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21.03.2018 – Steganography programs that hide information merely by manipulating the order of colors in the palette cause structural changes, as well. Why work for somebody else when you can become rich within 68 months! NG r racsian rsian rcan wv.
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1. 6PPs the Paris Psalter, ed.
2. 10 Morsbach Studien zur Eng.http://softik.org/norton-internet-security-2008-up-to-3-users/ http://softik.org/turbotax-deluxe-federal-e-file-2012-for-pc/Harris, Yale Studies, vol. B drepen pp.
3. 6 A conservative or malicious warden might actually modify all messages in an attempt to disrupt any covert channel so that Alice and Bob would need to use a very robust steganography method Chandramouli ; Fridrich et al. The most common steganography method in audio and image files employs some type of least significant bit substitution or overwriting. http://softik.org/buy-huawei-p8q77-m2-racing/ http://softik.org/alcatel-one-touch-view-837/Their meaning can however always be ascertained by referring to their components, and where the abbreviation Mdf is inserted the reader will understand that examples of words so compounded, or of the components, or of both, will be found in Birch’s Cartularium Saxonicum, or in Earle’s Land Charters, and that references to those examples are given in Middendorff’s Altenglisches Flurnamenbuch. A vast mass of valuable information as to the etymology, meaning and occurrence of Old English words is contained in that Dictionary, but is to a very large extent overlooked because it is to be found under the head of words which are now obsolete, so that unless one happens to know what was the last form which they had in Middle English, one does not know how to get at it.
4. 1 Long is split up aswhile long y is approximated with.Dictionary net 4 8 4518 portableFor example, you can use the case-insensitive string comparers provided by the StringComparer class to create dictionaries with case-insensitive string keys.
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6. 7 The keys are compared by using a specified comparer.
7. 4 Computes the average of a sequence of nullable Single values that are obtained by invoking a transform function on each element of the input sequence. Sprache, Aachen und Leipzig,
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This version is updated with current information and links. Steganography is the art of covered or hidden writing. The purpose of steganography is covert communication-to hide the existence of a message from a third party.
This paper is intended as a high-level technical introduction to steganography for those unfamiliar with the field. It is directed at forensic computer examiners who need a practical understanding of steganography without delving into the mathematics, although references are provided to some of the ongoing research for the person who needs or wants additional detail.
Although this paper provides a historical context for steganography, the emphasis is on digital applications, focusing on hiding information in online image or audio files. Examples of software tools that employ steganography to hide data inside of other files as well as software to detect such hidden files will also be presented.
The purpose of steganography is covert communication to hide a message from a third party. This differs from cryptography, the art of secret writing, which is intended to make a message unreadable by a third party but does not hide the existence of the secret communication.
Although steganography is separate dictionary distinct from cryptography, there are many analogies between the two, and some authors categorize steganography as a form of cryptography since hidden communication is a form of secret writing Bauer Nevertheless, this paper will treat steganography as a separate field.
Although the term steganography was only coined at the end of the 15th century, the use of steganography dates back several millennia. In ancient times, messages were hidden on the back of wax writing tables, written on the stomachs of rabbits, or tattooed on the scalp of slaves.
Invisible ink has been in use for centuries-for fun by children and students and for serious espionage by spies portable terrorists. Microdots and microfilm, a staple of war and spy movies, came about after the invention of photography Arnold et al.
Steganography hides the covert message but not the fact that two parties are communicating with each other. The steganography process generally involves placing a hidden message in some transport medium, called the carrier.
The secret message is embedded in the carrier to form the steganography medium. Figure 1 shows a common taxonomy of steganographic techniques Arnold et al. Technical steganography uses scientific methods to hide a message, such as the use of invisible ink or microdots and other size-reduction methods.
Linguistic steganography hides the message in the carrier in some nonobvious ways and is further categorized as semagrams or open codes. Semagrams hide information by the use of symbols or signs. A visual semagram uses innocent-looking or everyday physical objects to convey a message, such as doodles or the positioning of items on a desk or Website.
A text net hides a message by modifying the appearance of the carrier text, such as subtle changes in font size or type, adding extra spaces, or different flourishes in letters or handwritten text.
Open codes hide a message in a legitimate carrier message in ways that are not obvious to an unsuspecting observer. The carrier message is sometimes called the overt communication whereas the hidden message is the covert communication.
This category is subdivided into jargon codes and covered ciphers. Jargon code, as the name suggests, uses language that is understood by a group of people but is meaningless to others.
