Secure Information Sharing Using Personal Biometric Characteristics

The high-speed and constants changes in information technology and business needs to drive the development and evolution of Cognitive Information Systems (CIS). There are limited items of research on the general model related to the analysis and design of CIS. This paper attempts to create a joint design scheme, where tries to joining the various models for CISs and Understanding-based management systems (UBMSS). The examined components substantiate elements of CIS analysis and design; however, they weren’t delineated as modeling elements and not depicted as enabling instruments that are needed to create a consistent and integrated system. The vital ingredients for modeling as follows: semi-structured documents, business processes, constituents of knowledge management, the enterprise, and the information architecture, together with the self-directing software components—Artificial Intelligence (AI)—that yield functions. For CIS modeling, the constituents, which were mentioned previously, were combined into a unified framework. That framework follows the object-oriented paradigm and architecture approach. The research aims to describe and present a framework that covers an overarching model and assists our understanding of the properties of CIS and UBMSS, permitting the formulation of a practical development method for Cognitive Information and Cognitive Management Systems (CMSs).

Cognitive informatics in image semantics description, identification and automatic pattern understanding

This paper presents some advances techniques for the strategic data sharing and splitting used for encryption and division of secret data, and enterprise management as well as modern approaches for management of divided information. The presented data sharing and splitting techniques will concern cryptographic algorithms as well as data sharing procedures based on cognitive data analysis techniques. Secret information sharing techniques aim to secure strategic information or secrets against disclosure to unauthorized persons. This paper presents algorithms and techniques allowing for visual information division and sharing on the basis of cognitive data analysis systems. The development of computer techniques for classified information splitting should also be useful in the process of shared information distribution and management. Cognitive systems for the semantic analysis of strategic economic and financial data will also be used to conceal information about the condition of the enterprise/organization.

Secret sharing (SS) schemes based on cellular automata (CA) are considered as secure encrypting algorithms, where several secret data can be shared among some persons. Recently the SS schemes can be applied to solve real-world problems, such as security in cloud computing. The principal obstacle of use of the SS scheme is its considerably high computational cost; especially if a large amount of secret data must be encrypted and shared. In this work, we propose a parallel CA-based SS scheme suitable for any kinds of digital data in the graphic processing unit using compute unified device architecture technology. The uses of global memory and shared memory are analyzed from computational effectiveness and security points of view. The experimental results show the proposed parallel implementation provides a speedup rate more than 18-fold compared with its sequential implementation. Also we show the increase of the security level of the parallel implementation with respect to the sequential implementation.

A verifiable secret sharing scheme with combiner verification and cheater identification

U-healthcare, which grafted advanced IT technology onto medical technology, is in the limelight because it can provide medical services at anytime and anywhere. U-healthcare system applied RFID technology for Implantable Medical Device (IMD), but patient's biometric information can be easily exposed to third parties. In this article, RFID-based U-healthcare authentication protocol is proposed to prevent illegal usage for personal biometric information exposed to the third patty. The proposed protocol guarantees patients' biometric information integrity as compounding random numbers between administrators and hospital/clinic managers, and uses continuous number SEQ and time stamp T to synchronize IMD/administrators and administrators/hospital managers. Also, to protect user's privacy from the third party, patients' biometric information can be safely guarded by managing patients' security identifiers by administrators.

In recent years, a lot of data hiding algorithms have been proposed in the literature. Providing high payload capacity, high visual quality, and robustness is the main aim of data hiding algorithms. However, high visual quality and high payload capacity are inversely proportional. For this reason, we used a probabilistic method. Probabilistic method is one of the soft computing methods. In this paper, a new data hiding algorithm based on probabilistic XOR secret sharing (PXORSS) in lifting wavelet transform (LWT) domain is proposed for providing high capacity and high visual quality. Previous studies have used cover images as RGB images or multiple grayscale images. LWT is proposed to use secret-sharing-based data hiding algorithms with a single grayscale cover image. In the proposed method, we used low–high (LH), high–low (HL), and high–high (HH) high-pass filter bands as cover images, and the secret data are divided into three secret shares by using PXORSS scheme. The least distorted pieces of probabilities are embedded into the high-pass filter bands as the secret share of the host image. We obtained high capacity and high visual quality in LWT domain by using the proposed method.

This chapter proposes innovative features of future industrial organizations in order to provide them with the capabilities to manage high levels of environmental complexity in the 21st century. For such a purpose the author introduces the concept of Computational Organization Management Networks (COMN), which represents new organizations whose principles of operation are based on the concepts of Hierarchic Cognitive Systems (HCS) along with those of Telecommunications Management Networks (TMN). Structured with functional layers and cognitive roles that range from technical and managerial to institutional levels of analysis, and also equipped with operational, managerial and strategic processes, the concept of Computational Organization Management Networks (COMN) plays an important part in the developments of future organizations where cognitive machines and Cognitive Information Systems (CIS) are prominent actors of governance, automation and control of the whole enterprise. It is in such a context that the new organization COMN will provide customers and the whole environment with innovations such as immersiveness for the production of services and goods that are most customer-centric.

Threshold schemes are adaptable cryptographic primitives that distribute trust in secret data by requiring k out of n entities to co-operate before the data can be recovered. An important security management issue relating to threshold schemes is the problem of updating the parameters of a threshold scheme. The paper discusses serious shortcomings in two proposed protocols for threshold parameter update.

