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Classification of social. ped. of technologies
The most significant reasons for the classification of social. ped. technologies include:
- type of social. ped. technologies (they can be general, private and special);
- appointment (this can be pedal correction, ped rehabilitation, re-education, vocational guidance work);
- subject of application - social. the teacher (the level of his professionalism, individual qualities, etc.);
- the object of destination (student, family, etc.);
- place of application (educational institution, specialized center, place of residence, etc.);
- Implementation variant (methods used in technology, method of achieving the goal, for example, training).
Bibliography:
1. Уринбоев Х. Б., Мамажонова Г. К. САМОЦЕННОСТЬ И СМЫСЛ ЧЕЛОВЕЧЕСКОЙ ЖИЗНИ //Теория и практика современной науки. - 2017. - №. 3. - С. 741-743.
УДК 004.9
Egamnazarov K.
student
Fergana branch of TUIT named after Muhammad al-Khwarizmi
Uzbekistan, Fergana OVERVIEW OF BIOMETRY: FINGERPRINTS AND IRIS
Abstract: In this paper we give a survey of biometrical applications in security context. We start with a brief overview of the different biometric modalities which are most frequently used and compare their security contribution with classical cryptographic primitives. We then consider the case of fingerprints when used as password surrogates.
Keywords: Biometry, Iris, fingerprint, secret key.
1. Introduction
Confidential communication is a request with an old tradition, mostly with military applications. Two parties wish to communicate in such a way that no unauthorized (by them) third party may have a slight chance to reveal the content of the communication. Some side-requirements in such a setting are: The request for secure authentication; the request for provable signatures, or, more generally, insurance of the impossibility to repudiate the origin of a message. A common answer to these requirements was provided by cryptography. A logical art for dealing with this problem is known from early Antiquity; until recent times. It was commonly accepted that for confidentiality, one needed some secret keys that were shared only by the authorized parties. The algorithm by which these secret keys were used should also preferably contain some private tricks to make it more reliable. Since the ideas for encryption were based on a common collection of
techniques, one could not require completely private algorithms; but it was assumed that by adding some special tricks and complexity, an algorithm would become more resistant to attacks. The general attitude in this respect was completely reversed in modern cryptography, and since decades we prefer to use publically known algorithms, that have resisted the scrutiny of a world-wide community of specialists, thus proving their reliability. It is believed that additional private tricks can often lead to providing a false impression of security, which may lead to errors and attacks.
2. Fingerprints
In our context, biometry is the scientific domain which is concerned with measurements and images of (parts of the) human body, that are to high extent reproducible and may also practically be used for the identification of individuals. In order to be useful in applications, biometry should enjoy some fundamental properties, like
BM1: Universality, meaning that all potential users should possess this biometric trait.
BM2: Uniqueness, in the sense that the biometric trait is different from person to person, and thus helps distinguish individuals and authenticate them correctly.
BM3: Permanence, meaning that the trait will not change in time, and thus, an individual can be identified even on base of templates gathered long periods of time before.
BM4: Some practical properties, such as performance, acceptability, and lack of circumvention.
The processing time for identification should be low for reach "acceptable" recognition rates. The acceptability addresses a subjective, social issue: it should be accepted by the bulk of society that presenting one's biometric traits is acceptable. For instance, in some culture, showing the face of a woman and taking pictures of it, might appear as unacceptable, and even presenting one's eye into a camera may require some preparation. Biometric traits may often be imitated by fakes, so it is a requirement mainly for the authentication system, that it be capable of distinguishing between artificial fakes and living biometric sources. Since, in addition, human leave everywhere there fingerprint, due to the sweat and skin fat, the fingerprint became an important identification method in forensics: techniques for gathering latent fingerprints from crime sites developed. The fingerprint can be seen as an overall picture of a flaw of ridge lines, induced, in detail with natural endings and bifurcations of the lines. Therefore a first step in matching fingerprints out of large data bases will always begin with a matching of the 10 tuple of types of the ten fingers. This will lead to a small selection with in which a detailed identification based on matching of minutiae can be performed by the specialized. The precise number of identical minutiae may vary slightly from country to country, and one may even encounter some other classifications of ridge flaws than the one of Dalton—but the main features are the same. With the advent of computers, the machine-identification of fingerprints became a task of
study in image processing; dedicated methods were developed and towards the turn of the century sufficiently reliable plaintext matching system had been developed. For very good quality pictures, an error rate of around 0:1 % is frequent, while for pictures of poor quality, even an accuracy of 0.5-1.0% is acceptable in practice.
3. Iris
While fingerprint recognition has an old, forensic born history, the identification based on the human iris is a one-man show. It was the mathematician John Daugman, presently teaching at Cambridge, who recognized the identification potential in the human iris and developed after a lot of work the algorithms and patents for turning this insight into a practical biometrical identification procedure. The human iris has the advantage of a perfect crown-circular geometry, making its localization in images an easy task. The base for recognition is a system of log-like lines which are different in thickness and frequency, from person to person. Daugman had the bright idea of performing plain Fourier transforms on the iris picture, after having processed it and enhanced image qualities, while unfolding the circle along a line. The result of the analysis is a code of256 which was standardized and patented by Daugman, as the iris code. Claims are that between 20 % and 30 % of identical bits in this code helps ascertain the identity of a person with error rates within the one per million. Iris has been implemented at various airports, due to its claimed accuracy. Since biometry is not a deterministic science, as soon as iris recognition went public and entered scrutiny of various university research groups, new questions were raised, the claimed recognition rate slightly dropped and even the question was raised , if the iris imprint is permanent in time and if it did not chance after diseases and other organic disturbances. After all, the permanence of the fingerprint had been empirically watched in forensics over more than 100 years, while iris identification is only two decades old.
References:
1. Juels, A., Sudan, M.: A fuzzy vault scheme. In: Lapidoth, A. Teletar, E. (eds.) Proceedings of International Symposium on Information Theory, 2002, p. 408
2. Juels, A., Sudan, M.: A fuzzy vault scheme. Des. Codes Cryptogr. 38(2), 237257 (2006)
3. Yang, S., Verbaudwhede, I.: Automatic secure fingerprint verification system based on fuzzy vault scheme. In: Proceedings of International Conference on Acoustics, Speech and Signal Processing, 2005, pp. 609-612