Jargon codes include warchalking symbols used to indicate the presence and type of wireless network signal [Warchalking ]underground terminology, or an innocent conversation that conveys special meaning because of facts known only to the speakers.
A subset of jargon codes is cue codes, where certain prearranged phrases convey meaning. Covered or concealment ciphers hide a message openly in the carrier medium so that it can be recovered by anyone who knows the secret for how it was concealed.
A grille cipher employs a template that is used to cover the carrier message. The words that appear in the openings of the template are the hidden message. A null cipher hides the message according to some prearranged set of rules, such as “read every fifth word” or “look at the third character in every word.
As an increasing amount of data is stored on computers and transmitted over networks, it is not surprising that steganography has entered the digital age. On computers and networks, steganography applications allow for someone to hide any type of binary file in any other binary file, although image and audio files are today’s most common carriers.
Steganography provides some very useful and commercially important functions in the digital world, most notably digital watermarking. An artist, for example, could post original artwork on a Website.
Although conceptually similar to steganography, digital watermarking usually has different technical goals. Generally only a small amount of repetitive information is inserted into the carrier, it is not necessary to hide the watermarking information, and it is useful for the watermark to be able to be removed while maintaining the integrity of the carrier.
Steganography has a number of nefarious applications; most notably hiding records of illegal activity, financial fraud, industrial espionage, and communication among members of criminal or terrorist organizations Hosmer and Hyde Historically, null ciphers are a way to hide a message in another without the use of a complicated algorithm.
One of the simplest null ciphers is shown in the classic examples below:. Reading the first character of every word in the first message or the second character of every word in the second message will yield the following hidden text:.
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This message looks like typical spam, which is generally ignored and discarded. This message was created at spam mimic, a Website that converts a short text message into a text block that looks like spam using a grammar-based mimicry idea first proposed by Peter Wayner spam mimic ; Wayner The reader will learn nothing by looking at the word spacing or misspellings in the message; the zeros and ones are encoded by the choice of the words.
The hidden message in the portable carrier above is:. Special tools or skills to hide messages in digital files using variances of a null cipher are not necessary.
An image or text block can be hidden under another image in a PowerPoint file, for example. Messages can be hidden in the properties of a Word file. Messages 4518 be hidden in comments in Web pages or in other formatting vagaries that are ignored by browsers Artz Text can be hidden as line art in a document by putting the text in the same color as the background and placing another drawing in the foreground.
The recipient could retrieve the hidden text by changing its color Seward These are all decidedly low-tech mechanisms, but they can dictionary very effective. Many common digital steganography techniques employ graphical images or audio files as the carrier medium.
It is instructive, then, to review image and audio encoding before discussing how steganography and steganalysis works with these carriers. Figure 2 shows the RGB color cube, a common means with which to represent a given color by the relative intensity of its three component colors-red, green, and blue-each with their own axis moreCrayons The absence of all colors yields black, shown as the intersection of the zero point of the three-color axes.
The mixture of percent red, percent blue, and the absence of green form magenta; cyan is percent green and percent blue without any red; and percent green and percent red with no blue net to form portable. White is the presence of all three colors.
Figure 3 shows the RGB intensity levels of some random color. Each RGB component is specified by a single byte, so that the values for each color intensity can vary from This particular shade is denoted by a red level of hex BFa green level of 29 hex 1Dand a blue level of hex One pix of magenta, then, would be encoded using 24 bits, as 0xBF1D This bit encoding scheme supports 16, 2 24 unique colors Curran and Bailey ; Johnson and Jajodia A.
Most digital image applications today support bit true color, where each picture element pixel is encoded in 24 bits, comprising the three RGB bytes as described above.
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But at some prearranged time during the week, a version of the photograph is posted that contains a hidden message. To avoid empty crossreferences, a few entries, clearly identified, were restored from the first edition. These are all decidedly low-tech mechanisms, but they can be very effective. RPs der RegiusPsalter, ed. Analog signals need to be sampled at a rate of twice the highest frequency component of the signal so that the original can be correctly reproduced from the samples alone.
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Invokes a transform function on each element of a sequence and returns the minimum nullable Int64 value. Invokes a transform function on each element of a sequence and returns the minimum nullable Single value.
Invokes a transform function on each element of a sequence and returns the minimum Single value. Invokes a transform function on each element of a generic sequence and returns the minimum resulting value.
