New Classification Methods for Hiding Information into Two Parts: Multimedia Files and Non Multimedia Files

JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 144 New Classification Methods fo r Hiding Information into T wo Parts: Multimedia Files and Non Multimedia Files Hamdan.O.Alanazi, A.A.Zaidan, B.B.Zaidan, Hamid A. Jalab and Zaidoon Kh. AL-Ani Abstra ct — With the rapid development o f various multimedia techn ologies, more and mor e multimedia data are generated and transmitted in the medical, commercial, an d military fields, w hich may include some sensitive inf ormation which should not be acc essed by or c an only be partially ex posed to the general users. Therefore, security an d privacy has become an import ant, Another proble m with digital d ocument and video is that un detectable modifications can be ma de with very simple a nd widely availab le equipment, which p ut the digital mat erial for evidential purposes under question .With the large flood of information and the development of the digit al format Information h iding considers one of the te chniques which used to p rotect the import ant information. The main goals f or this paper , provides a gen eral overvi ew of the New Classification Method s for Hiding Information in to T wo Part s: Multimedia Files and Non Multimedia Files. Index T erms— Hidden in Mult imedia File, Hidden in No n Multimedia File, S trength and Weakness Factor s of S teganography ——————————  —————————— 1. INTRODUCTION D u e t o a d v a n c e s i n I C T , m o s t o f i n f o r m a t i o n i s k e p t electronica lly. Consequently, the se curity of informa tion has become a fundamental i ssue. Besides cryp tography, steganography can be employed to se cure information. Steganograph y is a technique of hiding information i n digital media. In contrast to cryptography, the message or encrypted message is em bedde d in a digital host before passing it through the network, thus the existence of the message is unknown. Besides hid ing data for confidentialit y, this app roach of information hiding can be extended to copyright protection for digital media: audio, video, and images [1].  Hamdan.O.Alanazi – Master Stu dent, Department of Computer Syste m & Technology , Univer sity Ma laya, Kuala Lumpur, Malay sia.  A. A. Zaidan – PhD Candidate on the Department of Electrical & Computer Engineering , Faculty of Engineering , Multimedia University , Cyberjay a, Malaysia.  B. B. Zaidan – PhD Can didate on the Department of Electrical & Computer Engineering / Faculty of Engineering, Mul timedia University, Cyberjaya, Malaysia.  Dr. Ham id.A.Jalab- Senior L ecturer, Department of Computer Science &Information Technology , University M alaya, Kuala Lumpur, Malaysia  Zaidoon Kh. AL-Ani - Master Student on the faculty of Information and Communi cation Technology at International Islamic University Malays ia, Kuala Lumpur, Malaysia. In addition, the rapid growth of publishing and broadcasting te chnology also require an alternative solution in hiding informat ion. The copyright such as audio, video and other source availa ble in digital form may lead to lar ge-scale unauthor ized copying. This is because the digital fo rmats make possible to provid e high image qua lity even under multi- copying. Therefore, The growing possibi lities of mod ern communicat ions need the speci al means of security esp ecially on computer network. The network se curity is becoming more important as the number of data being exchanged on th e I nter net inc rea ses. Th eref ore , th e co nfid enti ali ty and data inte grity are requires to protect against unauthorized access and use. This has resulted in an expl osiv e gro wth of th e fi eld of infor ma tion h idin g [2 ]. the special p art of invisi ble infor mation is fixed in ever y image that co uld not be easily extracted without specialized technique saving image qualit y simultaneously .Al l this is o f great concern to the music , film, book and software publishing in dustries[5],[7]. Information hiding is an eme rging research area, whi ch encompasses applications such as copyright protection for di gital me dia, waterm arking, fi ngerprint ing, an d steganogra phy. All these applicati ons of informatio n hiding are quit e diverse [8]. In watermarking applic ations, the message contains information such as owner identification and a digital time stamp, which usually appli ed for copyright protection [15]. Fingerprint, the owner of the data set embeds a serial number that uniq uely identifies the user of th e data set. This adds to copyright information to makes i t possible JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 145 to trace any unauthorized used of the data set back to the user [1]. Steganography hid e the secret message within the host data se t and presence imp erceptible. In thos e applications, information is hidden wit hin a host data set and is to be reliably com municated to a r eceiver. The host data set is purposely corrupted, but in a covert way, designed to be invisib le to an informal analysis [21]. Howeve r, this paper will o nly focus on info rmation hiding using steganography approach with in new classification methods for hidin g information in to two parts: Multimedi a File and Non Multimedia Fil e [15]. 