# Crypto-Biometric Models for Information Secrecy

Marek R. Ogiela, Lidia Ogiela, Urszula Ogiela

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Marek R. Ogiela, Lidia Ogiela, Urszula Ogiela. Crypto-Biometric Models for Information Secrecy. International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CDARES), Sep 2014, Fribourg, Switzerland. pp.172-178, 10.1007/978-3-319-10975-6_13 . hal-01403994

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# Crypto-biometric Models for Information Secrecy

Marek R. Ogiela, Lidia Ogiela, Urszula Ogiela

AGH University of Science and Technology
Cryptography and Cognitive Informatics Research Group
30 Mickiewicza Ave., PL-30-059 Krakow, Poland
{mogiela, logiela, ogiela}@agh.edu.pl

**Abstract.** In this paper will be presented some advances in crypto-biometric procedures used for encryption and division of secret data, as well as modern approaches for strategic management of divided information. Computer techniques for secret information sharing aim to secure information against disclosure to unauthorized persons. The paper will present algorithms dedicated for information division and sharing on the basis of biometric or personal features. Computer techniques for classified information sharing should also be useful in the process of shared information generation and distribution. For this purpose there will be presented a new approach for information management based on cognitive systems.

**Keywords:** cryptographic protocols; bio-inspired cryptography; secret sharing algorithms

## 1 Introduction

The important and vital information is very often secret. These information need to be protected using modern cryptographic procedures and techniques. To guarantee the highest level of protection needed to be applied special kinds of security. Sometimes it may be a personalized cryptography, which use some personal biometric pattern for security purposes.

Many methods of information secrecy include secret splitting techniques, secret sharing, secure information, individual human biometrics analysis [7-11]. The last one – the biometrics analysis include personal features, which are different for each person. The most important in such type of analysis is the ability to take into account the individual characteristics, for example personal biometrical features. Of course we can consider for such purpose both standard as well as non-standard biometric patterns.

The most important personal biometrics are following [11]:

* the DNA code,

* face/hand/foot geometry,

* the shape of fingerprints, of hand/foot bones,

* anatomical features of the face, hand, foot, iris,

* anatomical feature of the body,
* the structure of blood vessels.

The personal features are used to create crypto-biometrics secrecy. These type of secrecy is most important in many different kinds of IT systems [5, 6], but the particularly important in cognitive information systems, which may be applied for following tasks [11]:

* to sharing the secret information in enterprise,

* to splitting the strategic information in organization,

* to protection of confidential information.

The basic components of biometric analyses adopted in this paper are crypto-biometrics for the secrecy of information. The main content of this aspects can be a component for analysis, interpreting and mining managing processes [3, 4].

## 2 Data Security in Crypto-biometrics Model

Data security in crypto-biometrics models may be achieved using one of the following algorithm [4, 9, 13, 14] :

* Lagrange's algorithm,

* vector algorithm,

* Asmuth-Bloom algorithm,

* Karnin-Greene-Hellman algorithm,

* Ong-Schnorr-Shamir algorithm,

* ElGamal algorithm,

* Fiat-Shamir algorithm.

These cryptographic algorithms are used for information sharing and information splitting, and also to secure data by asymmetric encryption [2]. Among these procedures in particular information sharing protocols may be divided into the following groups [9, 14]:

* information sharing without the involvement of a trusted person,

* message sharing without disclosing one's parts,

* message sharing with disclosure prevention,

* message sharing with cheaters,

* message sharing with testing,

* message sharing with a share withdrawal.

Cryptographic algorithms of data sharing and splitting are used to construct the data security model. Such models are used to secure of encrypted or divided data.

The essence of this kind of models is application of biometric features to sharing and reconstruction of information [9, 12]. Some of the data security algorithms are based on the use of linguistics algorithms for data interpretation, analysis, and understanding, before its encryption and distribution. Information sharing and information splitting
ting approaches may use mathematical linguistics formalisms especially during cod-
ing processes. The main idea of this approach is used to linguistics formalism to pro-
cess of data encryption [1, 7], especially sequence, tree and grammatical formalisms.
Such formalism are used to record and interpret the meaning of the analyzed bio-
metric data.

