Towards New Classes of Intelligent Cognitive Information Systems for Semantic Pattern Classification

This paper introduces two new classes of specialised vision systems called UBIAS and E-UBIAS. Such systems belong to the group of cognitive reasoning systems and are designed for the semantic analysis of visual patterns in the form of medical images. Proposed systems are predecessors of a new generation of intelligent systems dedicated for understanding medical diagnostic visualization and using this data as biometric characteristics

METHODS OF COGNITIVE ANALYSIS IN MEDICAL INFORMATION SYSTEMS OF DSS-TYPE

This paper demonstrates that AI methods, in particular linguistic mechanisms of semanticmeaning reasoning can be applied to the development of intelligent IT systems. They enablealso conducting an in-depth meaning analysis in the presented DDS information systems.This paper presents also IT mechanisms of object meaning description on selected examplesof spinal cord image analysis. The procedures for such semantic reasoning are based on themodel of cognitive resonance. They have been applied to the task of meaning interpretationof a selected type of central nervous system diagnostic images, as an intelligent analysismodule in IT systems. The application presented in this paper is of research character and itserves the preparation of efficient lesion detection methods applied to a dataset originatingfrom magnetic and resonance examinations of the spinal cord structures

Human-artificial intelligence approaches for secure analysis in CAPTCHA codes

CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) has long been used to keep automated bots from misusing web services by leveraging human-artificial intelligence (HAI) interactions to distinguish whether the user is a human or a computer program. Various CAPTCHA schemes have been proposed over the years, principally to increase usability and security against emerging bots and hackers performing malicious operations. However, automated attacks have effectively cracked all common conventional schemes, and the majority of present CAPTCHA methods are also vulnerable to human-assisted relay attacks. Invisible reCAPTCHA and some approaches have not yet been cracked. However, with the introduction of fourth-generation bots accurately mimicking human behavior, a secure CAPTCHA would be hardly designed without additional special devices. Almost all cognitive-based CAPTCHAs with sensor support have not yet been compromised by automated attacks. However, they are still compromised to human-assisted relay attacks due to having a limited number of challenges and can be only solved using trusted devices. Obviously, cognitive-based CAPTCHA schemes have an advantage over other schemes in the race against security attacks. In this study, as a strong starting point for creating future secure and usable CAPTCHA schemes, we have offered an overview analysis of HAI between computer users and computers under the security aspects of open problems, difficulties, and opportunities of current CAPTCHA schemes.Web of Science20221art. no.

Strategic Information Splitting Using Biometric Patterns

Abstract In this paper will be proposed a new algorithm for secure strategic information sharing using biometric information. In classic cryptographic threshold schemes used for secret splitting and sharing there aren't any connection between generated shares and particular participants of threshold protocol. In fact sometimes it may be useful to generate a special personalized shadows, which allow not only reveal the original secret information, but also to identify who is the owner of particular shares or information shadow

Intelligent Data Management and Security in Cloud Computing

This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network