2. H IDDEN IN M UL TIMEDI A F ILE One of ea rlier and popular m ethods of hidden information is hidden data in t he text file, it takes m any phases and many ways, each one has its own affect ivity and efficiency, some of these methods used for hidden d a t a i n t h e t e x t a s w e s h o w n i n t h i s p a p e r h o w t h e Germ an s py use this a rt , oth er te chnol ogy use t he sp ac e between the word to embed da ta. 2.1 Hidden in Text The most common m ethods of c oncealment a nd simplest is Switches ( Binary Digit) known briefl y as (bit), least signific ant known as (LSB), Wher e it is altered binary digit characte rs to th e message characters to be hidden, after conversion of such characters to byte as well as the American standard code for informatio n intercha nge (ASC II). We c annot us e this me thod her e because switching bina ry digit might lead to an increase or decrease the value of letter by (1); this leads to the advance of this letter with the neighbor lett er, for example the letter (C) in Engl ish represent in b inary (100 0011) for instant i f we replace the Least Signifi cant bit the binary value b ecome (100 0 010) which is represent (B) in English, that will m ake the carrier t ext become a meaningless, wh ich denies the goal of hi dden techniqu e, Therefore resort to other means which exploit spaces between strings and words in the carrier text [6]. Methods of concealment in the text a re weak and inefficie nt it is also not suitable for the applic ation, the main disadvantages include [13],[16]:  Need large text to hide small message  Some methods requ ire complex t echniques for the application like method of hidden infor mation in the words [18].  The possibilit y of noting changes in th e carrier letter compared with the original  The probability of crash the system of concealment in case of presenting the letter using one service applications such as (word) as a result of it contains some automatic fo rmat, which leads to chang e the long spaces between words (for the English version)[19]. Hidd en techniques are limite d for the text with difficulty concealing other types of m essages like equations, c harts, images and sounds. 2.1.1 Hidden in Space In this technique; parts of the secret letter tight in to the spaces of the carrier letter these technical include two ways of methods; in the first method we may embed one or two spaces af ter each se t of phrases for the carrier letters, and the second method contains the same way of the first method except that the process is embedding after every word of the carrier le tter words [9]. The first method more efficient for la ck of change compared with the original text but i t is not efficien t in terms of the amount of data that possible to embed, the way in the second method could embed m ore quantita tive da ta but m ore likely for o bserva tion and perception compared to the origi nal text [10] . 2.1.2 Hidden in Words This t echnique was used duri ng the Second Worl d War, sending a hidden m essage co ntained by a nothe r message whi ch is not relevant, th e role of this ide a is nomination letters in every word of the carrier letter from the characters confiden tial letter to be sent [9]. One of these examples was the letter that was sent by Deutsch Spy during the Second World War “Apparently neutrals protest is thoroughly disc ounted and ignored. Is man hard hit Blockade issue affects pretext for embargo on by-products, ejecting suet’s a nd vegeta ble oils” by analyzing this lette r crafts taking the second letter in each word it wi ll show us the followi ng secret l etter “Perishing sails from NY June1 “[10]. This method is very complex and not e fficient in terms of application in the computer system sinc e it requires an expert system in the fiel d of language through which to cho ose the suita ble words and build the required s entence, as well a s a huge da tabase requires [11]. 