Individual biometric features are used for example in DNA cryptography. DNA cryp-
tography may be used to generate keys based on DNA codes and personal infor-
mation. It should be noted that DNA molecules, which have existed in nature as long
as known life forms, are beginning to play an increasing role in cryptography, but it
was only in the 21st century that science offered opportunities of using them as infor-
mation media, and the replication processes taking place in them as information cod-
ing techniques. Recent years have seen increasingly frequent reports of further dis-
coveries, while the results of DNA research are becoming significant not just in biol-
ogy or genetics, but also in the field of steganography.

People have not realises the computational potential associated with molecules for
many years. The first ideas of combining computers with DNA chains appeared in
1973, when Charles Benett published a paper in which he proposed a model of a pro-
grammable molecular computer capable of executing any algorithm. However, the
first successful attempts were made 20 years after this idea publication. In 1993,
Leonard Adleman became the first to execute calculations using a DNA computer and
solved the Hamilton path problem for several cities [1].

Since then, many new proposals for using DNA sequences as an information medium have been made. Practically every such method of classifying data boils down, at least at one stage, to storing this data in the appropriate DNA molecules. At this level there are several available possibilities of using these acids as the medium for coded information. The most obvious one is using the structure of particular nucleotides. As four types of them can be distinguished, one base can store 2 bits of information. We can thus assume that the coding will, for example, be executed as presented in Fig 1. One can also start from the assumption that one pair of nucleotides (a single bond) corresponds to one bit of information.

Such information coding methods are used in biological solutions which have inspired
us to development of a new class of algorithms for secret splitting described in [10].
However, presented algorithm, called a linguistic threshold scheme, operates in a
more general way and supports coding secret information (to be split) in longer se-
quences, i.e. containing more than 2 bits of information. The purpose of this algorithm
is a threshold split of strategic data managed within hierarchical structures, with var-
ied access capabilities dependent on the rights granted [9, 10, 11].
DNA chains in information encoding

<figure><img src="image_2.png" /><figcaption>Fig. 1. Possible methods of coding information using DNA molecules</figcaption></figure>

Thus, crypto-biometrics models based on DNA encoding and others biometric pat-
terns are used to:

• secret sharing and secret splitting,

• secure information,

- encoding of information by individual biometrics feature,

* decoding information by personal biometrics feature,

* secure information prior to the disclosure to others person.

The secret and confidential information is analyzed and interpreted by way of crypto-
graphic information analyses. The authors of this paper proposed to use the crypto-
biometrics analysis to strategic information management in enterprises.

3 Crypto-biometrics Model for Strategic Information Management

Strategic business data require special protection, therefore they must be protected from disclosure. The methods of strategic data sharing in the enterprise presents Fig.2. Strategic data are splitting by used one of the cryptographic algorithms used to splitting processes. Consequently in this process information is divided into a number of parts of this information. Each of them is assigned to another holder. And no other person knows the other parts of strategic data. Therefore data are protected. To reproduce the strategic information is necessary to submit a certain number of them. Not necessarily all parts of divided strategic information. The number of necessary parts of strategic information needed to reproduced specifies the algorithm that was used to divide strategic information.
<figure><img src="image_3.png" /><figcaption>Fig. 2. The process of sharing strategic information in enterprise</figcaption></figure>

The strategic information management in enterprise present Fig. 3.
<figure><img src="image_4.png" /><figcaption>Fig. 3. The process of crypto-biometrics model for strategic information management in enterprise</figcaption></figure>

In this process the most important is stage of coding strategic information using per-
sonal biometrics feature. The biometrics features are different for different persons or
kinds of biometrics. The encoded strategic information by one of the personal bio-
metric is shared between the participants of procedure. In this way the information is
not only divided, but also encoded. Reproduction of information therefore requires:

* submit an appropriate amount of parts shared information,

* disclosure of key biometric that was used to encode information.

Crypto-biometrics models therefore protected by algorithms of secret sharing and
biometrics keys.

4 Conclusions

Crypto-biometrics models are currently used to ensure security of different kinds of
information, especially strategic information in organization. Strategic information
management is often understood as management secret information. Ensure secrecy
of strategic information is the responsibility of crypto-biometrics systems. The ad-
vantages of the proposed systems is:

* guarantee the security of strategic information,

* safety features during performing secret distribution,
* dividing important strategic data and assigning its shares to members of the authorized group,

* handle any digital data which needs to be intelligently divided among authorized persons and then possible to secretly reconstruct,

* used in different economical management structures e.g. hierarchical, divisional, functional etc.

**Acknowledgments.** This work has been supported by the National Science Centre, Republic of Poland, under project number DEC-2013/09/B/HS4/00501.

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