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A third less widely used technique is called speci cation-based detection We now discuss each of these techniques in detail The misuse detection technique involves analyzing the collected data for speci c behavior patterns known to be consistent with speci c attacks These behavior patterns are called signatures For example, a UDP packet destined to port 0 can crash some machines [79] The signature of a ping-of-death attack is a very large ping packet; the signature of an RPC locator attack is a packet intended for port 135 that contains a command that the system is not expecting; the signature of a Bubonic attack is made from various values, such as a TTL of 255, a TOS eld value of 0 C9, exactly 20 byte payload in the IP datagram, and the fragment ID value with consistent increments of 256 [79] The misuse detection technique is being used widely today by commercial systems because it allows for very precise detection of attacks, thereby resulting in low false alarm rates When a signature for an attack has been identi ed (typically a bit-by-bit precise speci cation of an attack packet), it is straightforward to detect the attack by comparing a packet against the precise attack signature The problem with misuse detection intrusion detection techniques is that these techniques can only detect previously known attacks with wellde ned patterns of malicious behavior Novel attacks that have not been seen before cannot be detected until a new signature for the attack is created The anomaly detection technique involves looking for behavior that is outside the normal expected behavior This is usually done by utilizing statistical techniques that compare the observed behavior against the statistics of the expected normal behavior These techniques often utilize thresholds (such as amount of excessive loading of CPU, counts of traf c of speci c type, etc) that if exceeded indicate an attack Therefore, detectors utilizing this technique require prior training so that the thresholds used for detecting abnormal behavior are set at the appropriate values The advantage of anomaly-based detection is that this technique does not equire the existence of precise signatures and can therefore be used for detecting attacks not previously seen The disadvantage of anomaly-based detection is that, due to its statistical nature, it is more prone to false positives depending on how the thresholds are set There is always a trade-off between setting very tight thresholds (close to normal behavior), thus triggering a lot of false positives when users deviate even slightly from expected behavior, and setting very loose thresholds that minimize false positives but allow.

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In the primary phase of the attack, we make use of he fact that if we know T(O),then known plaintext-ciphertext pairs place restrictions on the possible values of other T ( j ) In fact, we can show that each known plaintext gives us three tests that can be used to check the validity of other putative T ( j ) If any of these tests fail, then the computed value of T ( j )must be incorrect, which implies that the assumed value of T ( 0 )is incorrect For the primary phase of the attack, we guess each possible value for T(O), and use the known plaintext to deduce information about other T ( j )bytes.

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If our guess for T ( 0 ) is incorrect, given sufficient known plaintext, we are highly likely to arrive at a contradiction, at which point we can eliminate our current putative T ( 0 )as a candidate for T ( 0 ) Once all possible T ( 0 )have been tested in the primary phase, we will have determined T(O), a small number of candidates for T(O), or depending on the number of known plaintext blocks available We then move on to the secondary phase, where we use a combinatorial search technique known as backtracking [87] to recover the key This secondary phase relies on information accumulated during the primary phase-information gleaned from the known plaintext The success of the secondary phase depends not only on the fact that T ( j ) j is in the Cave Table, as can be seen from (4.

7), but also on the fact that the intermediate values, & ( j ) - j , R ( j )- j , and S ( j ) j , are in the Cave Table, as can be seen in (46) Meet-in-the-middle is a standard technique from the ield of combinatorial search, where it goes by the clever name of meet-in-the-middle When it is applicable, a meet-in-themiddle attack can essential provide a square root improvement in the work fador, but it is can be relatively complex to implement Next, we describe this known plaintext attack in more detail For simplicity, we initially focus on the SCMEA cipher, then we show that the attack extends easily to CMEA-although significantly more known plaintext is required to obtain comparable results QR Code 2d Barcode generating on net generate, create qr Related: QR Code Generating NET , NET Code 39 Generating , Generate Code 128 .

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