2.2 Hidden in Digital Images In the comp uter images are rep resenting as two dimensional array, this arrays incl ude the pixels, in fact the number of bits in pixels represent the type of image; each one representing inten sity lighting of pixel (the smallest unite i n the image ) Thes e va lu es u sed b y Ra st er to view on the screen the place posed by each of these values. The pr ocess of access each unit valu es of the JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 146 image befor e scanni ng dep ends on th e represe ntation technical, depends on th e number of byte which used to r e p r e s e n t e a c h p i x e l , a n d t h a t w h a t t h e y c a l l i t t h e representation of image, now the representation of the image is the number of byte in the single pixel [6]. The most common representation is the 24 -bit, on which 3-byte represent the color of the image in the single pixel, there is other representation the call it 8-bit, in which only one b yte represent the color in the image, and each method representation has its own characteristics and dete rminants in the process of concealment, in this resear ch we will focus on the ima ge with the extensio n (JPG, BMP)[13]. 2.2. 1 Hidden in (24) Bit Image In this type of images the representatio n of each pixel is 24-bit where ea ch 3 byte represent basic colors Red, Green, and Blue (the C olor intensity light ing) And the integra tion of the t hree illumi nation intensit y is formed the required colo r (RGB) note that these percentages represent the true colors, and therefore they will be adopt ed directly by th e scanner to show the color requ ired for th e corre spondin g locati on on th e screen, which is why so of this kind of representation call ed (True Color) [16]. The use of this type of representation means that i t is possible to represent 256 different level of color for each of the three colors, this means that changing the least significant bit for each color cannot be realized by the human eye becau se of the change will increase or decrease the intens ity of the lighting color by (1) only from total (256), al so we can replace the 2nd least significant bit without th e possibility of recognition that change [16]. We can take this advantage of this feature to hide data within thes e areas and that by replacement bit of image by bit of data which should be hid den [16]. Fig 1. 24-bit images 2.2.2 Hidden in (8) Bit Image I n this type of images the presentation of each pixel by one byte or 8 -bit, image is repr esent as a valu es in a matrix models w hich do not represent th e true va lues of the image pixel, but it represent color index for the address on the s chema just gran dmothers of the true colors, or called (Palette) found in the image Heade r [18]. T h e n u m b e r o f c o l o r s l e v e l a t d i f f e r e n t p o s s i b l e presentation in eight bit is (256) color l evel, namely the schema just grandmothe rs contains 256 colors different expect level of the color, there a re two types of offers in this type of image one is represented by (256) different level of col or (256 Color), a nd the other r epresented by (256) different level of intensity diffe rent gray scale, each of these types ha s its own characteristics and advantages [18]. Fig 2. 8-b it images 2.2.3 Image Represent in 256 Colors Here, 256 diffe rent 24 bit colors (can also use 16 or 32 bit) are selected out of the 16 millio n possible. These 256 colors are ca lled the pa lette. Each p ixel in th e image is represented by a single byte. This byte is not the color but rather is the inde x of the color in the palette. When an image is sto red, the 8 b it color i ndex for e ach pixe l is saved along with the palette. For a large image this can be significant sp ace s aving s [18]. JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 147 Fig 3. 8-bit color i mages 2.2.4 Image Represent by 256 of Grey Level A grayscale or gray level image is simply one in which the only c olors are sha des of gray. The reason for differentiating such image s from any other sort of color image is that less info rmation needs to be provided for each pixel. In fact a `gray' color is one in which the red, green and blue components a ll have equal int ensity in RGB space, and so it is only necessary to sp ecify a single intensity value for each pixel, as opposed to th e three inte nsiti es need ed t o sp eci fy each pix el in a f ull c olo r image [19]. Often, the graysca le intensity is stored as an 8 -bit integer givin g 256 possible different shades of gray from black to white. If the levels are evenly spaced then the difference betwe en succes sive gray levels is signifi cantly better than the gray level re solving power of the human eye [19]. Grayscale images are very common, i n part because much of to day's dis play and image capture for hardware can o nly s upport 8-bit imag es. I n addit ion, grays cale images are enti rely sufficient for many tasks and so there is no need to u se more complica ted and har der-to- process color image s [19]. 