Filters the elements of an IEnumerable based on a specified type. Sorts the elements of a sequence in ascending order according to a key. Sorts the elements of a sequence in ascending order by using a specified comparer.
Sorts the elements of a sequence in descending order according to a key. Sorts the elements of a sequence in descending order by using a specified comparer. Adds a value to the beginning of the sequence.
Inverts the order of the elements in a sequence. Projects each element of a sequence into a new form. Projects each element of a sequence into a new form by incorporating the element’s index.
The index of each source element is used in the projected form of that element. The index of each source element is used in the intermediate projected form of that element. Determines whether two sequences are equal by comparing the elements by using the default equality comparer for their type.
Returns the only element of a sequence, and throws an exception if there is not exactly one element in the sequence. Returns the only element of a sequence that satisfies a specified condition, and throws an exception if more than one such element exists.
Returns the only element of a sequence, or a default value if the sequence is empty; this method throws an exception if there is more than one element in the sequence. Returns the only element of a sequence that satisfies a specified condition or a default value if no such element exists; this method throws an exception if more than one element satisfies the condition.
Bypasses a specified number of elements in a sequence and then returns the remaining elements. Bypasses elements in a sequence as long as a specified condition is true and then returns the remaining elements.
The element’s index is used in the logic of the predicate function. Computes the sum of the sequence of Decimal values that are obtained by invoking a transform function on each element of the input sequence.
Computes the sum of the sequence of Double values that are obtained by invoking a transform function on each element of the input sequence. Computes the sum of the sequence of Int32 values that are obtained by invoking a transform function on each element of the input sequence.
Computes the sum of the sequence of Int64 values that are obtained by invoking a transform function on each element of the input sequence. Computes the sum of the sequence of nullable Decimal values that are obtained by invoking a transform function on each element of the input sequence.
Computes the sum of the sequence of nullable Double values that are obtained by invoking a transform function on each element of the input sequence. Computes the sum of the sequence of nullable Int32 values that are obtained by invoking a transform function on each element of the input sequence.
Computes the sum of the sequence of nullable Int64 values that are obtained by invoking a transform function on each element of the input sequence. Computes the sum of the sequence of nullable Single values that are obtained by invoking a transform function on each element of the input sequence.
Computes the sum of the sequence of Single values that are obtained by invoking a transform function on each element of the input sequence. Returns a specified number of contiguous elements from the start of a sequence.
Returns elements from a sequence as long as a specified condition is true. Produces the set union of two sequences by using the default equality comparer. Filters a sequence of values based on a predicate.
Each element’s index is used in the logic of the predicate function. Applies a specified function to the corresponding elements of two sequences, producing a sequence of the results.
You can browse through the source code online, download the reference for offline viewing, and step through the sources including patches and updates during debugging; see instructions.
Each addition to the dictionary consists of a value and its associated key. The speed of retrieval depends on the quality of the hashing algorithm of the type specified for TKey.
A key cannot be null , but a value can be, if the value type TValue is a reference type. If type TKey implements the System. For example, you can use the case-insensitive string comparers provided by the StringComparer class to create dictionaries with case-insensitive string keys.
The order in which the items are returned is undefined. The foreach statement is a wrapper around the enumerator, which allows only reading from the collection, not writing to it. Because keys can be inherited and their behavior changed, their absolute uniqueness cannot be guaranteed by comparisons using the Equals method.
The example demonstrates that the Add method throws an ArgumentException when attempting to add a duplicate key. The example uses the Item property the indexer in C to retrieve values, demonstrating that a KeyNotFoundException is thrown when a requested key is not present, and showing that the value associated with a key can be replaced.
The example shows how to use the TryGetValue method as a more efficient way to retrieve values if a program often must try key values that are not in the dictionary, and it shows how to use the ContainsKey method to test whether a key exists before calling the Add method.
The example shows how to enumerate the keys and values in the dictionary and how to enumerate the keys and values alone using the Keys property and the Values property.
Finally, the example demonstrates the Remove method. Even so, enumerating through a collection is intrinsically not a thread-safe procedure. In the rare case where an enumeration contends with write accesses, the collection must be locked during the entire enumeration.
The content you requested has been removed. The telephone network converts each voice sample to an eight-bit value whereas music applications generally use bit values , Fries and Fries ; Rey Analog signals need to be sampled at a rate of twice the highest frequency component of the signal so that the original can be correctly reproduced from the samples alone.
