2PN used in the sender to select the coefficients where the data has been embedded and to extract the bits of the final ciphered image. By taking the inverse of the ways used in encryption process, the four secret images are perfectly reconstructed. 7. Conclusions The proposed system can be defined as a secret key Steganographic system where the same key has been used by the sender and recipient. The images which contain sharp edges or more high frequency component (more details) can better be used in the embedding process. The result which is obtained in Hybrid transform is more stability against noise than Wavelet transform, table (1) shows values of PSNR and correlation test for some types of image format for Wavelet transform and Hybrid transform. Table (1) values of PSNR and correlation test for some types of image format for Wavelet transform and Hybrid transform.

Figure(4) shows original cover image and it's corresponding stego-image in Wavlet transform case and in Hybrid transform case.

References [1] N., Johnson, Z., Duric and S., Jajodia, "Information Hiding Steganography and Watermarking Attacks and Countermeasures", Kluwer Academic Publisher, 2001. [2] G., Chen, "Applications of Wavelet Transform in Pattern recognition and De-noising", M.Sc. thesis, Concordia University,1999. [3] P., Xiao, "Image Compression by Wavelet Transform", M.Sc. thesis, East Tennessee State University, 2001.

[4] M. Misiti, Y. Misiti and J. Poggi, "Wavelet Toolbox for use with MATLAB", MATLAB version 6.5. [5] F., A., Sabir, "Evaluation of Information Hiding For Still Image", M.Sc. thesis, University of Technology, Electrical Dept., 2004. [6] Jacob T. Jackson, Gregg H. Gunsch, Roger L. Claypoole, Jr., Gary B. Lamont, "Blind Steganography Detection Using a Computational Immune System", International Journal of Digital Evidence, Vol. 4, Issue 1, pp.1-19, Winter, 2003.

Image type and name Transform Type

01.BMP 02.JPG 03.TIF

Wavelet transform

PSNR =47.7010

correlation =0.9999

PSNR =47.5405

correlation =0.9999

PSNR =47.5450

correlation =0.9999

Hybrid transform

PSNR =52.2401

correlation =0.9999

PSNR =52.4401

correlation =0.9999

PSNR =52.0451

correlation =0.9999

Stego-image using wavelet transform

Stego-image using Hybrid transform

Original cover

Figure (3) Original cover image with it's corresponding stego-image in Wavelet transform case and in Hybrid transform case

١٩٠

[7] W. Chen and C. Chen, "Multi-Resolution Structure Color Image Compression Using DWT and VQ", Dept. of Electrical Engineering, National Cheng Kung University Tainan,70101, Taiwan, R.O.C. [8] S. Areepongsa, Y. F. Syed, N. Kaewkamnerd and K. R. Rao, "Steganography for Low Bit Rate Wavelet Baesd Image Coder in Image Retrieval System", explre2, pp. 1-6, 2000.

[9] K., Gulati, "Information Hiding Using Fractal Encoding", M.Sc. thesis, School of Information Technology, Indian Institute of Technology Bombay, 2003.