2.3 Hidden Data in Wave Module 2.3.1 Hidden Data in the 8-bit Model Representation It was pointed out that thi s pattern is represented by each audio sample size ( 1Byte/Sample) and common here that the p rocess of concealment in last signi ficant bit each model where the sw itch imperceptibly by authorizing human [4]. In the 8-bit audio file representation means that each model will be rep resented eight size, m eaning that there is (256) audio level can be re presented at the highes t in this type is between (0 - 25 5) [4]. In th is k i n d o f r ep re s e n t a ti on re se ar c h e r h i de da ta i n the first bit that less important to detect this concealme nt, that is to conceal ratio (12.5% from the size of the file)[4]. 2.3.2 Hidden Data in the 16-bit Model Representation Presentation of the audio sample here using two bytes for each sample (2 Byte / sample ), a pattern that can be used as cover to hide in last two signific ant bit (2 LSB), or even in the third bit which is th e less significa nt to achieve the same co ndition in the above. This is the kind of repres entation of each audi o sample 16-bit, meaning that the number of audio levels that can be represented are (6 5536) a different l evel, so it is obvious that researcher find space to conceal much more than the previous type, for example, means changing, the bit less important, by increasi ng or decreasing one level of the above, and 2 bit change means b y increasing or decreasing three levels of th ose worst off, an d so on [4]. 2.3.3 Color System  RGB The RGB color mo del is an additiv e color mo del in which red, green, and blue light are added together in various ways to reproduce a broa d array of colors . The name of the model comes from the initial s of the three additive primary colors, red, green, and blue [5]. The ma in purp ose of the RGB color m odel is for the sensing, repr esentation, and di splay of images in electronic systems, such a s televisions and comp uters, t h o u g h i t h a s a l s o b e e n u s e d i n c o n v e n t i o n a l photography. Before the electronic age, the RGB color model already had a solid theory behind it, based in human perception of colors [5].  Color Color or Colour is t he visua l perceptual p roperty corresponding in hum ans to the categories call ed red, yellow, blue, bla ck, etc. The RGB color m odel is the most common way to encode color in computing, and several diffe rent b inary digi tal repr esentati ons are in use. Co lor derives from the spectrum of light (distribution of light energy versus wavelength) interacting in the eye with the spectral s ensitivities of the light receptors. Color categories and p hysical specificat ions of color are a lso associated with objects, mate rials, light sources, etc., based on th eir physical p roperties such as light absorption, reflection, or em ission sp ectra [12]. JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 148  Physical color Electromagnetic radiation is characterized by its wavelength (or frequency) and its inte nsity. When the wavelength is within th e visi ble spectrum (th e range of wavelengths humans can perceive, approximately from 380 nm to 740 nm), i t is known as "vis ible light". Most light source s emit light at ma ny different wavelengths; a source's spectrum is a distr ibu tion giving its intens ity at each wavelength. Although the spectr um of light arriving at the eye from a given direction determines th e color sensat ion in that di rection, there ar e many more possible spectral comb inations than color se nsations. In fact, one may formally define a color as a class of spectra that give rise to the same co lor sensation, a lthough such classes would vary widely among different sp ecies, and to a lesser extent among in dividuals within the same species. In each such class the members are called metamers of the color in qu estion [3].  Color in b it The main characteristi c of all of them is the quantization of the possible values per comp onent (technically a sample) by using only in teger numbers within some rang e [17]. 3. H IDDEN IN N ON M UL TIMEDI A F ILE 3.1 Hidden in Disk Space A nother way to hid e informa tion relies on hidden unused space that is not readil y apparent to an obse rver. Taking advanta ge of an unused or reserved space t o hold covert informat ion provides a mea n of hidden information without perceptually degrading the carr ier. The way operating system stores files typically results in an unused space that appears to be allocated to fi les [15]. Another method of hidden information in file system is to create hidden pa rtitions. These p artitions ar e not seen if the system is started normally [15]. 