In the telephone network, the human voice is carried in a frequency band Hz although only about Hz is actually used to carry voice ; therefore, voice is sampled 8, times per second an 8 kHz sampling rate.
Music audio applications assume the full spectrum of the human ear and generally use a The bit rate of uncompressed music can be easily calculated from the sampling rate This would suggest that a one-minute audio file uncompressed would occupy Audio files are, in fact, made smaller by using a variety of compression techniques.
One obvious method is to reduce the number of channels to one or to reduce the sampling rate, in some cases as low as 11 kHz. Other codecs use proprietary compression schemes. All of these solutions reduce the quality of the sound.
There are many ways in which messages can be hidden in digital media. Digital forensics examiners are familiar with data that remains in file slack or unallocated space as the remnants of previous files, and programs can be written to access slack and unallocated space directly.
Small amounts of data can also be hidden in the unused portion of file headers Curran and Bailey Information can also be hidden on a hard drive in a secret partition.
A hidden partition will not be seen under normal circumstances, although disk configuration and other tools might allow complete access to the hidden partition Johnson et al.
This theory has been implemented in a steganographic ext2fs file system for Linux. A hidden file system is particularly interesting because it protects the user from being inextricably tied to certain information on their hard drive.
This form of plausible deniability allows a user to claim to not be in possession of certain information or to claim that certain events never occurred. Under this system users can hide the number of files on the drive, guarantee the secrecy of the files’ contents, and not disrupt nonhidden files by the removal of the steganography file driver Anderson et al.
Another digital carrier can be the network protocols. Covert Transmission Control Protocol by Craig Rowland, for example, forms covert communications channels using the Identification field in Internet Protocol packets or the sequence number field in Transmission Control Protocol segments Johnson et al.
There are several characteristics of sound that can be altered in ways that are indiscernible to human senses, and these slight alterations, such as tiny shifts in phase angle, speech cadence, and frequency, can transport hidden information Curran and Bailey Nevertheless, image and audio files remain the easiest and most common carrier media on the Internet because of the plethora of potential carrier files already in existence, the ability to create an infinite number of new carrier files, and the easy access to steganography software that will operate on these carriers.
For that reason, the manuscript focus will return to image and audio files. The most common steganography method in audio and image files employs some type of least significant bit substitution or overwriting.
The least significant bit term comes from the numeric significance of the bits in a byte. The high-order or most significant bit is the one with the highest arithmetic value i.
As a simple example of least significant bit substitution, imagine “hiding” the character ‘G’ across the following eight bytes of a carrier file the least significant bits are underlined:.
These eight bits can be “written” to the least significant bit of each of the eight carrier bytes as follows:. In the sample above, only half of the least significant bits were actually changed shown above in italics.
This makes some sense when one set of zeros and ones are being substituted with another set of zeros and ones. By overwriting the least significant bit, the numeric value of the byte changes very little and is least likely to be detected by the human eye or ear.
Least significant bit substitution is a simple, albeit common, technique for steganography. Its use, however, is not necessarily as simplistic as the method sounds.
Only the most naive steganography software would merely overwrite every least significant bit with hidden data. Almost all use some sort of means to randomize the actual bits in the carrier file that are modified.
This is one of the factors that makes steganography detection so difficult. One other way to hide information in a paletted image is to alter the order of the colors in the palette or use least significant bit encoding on the palette colors rather than on the image data.
These methods are potentially weak, however. Many graphics software tools order the palette colors by frequency, luminance, or other parameter, and a randomly ordered palette stands out under statistical analysis Fridrich and Du Newer, more complex steganography methods continue to emerge.
Spread-spectrum steganography methods are analogous to spread-spectrum radio transmissions developed in World War II and commonly used in data communications systems today where the “energy” of the signal is spread across a wide-frequency spectrum rather than focused on a single frequency, in an effort to make detection and jamming of the signal harder.
Spread-spectrum steganography has the same function-avoid detection. These methods take advantage of the fact that little distortions to image and sound files are least detectable in the high-energy portions of the carrier i.
There are more than steganography programs currently available, ranging from free downloads to commercial products. The first example employs Gif-It-Up, a Nelsonsoft program that hides information in GIF files using least significant bit substitution and includes an encryption option.
The original carrier is , bytes in length and uses unique colors, whereas the steganography file is , bytes in length and uses unique colors. The file size is larger in the steganography file because of a color extension option used to minimize distortion in the steganography image.