Quantum secret sharing is a cryptographic scheme that enables the secure storage and reconstruction of quantum information. While the theory of secret sharing is mature in its development, relatively few studies have explored the performance of quantum secret sharing on actual devices. In this work, we provide a pedagogical description of encoding and decoding circuits for different secret sharing codes, and we test their performance on IBM’s 127-qubit Brisbane system. We evaluate the quality of the implementation by performing a SWAP test between the decoded state and the ideal one, as well as by estimating how well the code preserves entanglement with a reference system. The results indicate that a ((3,5)) threshold secret sharing scheme and a non-threshold 7-qubit scheme perform similarly based on the SWAP test and entanglement fidelity, with both attaining a roughly 70–75% pass rate on the SWAP test for the reconstructed secret. We also investigate one implementation of a ((2,3)) qutrit threshold scheme and find that it performs the worst of all, which is expected due to the additional number of multi-qubit gate operations needed to encode and decode qutrits. A comparison is also made between schemes using mid-circuit measurement versus delayed-circuit measurement.

As today’s world are switching to the digital media through the Internet and multimedia tools like Facebook, YouTube, Twitter and WhatsApp which consists of a number of videos, hence it always better to take urgent problems of such digitally transmitted video in terms of information security. The current video steganography approach is not so effective for imperceptibility, robustness, security of hidden secret data, embedding capacity and very good visual recovery of a secret as well as original data. Hence, to maintain the balance between these issues is another big challenge. This work employs a novel and efficient Field Programmable Gate Array (FPGA) implementation of audio, video crypto steganography using General Modified Secured Diamond Encoding (GMSDE) scheme. The new proposed scheme is based on Diamond Encoding (DE), Exploiting Modification Direction (EMD) and Adaptive Pixel Pairing Matching (APPM) algorithms called as General Modified Secured Diamond Encoding (GMSDE). The DE method is always used for k > 1 which produces distortion, less embedding capacity and security of hidden data. The GMSDE scheme changed the Diamond Characteristic Value (DCV) to conceal more than one secret bit vertically and horizontally to create a modified diamond shape of secret data which is equal to log2(2x2 + 6x + 5) - ary and produces the conceal capacity of 1.16 to 4.82 bpp for the values of x = 0 to 25 where x is the embedding parameter. Experimental results confirm that the conceal capacity measured by bit per pixel (bpp), security of hidden secret data, very good visual recovery of both original and secret data, Cross-Correlation (CC) and Peak Signal to Noise Ratio (PSNR) values are better than existing approaches. Further through many attacks on stego video during transmission using forensic detection approach, the imperceptibility, security of hidden data and robustness is increased for secure communication.

Because the authentication method based username-password has the disadvantage of easy disclosure and low reliability, and also the excess password management degrades the user experience tremendously, the user is eager to get rid of the bond of the password in order to seek a new way of authentication. Therefore, the multifactor biometrics-based user authentication wins the favor of people with advantages of simplicity, convenience and high reliability, especially in the mobile payment environment. Unfortunately, in the existing scheme, biometric information is stored on the server side. As thus, once the server is hacked by attackers to cause the leakage of the fingerprint information, it will take a deadly threat to the user privacy. Aim at the security problem due to the fingerprint information in the mobile payment environment, we propose a novel multifactor two-server authentication scheme under mobile computing (MTSAS). In the MTSAS, it divides the authentication method and authentication means, in the meanwhile, the user's biometric characteristics cannot leave the user device. And also, MTSAS chooses the different authentication factors depending on the privacy level of the authentication, and then provides the authentication based on the different security levels. BAN logic's result proves that MTSAS has achieved the purpose of authentication, and meets the security requirements. In comparison with other schemes, the analysis shows that the proposed scheme MTSAS not only has the reasonable computational efficiency, but also keeps the superior communication cost.

The handling of sensible data in Information Systems is currently very usual. Which data is to be considered sensible is up to the application, but at least we can consider those such as personal data, financial data as well as access control data. Actors dealing with such Information System (clients/citizens, service providers, integrators, etc.) have to be aware of the security level achieved within the system. Although this is a very important issue in any system, when biometric information is handled it becomes a critical point. Reason for this is that biometric information is permanently valid, as it is expected to be kept the same during the whole life of a person. While a private key can be changed as desired and even cancelled, a user cannot change his fingerprint (unless changing finger) or even cancel it. If cancelling biometric raw data, the user will be limited, in case of fingerprints, to 10 successful attacks during his/her whole life. These kind of considerations has already been published even back to 1998, as it can be read in [1]. Therefore, biometric systems have to be kept as secure as possible. There are several Potential Vulnerable Points (PVPs) in any Biometric System, as it can be seen in Fig. 1. All those 9 PVPs have to be considered when designing a biometric solution. A good introduction to threats in a Biometric System can be found in [2, 3], and in BEM [4].

Data management in cognitive financial systems

A Cognitive Revolution in Management (CRM) has been brought about through Stafford Beer's work in management cybernetics. Explains the philosophical undertone of CRM as well as cybernetic features associated with it. The work on varietal aspects of management systems by Ansoff has also contributed to CRM, which needs to be backed by a cognitive information system, and a Cybernetic Theory of Management.