3.2 Hidden in Ne twork Packets With the rapid development of Internet technologies, the n umb er o f da ta pa cket s s ent a nd rec eiv ed electronica lly is increasing greatly. As th e technology of transmitting information on network in secure, the importance of informati on hidden as a field of information securi ty comes t o be re cogn ize d w ide ly [ 14 ]. Any of these packets can provide a covert communication channel. For example, TCP/IP packets are used to transport information ove r the internet. The pocket headers have unused space or oth er features that can be manip ulated to hid e information [ 21]. 3.3 Hidden in Software and Circuitry Data can also be hidden base d on the ph ysical arrangement of carrier. The ar rangement itself may be a n embedde d signature that is unique to the creator. An example is in the la yout of code dis tribution in a program or the layout of electronic circuits on a board. This type of ‘marking’ can be use d to uniquely identify the design origin and can not be removed without significant change to the work [21]. Table 1 Weaknesses of Method for Hiding Information . From the table above, it is clear that the main weaknesses of those methods are the size of the hidden data depends on the size of the cover file and any changes made are easily det ected by anti virus software. Thus, through this paper, these weaknesses will be solved through the use of exe.fil e. 3.4 Hidden in Portabl e Executable File (PE-F ile) The planne d system uses a portable exe cutable file as a cover to e mbed an executable program as an exam ple for t he p la nned sys tem.T his sect ion i s d ivid ed into four parts [1]:  Characteristic s of executable files  Advantage of PE-file. JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 149 3.4.1 Characteristics of Executable Fil es The chara cteristics of the Executa ble file does not have a standard size, li ke other files, for e xample the image file (BMP) the size of th is file is between (2-10 MB), Other example is the text file (TXT) the size often is less than 2 MB.Through our study the characteristics of files have been us ed a s a co ver, it fo un d tha t la cks sufficient size to serve as a cover for informatio n to be hidd en [ 15 ]. For these feat ures of the Executable fil e, it has unspecifie d size; it can be 650 MB like window se tup File or 12 MB such as installation file of multi-m edia players. Taking advantage of this feature (disparity size) make it a suitable environme nt for conc ealing informa tion without detect the file from attacker and discover hidden information in this fi le [2]. 3.4.2 Advantage o f PE-File The addition o f the Microsoft® windows NT™ operating system to the fami ly of windows™ operat ing systems brought many changes to the dev elopment environ ment and more than a few changes to applications themselves. One of the more significant changes is the introduction of the Portable Exec utable (PE) file format. The name "Portable Executable" refers to the fact that th e format is not architecture speci fic .In other words, the term "Portable Executable" was chosen because the intent was to have a common file format for all flavors of windows, on all supported CP Us. The PE files formats drawn primar ily from the Common Object File Format ( COFF) specification that is common to UNIX® operating systems [5]. Yet, to remain compatible with previous ve rsions of the MS-DOS® and windows operating systems, th e PE file format also retains the old familiar MZ header from MS-DOS. The PE file format for Windows NT introduced a completely new structure to developers f amiliar wit h the windows and MS-DOS environments [7],[8] . Yet developers f amiliar wit h the UNIX environment will find th at the PE file format is similar to, if not b ased on, the COFF specification .The entire format consists of an MS-D OS MZ header, followed by a real-mode stub p rogram, the PE fi le signature, the PE file header, the PE optional header, all of the section he aders, and finally, all of the section bodies[9],[10],[11],[15]. 4. O THER T ECHNIQ UES Other techniques commonly used to hide data, using the u nu sed are as o f di sk, for exa mp le i n th e op er ati ng system under Windows environment, organizes disk players (Formatted) using groupings (Clusters) size (32kB), and if the size of the file is open (1kB), the only remaining volume 3 1kB will be m issed, and these c ould be used to c onceal a signific ant amount of data[ 5],[12]. This is a good way in terms of size can take advantage of it to hide but it is not effici ent since its easy detection by using s ome service soft ware such as (Norton Commander) it could of fer six-ten f ormat, a s well as the correspondin g additional text note are hidden. Other techniques and th e use of abandoned areas (Reserved) of the prefix fil es (Files Header) im age and sound files, and thes e method s a lso vulnerable to the possibility of distinguished, and t he relatively small siz e [18],[19]. 