If color extension is not employed, the file size differences are slightly less noticeable. Figure 7 shows the carrier file’s palettes before and after message insertion.
Like all least significant bit insertion programs that act on eight-bit color images, Gif-It-Up modifies the color palette and generally ends up with many duplicate color pairs. The Blowfish crypto algorithm is used for least significant bit randomization and encryption Johnson and Jajodia B.
Figure 8 shows an example JPEG file with the airport map embedded in it. The original carrier file is , bytes in size and contains , unique colors. The steganography file is , bytes in size and contains , unique colors.
There is no color palette to look at because JPEG uses bit color coding and discrete cosine transforms. S-Tools uses least significant bit substitution in files that employ lossless compression, such as eight- or bit color and pulse code modulation.
Figure 9 shows a signal level comparison between a WAV carrier file before and after the airport map was hidden. Although the relatively small size of the figure makes it hard to see details, some differences are noticeable at the beginning and end of the audio sample i.
Some steganography tools have built-in intelligence to avoid the low-intensity portions of the signal. Audio files are well suited to information hiding because they are usually relatively large, making it difficult to find small hidden items.
They are free, easy to use, and perform their tasks well. Although the discussion above has focused only on image and audio files, steganography media are not limited to these types of files.
Other file types also have characteristics that can be exploited for information hiding. Developed by Rakan El-Khalil, Hydan takes advantage of redundancy in the i instruction set and inserts hidden information by defining sets of functionally equivalent instructions, conceptually like a grammar-based mimicry e.
The program can hide approximately one message byte in every instruction bytes and maintains the original size of the application file. Blowfish encryption can also be employed El-Khalil The Prisoner’s Problem Simmons is often used to describe steganography, although it was originally introduced to describe a cryptography scenario.
The problem involves two prisoners, Alice and Bob, who are locked in separate prison cells and wish to communicate some secret plan to each other. Alice and Bob are allowed to exchange messages with each other, but William, the warden, can read all of the messages.
Alice and Bob know that William will terminate the communications if he discovers the secret channel Chandramouli ; Fridrich et al. William can act in either a passive or active mode.
In the passive warden model, William examines each message and determines whether to forward the message or not based on his ability to detect a hidden message.
In the active warden model, William can modify messages if he wishes. A conservative or malicious warden might actually modify all messages in an attempt to disrupt any covert channel so that Alice and Bob would need to use a very robust steganography method Chandramouli ; Fridrich et al.
The difficulty of the warden’s task will depend largely on the complexity of the steganography algorithm and the amount of William’s prior knowledge Chandramouli ; Fridrich et al. In a pure steganography model, William knows nothing about the steganography method employed by Alice and Bob.
This is a poor assumption on Alice and Bob’s part since security through obscurity rarely works and is particularly disastrous when applied to cryptography. This is, however, often the model of the digital forensics analyst searching a Website or hard drive for the possible use of steganography.
This is consistent with the assumption that a user of cryptography should make, per Kerckhoff’s Principle i. This may also be too strong of an assumption for practice, however, because complete information would include access to the carrier file source.
Steganalysis, the detection of steganography by a third party, is a relatively young research discipline with few articles appearing before the lates. The art and science of steganalysis is intended to detect or estimate hidden information based on observing some data transfer and making no assumptions about the steganography algorithm Chandramouli Detection of hidden data may not be sufficient.
Steganalysis techniques can be classified in a similar way as cryptanalysis methods, largely based on how much prior information is known Curran and Bailey ; Johnson and Jajodia B. A known message and steganography algorithm are used to create steganography media for future analysis and comparison.
The carrier and steganography medium, as well as the steganography algorithm, are known. Steganography methods for digital media can be broadly classified as operating in the image domain or transform domain.
Image domain tools hide the message in the carrier by some sort of bit-by-bit manipulation, such as least significant bit insertion. Transform domain tools manipulate the steganography algorithm and the actual transformations employed in hiding the information, such as the discrete cosine transforms coefficients in JPEG images Johnson and Jajodia B.
It follows, then, that steganalysis broadly follows the way in which the steganography algorithm works. One simple approach is to visually inspect the carrier and steganography media.
Many simple steganography tools work in the image domain and choose message bits in the carrier independently of the content of the carrier. Although it is easier to hide the message in the area of brighter color or louder sound, the program may not seek those areas out.
