Secure Information Management in Hierarchical Structures

Self Cite

Summary This paper presents new approach for creation of advanced multilevel user authentication protocols using hybrid CAPTCHA codes. Such codes will define a new class of cognitive CAPTCHAs, which, during verification, require from users special skills and knowledge, which is necessary for proper authentication. This way of authentication may be oriented for providing data access only for a special group of experts or trusted users who represent particular expertise areas and have special perception abilities and knowledge. For presented authentication protocols, possible examples of applications will be presented, and security features will be described. Presented innovative verification codes will considerably expand the existed security protocols toward the creation of cognitive‐based approaches oriented for user authentication. Such approaches define novel classes of cryptographic procedures, which can use personal features and perception skills.

Section: Multilevel Authentication Codes Using Expert Knowledgementioning

confidence: 99%

Cognitive cryptography for data security in cloud computing

Ogiela

2019

Self Cite

“…Protecting any kind of information from unauthorized access has been a subject of security research for many years and numerous schemes have been developed over time to secure strategic data and transactions from several menaces, ranging from insider threats to common attacks to authentication mechanisms and infrastructures . The diffusion of new smart devices is creating new opportunities and opening new perspectives for developing new enhanced and more usable authentication schemes, which will be better capable to face these challenges.…”

Section: Related Workmentioning

confidence: 99%

Securing PIN‐based authentication in smartwatches with just two gestures

Guerar

Migliardi

Palmieri

et al. 2019

Summary Smartwatches are becoming increasingly ubiquitous as they offer new capabilities to develop sophisticated applications that make daily life easier and more convenient for consumers. The services provided include applications for mobile payment, ticketing, identification, access control, etc. While this makes modern smartwatches very powerful devices, it also makes them very attractive targets for attackers. Indeed, PINs and Pattern Lock have been widely used in smartwatches for user authentication. However, such authentication methods are not robust against various forms of cybersecurity attacks, such as side channel, phishing, smudge, shoulder surfing, and video‐recording attacks. Moreover, the recent adoption of hardware‐based solutions, like the Trusted Execution Environment (TEE), can mitigate only partially such problems. Thus, the user's security and privacy are at risk without a strong authentication scheme in place. In this work, we propose 2GesturePIN, a new authentication framework that allows users to authenticate securely to their smartwatches and related sensitive services through solely two gestures. 2GesturePIN leverages the rotating bezel or crown, which are the most intuitive ways to interact with a smartwatch, as a dedicated hardware. 2GesturePIN improves the resilience of the regular PIN authentication method against state‐of‐the‐art cybersecurity attacks while maintaining a high level of usability.

“…Data splitting and sharing algorithms have been developed for many years with a view to store and distribute secret data in a safe manner. 1,2,[4][5][6][7][8][9][10][11][12][13][14][15] The development of IT techniques and a need to collect and store increasingly larger sets of secret data resulted in the need to develop new data protection protocols. This is why the class of data sharing algorithms has been enhanced by new solutions, described in the literature as linguistic 12,[14][15][16][17] and biometric threshold schemes.…”

Section: Introductionmentioning

confidence: 99%

“…A new class of data sharing algorithms is combining the solutions presented above to develop linguistic-biometric threshold schemes. This class of schemes has been described in other studies, 4,5,[9][10][11][12][13][14][15][16][17] and they are used for the data protection processes, taking into consideration the layers of semantic meaning of the secret as well as the dedicated shadow allocation, executable by means of such biometric techniques.…”

Section: Introductionmentioning

confidence: 99%

Cognitive security paradigm for cloud computing applications

Ogiela¹,

Ogiela

2019

Self Cite

Summary This article presents new paradigms of confidential data protection. New classes of paradigms are dedicated to enhancing the already‐known cryptographic solutions belonging to the group of data sharing schemes. Data sharing schemes are dedicated to executing data protection tasks by means of splitting data into parts (called shadows) and distributing those shadows among a group of secret trustees. This process is enriched by linguistic and biometric solutions to guarantee protection of the shared data by means of biometric labeling or by means of user verification with the application of meaning interpretation of individual secret parts. The novelty in this solution is in the application of cognitive algorithms to describe correctly the shared secret. Cognitive paradigms guarantee an execution of information concealment protocols and their division at various levels of knowledge held by individual protocol participants. The paradigms of cognitive description of the concealed data have been introduced into a new class of data sharing protocols, ie, into the linguistic‐biometric threshold schemes. A special feature of the proposed solution is its universality, which is a possibility to apply the here‐discussed threshold schemes in the processes of data concealment with varying importance. At the same time, this solution can be applied to execute data protection tasks against unauthorized acquisition or disclosure. This paper will present also the possibilities of application of the paradigms presented here to conceal data dedicated to the data management processes.