5. S TRENG TH AND W E AKNESS F AC TO R S OF S TEGANOGRAPHY Although Steganography encompasses methods o f transmitting secret messages throu gh innocuous cover carriers in such a manne r that the very existence of the embedded messages is undetecta ble, but it also has some weaknesses that attackers ca n utilize these weak nesses and de tect and /or destru ct the embedded message 5.1 Weaknesses in the Concealment Systems The most imp ortant weaknesses of Steganography are as follows:  The process of hidden data by using Least Significa nt Bit (LSB), which is a common method, used the image as a cover for data to be hidden, but i t’s mostly subjected to attacks from attackers. Once attackers suspect there is Steganogr aphy implemented in the data, they will reproduce LBS and examine it to check whethe r it has a meaning or not.  the results of Steganography might be com pressed by Lossy Compression to reduce the size of the file especiall y at transferring the data, which leads to destroy the hidden data in that file after the reopening  In the case of using a co ver environment with equal value spaces a s in the pictures with con stant value c o lo ur s p a c e s ( w e e k t e x t u r e ) or s o u n d s w i t h co n s t a n t intensity sound intervals, that may lead to discovery or differentiation at these sectors .  One of the methods of breaking concea lment in image and sound is changing the format of the file. 5.2 Disadvantag es of the Concealment System The disadvantages of Steganography are as follows:  It requires other meth ods to hide the data.  The size of the output of the hidden data file is la rger comp arin g to th e enc oded da ta. In it s m ost effi cien t possible case, it may reach double the size of encoded d a t a o r a b e t l e s s . I n s o m e s i t u a t i o n s o u t p u t f i l e m a y reach eight times larger than the encoded data, as well as certa in files of med ia images and t ext, files may reach fifty times larg er when they are encoded. JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 150  It is not possible to combine the (maximize/ maximum) strength of Robustness with maximize/maxi mum amount of hidde n data comparing to data cover. 6. C ONCLUSION In this paper a overview for the new classification methods for Hiding Informat io n were presen ted into Two Parts: Multimedia Files , one of ea rlier and p opular methods of hidden informat io n ar e hi dden da ta i n th e (text file or D igital Images or Wave Mod ule ), it ta kes many phases and many ways , each one has its own affectivity and effici ency, Non Multimedia Files methods of hidden infor mation are hid den data in the (Disk Sp ace Network Packets, Software an d Circuitry), in this pap er explained, why the researcher used P-E-File as the cov er file and it classifi er to the non m ultimedia file , finally it discussed about Characterist ics of Executable Files , Adva ntage of PE-F ile an d Stre ngth and We aknes s Factors of Steganography. ACKNOWLEDGEMENT This research wa s fully supported by “King Saud University”, Riyadh, Saudi Arabia. The author woul d like to acknowledg e all workers inv olved in this project whom had given their support in many wa ys, aslo he would like to t hank in advance Dr. Musaed AL-J rrah, Dr. Abdullah Al sbail, Dr. Abdull ah Alsbait. Dr.Khali d Alhazmi, Dr.Abdu llah Al-A fnan, Dr.Ibrahim Al - Dubaian and a ll the staff in king Saud Universit y especially in Appl ied Medical Science In “A l-Majmah” for thier unlimited support, without thier notes and suggestion this research would not be appear. REFERE NCES [1] A.A.Zaidan, B.B.Za idan, Fazidah Othman , “New Techn ique of Hidden Data in PE-File with in Unused Area One”, International Journal of Computer and Electrical Engineering (IJ CEE), Vol.1, N o.5, ISSN: 1793-8 198, p. p 669-678. [2] A.A.Zaidan, B.B.Za idan, Anas Majeed, "High Se curing Cover-File of Hidden Data Us ing S tat isti cal T echn ique a nd AES Encr ypti on Algorithm", World Academy of Science Engineering an d Technology (WASET ), Vol.54, ISS N: 2070-3724, P.P 46 8-479. [3] A.A.Zaidan, B.B.Zaidan , “Novel Approach for High Secure Data Hidden in MPEG V ideo Using Public Key In frastructure”, Internationa l Journal of Comput er and Network Se curity, 20 09, Vol.1 , No.1, ISSN: 19 85-1553, P.P 71 -76. [4] Mohamed A. Ahmed, Miss La iha Mat Kiah, B.B.Zaidan , A.A.Zaidan , "A Novel Embedding Method to Increase Capacity o f LSB A udi o Ste gan ogra phy Usin g No ise Gate So ftwa re L ogi c Algorithm", Journal