Thus, visual inspection may be sufficient to cast suspicion on a steganography medium Wayner A second approach is to look for structural oddities that suggest manipulation. Least significant bit insertion in a palette-based image often causes a large number of duplicate colors, where identical or nearly identical colors appear twice in the palette and differ only in the least significant bit.
Steganography programs that hide information merely by manipulating the order of colors in the palette cause structural changes, as well. The structural changes often create a signature of the steganography algorithm that was employed Jackson et al.
Steganographic techniques generally alter the statistics of the carrier and, obviously, longer hidden messages will alter the carrier more than shorter ones Farid ; Fridrich and Du ; Fridrich and Goljan ; Ozer et al.
Statistical analysis is commonly employed to detect hidden messages, particularly when the analyst is working in the blind Jackson et al. There is a large body of work in the area of statistical steganalysis.
Statistical analysis of image and audio files can show whether the statistical properties of the files deviate from the expected norm Farid ; Ozer et al. Although these measures can yield a prediction as to whether the contents have been modified or seem suspicious, they are not definitive Wayner Statistical steganalysis is made harder because some steganography algorithms take pains to preserve the carrier file’s first-order statistics to avoid just this type of detection.
Encrypting the hidden message also makes detection harder because encrypted data generally has a high degree of randomness, and ones and zeros appear with equal likelihood Farid ; Provos and Honeyman Recovery of the hidden message adds another layer of complexity compared to merely detecting the presence of a hidden message.
Recovering the message requires knowledge or an estimate of the message length and, possibly, an encryption key and knowledge of the crypto algorithm Fridrich et al. Carrier file type-specific algorithms can make the analysis more straightforward.
JPEG, in particular, has received a lot of research attention because of the way in which different algorithms operate on this type of file. JPEG is a poor carrier medium when using simple least significant bit insertion because the modification to the file caused by JPEG compression eases the task of detecting the hidden information Fridrich and Du There are several algorithms that hide information in JPEG files, and all work differently.
More advanced statistical tests using higher-order statistics, linear analysis, Markov random fields, wavelet statistics, and more on image and audio files have been described Farid ; Farid and Lyu ; Fridrich and Goljan ; Ozer et al.
Detailed discussion is beyond the scope of this paper, but the results of this research can be seen in some steganography detection tools. Most steganalysis today is signature-based, similar to antivirus and intrusion detection systems.
Anomaly-based steganalysis systems are just beginning to emerge. Although the former systems are accurate and robust, the latter will be more flexible and better able to quickly respond to new steganography techniques.
One form of so-called “blind steganography detection” distinguishes between clean and steganography images using statistics based on wavelet decomposition, or the examination of space, orientation, and scale across subsets of the larger image Farid ; Jackson et al.
This type of statistical steganalysis is not limited to image and audio files. The Hydan program retains the size of the original carrier but, by using sets of “functionally equivalent” instructions, employs some instructions that are not commonly used.
This opens Hydan to detection when examining the statistical distribution of a program’s instructions. Future versions of Hydan will maintain the integrity of the statistical profile of the original application to defend against this analysis El-Khalil The law enforcement community does not always have the luxury of knowing when and where steganography has been used or the algorithm that has been employed.
Generic tools that can detect and classify steganography are where research is still in its infancy but are already becoming available in software tools, some of which are described in the next section McCullagh This article has a stated focus on the practicing computer forensics examiner rather than the researcher.
This section, then, will show some examples of currently available software that can detect the presence of steganography programs, detect suspect carrier files, and disrupt steganographically hidden messages.
This is by no means a survey of all available tools, but an example of available capabilities. The detection of steganography software on a suspect computer is important to the subsequent forensic analysis.
As the research shows, many steganography detection programs work best when there are clues as to the type of steganography that was employed in the first place. Finding steganography software on a computer would give rise to the suspicion that there are actually steganography files with hidden messages on the suspect computer.
Furthermore, the type of steganography software found will directly impact any subsequent steganalysis e. Gargoyle employs a proprietary data set or hash set of all of the files in the known steganography software distributions, comparing them to the hashes of the files subject to search.
Figure 10 shows the output when Gargoyle was aimed at a directory where steganography programs are stored. Gargoyle data sets can also be used to detect the presence of cryptography, instant messaging, key logging, Trojan horse, password cracking, and other nefarious software.
In general, these data sets are designed to exclude hashes of known “good” files from search indexes during the computer forensic analysis. Gargoyle can also import these hash sets.
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