Pseudo False Acceptance Attack on CB in .NET

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Pseudo False Acceptance Attack on CB
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If the CB secret transform is not known, the attacker may try to obtain a false acceptance by varying transforms. If successful, the attacker may forge a token storing the transform and use it with his own biometrics. The attack requires more computations than obtaining a false match with a known transform; however, the attacker does not need to collect or generate a biometric database. The FAR in the nonstolen token scenario may provide an estimate for the average number of transforms required,
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Biometric Encryption: The New Breed of Untraceable Biometrics
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although a more direct method would be to generate a pseudo-FAR curve by varying the transforms only. 26.6.1.3 Inverting the Hash
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This is another brute force attack. If a hashed key is stored into the helper data, the attacker may try to cryptographically invert the hash. As we already discussed, this attack should always be made more computationally expensive for an attacker than other attacks. 26.6.1.4 Nearest Impostors Attack
Unlike conventional biometrics or CB, a BE algorithm does not have a veri cation score: Its output is either a correct key or a failure message. However, an attacker may try to derive an intermediate score based on the knowledge of the algorithm. This score may be either global or partial that is, dealing with some parts of the helper data. This is usually the case when an ECC divides the helper data into smaller chunks, such as in Mytec2 [15] with a simple repetition code in k chunks, or in the Hao et al. fuzzy commitment scheme for iris [31] with Reed Muller ECC in 32 chunks. The partial score would be a length of the chunk minus a distance to the nearest codeword. The attacker may run a small (starting from a few hundred) database of images/ templates against the helper data to obtain a partial score for each chunk and a global score as the sum of the partial scores. The attacker identi es several nearest impostors [153] that is, the attempts with the highest global score or, alternatively, with the highest partial score for a given chunk. If, for any impostor s attempt, the partial score is large enough for a particular chunk, the attacker may assume that the correct codeword has been decoded for this chunk. Other impostors attempts may decode other chunks. Then a voting technique is applied to several of the nearest impostors attempts to make the process more robust. The attacker does not need to decode all or nothing he can do it chunk by chunk instead. A scheme that uses a simple repetition code, such as Mytec2, is especially vulnerable to this attack. If an (m, L) ECC is used, the success rate of the attack quickly diminishes when the L value (i.e., the number of codewords) increases [153]. 26.6.1.5 Hill Climbing Attack
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This is one of a few published practical attacks. It was developed by Adler [133, 134] against Mytec2 BE. The scheme was deliberately weakened and altered6 to make the attack easier and to prove the concept (note that this is a common practice in cryptography). Similar to the nearest impostors attack, the hill climbing attack is also based on the ability of the attacker to derive an intermediate score during the veri cation process.
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author omitted the second Fourier transform from the Mytec2 algorithm and did binary encoding in the lter domain rather than for the output array c0 (x).
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26.6 Security Issues with UB: Attacks
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Figure 26.5. Hill climbing attack on Mytec2 BE system. (Courtesy of A. Adler.)
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However, the hill climbing attack is more sophisticated than the nearest impostors attack, although the latter is usually more ef cient. For a BE chunk of (m, 1) repetition code, the partial score is derived in the same way as described for the nearest impostors attack. Then a global matching score is constructed as a sum of all chunk partial scores. By making small changes in the input impostor s image, the attacker watches how the score changes. If it increases, the change is retained; if not, the attacker tries a different change. After a number of iterations, the attacker may be able to retrieve a key. The details of the attack, which uses quantized hill climber, are thoroughly described in references 133 and 134. As shown in Figure 26.5, the attack converges quite quickly toward the correct key; the impostor face image becomes looking somewhat similar to the enrolled image. If successful, the hill climbing attack retrieves the key and creates a masquerade image/template. There are two conditions necessary for the hill climbing attack: 1. The attacker must be able to obtain a global, or a partial/intermediate matching score. The score must be meaningful; that is, a higher score means closer similarity. 2. Small changes in the input cause relatively small changes in the score (although Adler s algorithm is able to handle score quantization to some extent). Most vulnerable to the hill climbing attack are the schemes with short ECCs, such as Mytec2 with a repetition code. A BE scheme with a single block ECC is much better protected against this and the nearest impostors attack. Most CB schemes are inherently vulnerable to the hill climbing attack, since, unlike BE, the CB algorithm always outputs a veri cation score. A successful hill climbing attack on CB would create a masquerade image/template. It is likely that an intermediate score can be derived for the fuzzy vault scheme, which stores real ngerprint minutiae buried among chaff points. The applicability of a hill climbing attack to the fuzzy vault has been claimed by Adler [133]. The advanced
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