of Applied Scie nces, Vol.10, Issue 1, ISSN: 1812- 5654, 2010, P.P 59- 64 [5] A.W.Naji, A.A.Zaidan, B. B.Zaidan, Shihab A, Othman O. Khalifa, “ Novel Approac h of Hidden Data in the (Unused Area 2 withi n EXE File) Usin g Computation Between Crypto graphy and Steganography ”, International Journal of Computer Science and Network Security (IJCSNS) , Vol.9, No.5 , IS SN : 1738- 7906, pp. 294-300 . [6] Anas Majed Hamid, Miss Laiha Mat Kiah, Hayan .T. Madhloom , B.B Zaidan, A.A Zaidan,” Novel Approach for High Secu re and High Rate Data Hidden in th e Image Using Image Text ure Analysis”, International Journal of Engineering and Technology ( IJET) , Published by: Engg Journals Pu blications, ISSN :0975-4042, Vol.1,NO.2,P.P 63- 69. [7] A.A.Zaidan, F azidah. Ot hman, B.B.Zaida n, R.Z.Raji, Ahmed.K.Hasan , and A.W .Naji," S ecuring Co ver-File without Lim itatio n of Hidden Data Size Using Comput ation between Cryptog raphy and Steganography " , World Cong ress on Engineering 2009 (WCE), Th e 2009 International Conferen ce of Computer Science and Enginee ring, Proceedings of the Internat ional Multi Conferen ce of Engineers and Computer Scie ntists 2009, ISBN : 978-988- 17012-5-1, V ol.I, p.p259- 265. [8] A.A.Zaidan, A.W. Naji , Shihab A. Hameed, F azidah Othm an and B.B. Zaidan, " Approved Undetecta ble-Antivirus Steganog raphy for Multimedia Information in PE-File " ,International C onference on IACSIT Spring Confer ence (IACSIT-SC09) , Advanced M anagement Science (AMS), Liste d in IEEE Xplore and be index ed by both EI (Compe ndex) and ISI Thomso n (ISTP), Session 9, P.P 425-429. [9] A.A.Za idan, B.B.Zaidan, M.M. Abdulrazzaq, R.Z. Raji, and S.M.Mohammed," Im plementation Stag e for High Securing Cover- File of Hi dden Data Using Compu tation Betwee n Cryptography and Steganography", Inte rnational Conference on Computer Engi neering and Applications (IC CEA09), Teleco m Technology an d Applications (TTA), indexi ng by Nielsen, Thomso n ISI (ISTP), IACSIT Datab ase, British Li brary and EI Compendex, Vol. 19, Session 6, p.p 482-489. [10] A.W. Na ji, A.A.Zaidan, B.B. Zaidan, Ibrahim A.S.Muhamadi, “New Approach of Hidden Data in the portable Executable File without C h a n g e t h e S i z e o f C a r r i e r F i l e U s i n g D i s t o r t i o n T e c h n i q u e s ” , Proceed ing of Wo rld Academy of Science En gin eering and Technolo gy (WASET),Vo l.56, ISSN: 2070-3724, P. P 493-497. [11] A.W. Naj i, A.A.Zaidan, B.B.Zaidan, I brahim A.S.Muhamad i, “Novel Approach for Cover File of Hidden Data in the Unused Area Two with in EXE Fi le U sing Dist orti on Te chn ique s and Advan ce Encryp tion Standard. ”, Proceeding o f World Academy of Sci ence Engineeri ng and Technology (WA SET),Vol.56, ISSN:2070-3724, P.P 498-502. [12] M. Abomhara, Omar Z akaria, Othman O. Khalifa , A.A .Zaidan, B.B.Zaid an, “Enhancing Sel ective Encr yption for H.264/AVC Usi ng Advance Encry ption Standard “, Internationa l Journal of Computer and Electrica l Engineering (IJ CEE), ISSN: 1793- 8198,Vol.2 , NO .2, April 2010, Singapore .. [13] Md. Rafiqul Islam, A.W. Naji, A.A.Za idan, B.B.Zaidan “ New System for Se cu re Co ver File of Hi dden Dat a in the Ima ge P age w ith in Executable File Using Statistical Stegan ography Techniques”, International Journal of Computer Sc ience and Inf ormation Secu rity (IJCSIS ), ISSN: 1 947-5500, P. P 273-279, Vol.7 , NO.1, J anuary 20 10, USA.. [14] Ham id.A.Jalab, A.A Zaidan, B.B Zaidan , “New Design for Inform ation H iding wi th in Steg anogra phy Usi ng Distor tion Techniques”, Internatio nal Journal of Engineering and Technology (IJET)), Vol 2, No. 1, ISSN: 1793-823 6, Feb (2010), Singa pore. [15] Hamd an. Alanazi, Ha mid.A.Jalab, A.A.Zaid an, B.B. Zaidan, “New Frame Work of Hidde n Data with in Non Multime dia File”, International Jour nal of Computer and Network Security, 2010, Vol.2, No.1, ISSN: 1985-1553, P.P 46-54,30 Janua ry, Vienna, Austria. [16] A.A.Zaidan, B.B.Za idan, Hamid.A.Jalab, “ A New System for Hiding Data within (Unused Area Two + Image Page) of Portable Executable File using Statistical Technique a nd Advance Encryption Standared “, International Journal of Computer The ory and Engineering (IJCT E), 2010, VOL 2, NO 2, ISSN:1793-8201, Singapore. [17] Alaa Taqa, A.A Zaidan, B.B Zaidan ,“New Framework for High Secure Data Hidden in the MPEG Using AES Encryption Algorithm”, Int ernational Journal of Compute r and Electrical Engineering (IJCEE ),Vol.1 ,No.5, ISSN: 1793- 8163, p.p.566-571 , December (2009). Singapore. [18] B.B Zaidan , A.A Zai dan ,Alaa Taqa , Fazida h Othman ,“ Stego- Image Vs Ste go-Analysis System”, Interna tional Journal of JOURNAL OF COMPUTING , VOLUME 2, ISSUE 3, MARCH 2010, ISSN 215 1-9617 HTTPS:// SITES.GOOGLE.CO M/SITE/JOURNALOFCO MPUTING/ 151 Computer a nd Electrical Engineering ( IJCEE),Vol.1 ,No.5 , ISSN: 1793-8163, pp.572 -578 , December (2009), Singa pore. [19] A.W. Naji, Shihab A. Hameed, B.B.Zaidan, Waj di F. Al-Khateeb, Othman O. Khalif a, A.A.Zaid an and Teddy S. Gunawan, “ Novel Framework for Hidde n Data in the Image Page within Executable File Using Com putation between Advance Encrypti on Standared and Distortion Techni ques”, International Journa l of Computer Science and Information S ecurity (IJCSIS), Vol. 3, No 1 ISS N: 1947-5500, P.P 73-78,3 Aug 2009, USA. [20] Hamid .A.Jal ab, A.A Z aidan and B.B Zaid an,” Frame S elect ed Approach for Hiding D ata within MPEG Video Using Bit Plane Complexity Se gmentation”, Journal of Com puting (JOC), Vol.1, Issue 1, ISSN: 2151 -9617, P.P 108-113, December 2009, Lille , France. [21] Mahmoud Elnajjar, A.A Zaidan, B.B Zaidan, M ohamed Elhadi M.Sharif and Hamdan.O.Alanazi ,” Optimization Digita l Image Watermarking Tec hnique for Patent Protection”, Journal of Computing (JOC ), Vol.2, Issue 2, ISSN: 2151-9 617, P.P 142-148 February 2010, Li lle, France. Hamdan A l- Anazi : has o btained his bachelor dg ree from “King Suad University”, Riyadh, Saudi Arabia. He worked as a lecturer at Health College in the Mi nistry of Health in Saudi Arabia, t hen he worked as a lecturer at King Saud University in the comput er department . Currently he is Master candi date at faculty of Computer Sci ence & Information Tech nology at Uni versity of Malaya in Kuala Lumpur, Malaysi a. His research interest on Informatio n Security, cryptography, steganog raphy and digital watermarking, He has co ntributed to many pap ers some of them still under reviewer. Aos A laa Z aidan : He obtained his 1st Clas s Bachelor degree in Computer En gineer ing from un iversity o f Technolo gy / Bagh dad follow ed by maste r in data communica tion and comp uter ne twork from Univ ersity of Malaya. He led or membe r for many funded research projects a nd He has published m ore than 55 pape rs at various inter national an d national con ferences an d journals , His interest ar ea are Informati on security (Stegan ograph y and Digital watermarking), Ne twork Security (Encrypti on Methods) , Image Proc essing (Ski n Detector), Patter n Recognition , Mac hine Learnin g (Neural Network , Fuzzy Logic and Ba yesian) Method s and Text Mining and Vide o Mining. .Currently, he is PhD Ca ndidate on the Depar tment of Electrical & Com puter Engineering / F aculty of Engineering / Mu ltimedia Univers ity / Cyberja ya, Malaysia. He is members IAENG, CSTA, WASET, and IACSIT. He is reviewer in the (IJSIS, IJCSN, IJCSE and IJCIIS). Bilal Bahaa Zaidan: He obtained his bachelor de gree in Mathemat ics and Computer Ap plication fro m Saddam University/B aghdad follo wed by master in data communica tion and comp uter ne twork from Univ ersity of Malaya. He led or membe r for many funded research projects a nd He has published m ore than 55 pape rs at various inter national an d national con ferences an d journals , His interest ar ea are Informati on security (Stegan ograph y and Digital watermarking), Ne twork Security (Encrypti on Methods) , Image Proc essing (Ski n Detector), Patter n Recognition , Mac hine Learnin g (Neural Network , Fuzzy Logic and Ba yesian) Method s and Text Mining and Vide o Mining. .Currently, he is PhD Ca ndidate on the Depar tment of Electrical & Comput er Engineeri ng / Faculty of Engineering / Mu ltimedia Univers ity / Cyberja ya, Malaysia. He is members IAENG, CSTA, WASET, and IACSIT. He is reviewer in the (IJSIS, IJCSN, IJCSE and IJCIIS). Dr.Hamid.A.Jalab : Received his B.Sc degree from Univ ersity of Technol ogy, Baghda d, Iraq. M Sc & Ph.D degrees from Odes sa Polytechnic Natio nal State Univers ity 1987 an d 1991, respect ively. Presently, Visi ting Senior Lecturer of Co mputer S ystem and Tec hnolog y, Facult y of Compute r Science and Information Technology, Uni versity of Malay a, Malaysia. various int ernational and national conferences a nd journals , His interest ar ea are Inform ation security (Steganograph y and Digital watermarkin g), Network Security (Encryption Met hods) , Image Proce ssing (Skin Detecto r), Pattern Recogn ition , Machine Le arning (Neural Network, Fuzzy Logic and Bayesian) Me thods and Text Mining a nd Video Mining. Zaidoon Kh. AL-Ani: H as gained his bachelor De gree in compute r science f rom Univers ity of Bagh dad in 2003 . Presently, he is cond ucting his maste r degree in Inform ation and Communication Te chnolog y at International Isla mic Unive rsity Malaysi a. The field of intere st is stegano graphy. Projects have been done which are t itled as “Data securit y using h iding data” and Evaluation o f Steganography for Arabic text”.