Enhance cloud security and effectiveness using improved RSA-based RBAC with XACML technique

Sensitive information has become a bottleneck of enterprises' collaboration, especially to competitive enterprises' collaboration. How to make collaborative decision under the protection of sensitive information is an important problem to advance enterprises' collaboration. To investigate the problem, a collaborative ordering of enterprises with differentiated products is modeled to get the optimal ordering. The model's computation needs the information of cost and demand which other enterprises are unwilling to provide. So a secure computation protocol under the protection of cost and demand information is designed to compute the optimal ordering of collaborative enterprises. The result shows the decision of complete information sharing can be achieved even without leaking the sensitive information through using the secure computation protocol.

The escalating need for robust data security has propelled cyber security practitioners into a perpetual quest for innovative solutions. This endeavor involves the strategic amalgamation of cryptographic algorithms with meticulously customized alterations to specific algorithmic processes. In this pursuit of heightened data protection, the Arnold Cat Map emerges as a pivotal tool, a mathematical transformation that gracefully elucidates the intricate movement of points within a two-dimensional plane. This movement occurs in a systematic and repetitive manner, rendering it an indispensable asset in the domains of cryptography and image scrambling. The Arnold Cat Map operates by meticulously relocating each point within the two-dimensional plane to a fresh coordinate, all the while adhering to an intricately structured pattern. The result is a formidable "mixing" effect that enhances data security. When applied theoretically to widely employed encryption methods like Advanced Encryption Standard (AES) for symmetric encryption and the Rivest-Shamir-Adleman (RSA) algorithm for asymmetric encryption, the Arnold Cat Map exhibits the potential to significantly augment the randomness of the encrypted output. This augmentation of randomness, in turn, fortifies the security of digital assets and communications, making them more resilient against adversarial attacks. By introducing this innovative concept into the realm of cryptography, cyber security practitioners endeavor to fortify data security, offering a higher degree of confidence in the protection of sensitive information and digital assets against a backdrop of ever-evolving cyber threats.

Automated trust negotiation is an iterative process that establishes trust gradually between strangers wishing to share resources or conduct business transactions, by requesting and disclosing digital credentials. Protection of sensitive information in automated trust negotiation has been drawn much attention all over the world. Recently, policy database has been proposed as a means to protect possession-sensitive attributes. However, possession sensitive information leakage through probabilistic inference still exists in it. In order to solve this problem, in this paper, a formal definition for relevant attributes is given. A relation model of relevant attributes is also designed. Besides that, we present a desideratum of policies for relevant attributes based on the relation model. And the desideratum is enforced in a relevance checker that is used to check whether the submitted policies satisfy the desideratum, which is an addition to the policy database system as an improvement. Safety in this improved policy database system is analyzed, which comes to a conclusion that this approach, compared with the original policy database system, provides more strongly protection to possession sensitive attributes.

This work outlines engineering decisions required to support a provenance system in an open world where systems are not under any common control and use many different technologies. Real U.S. government applications have shown us the need for specialized identity techniques, flexible storage, scalability testing, protection of sensitive information, and customizable provenance queries. We analyze tradeoffs for approaches to each area, focusing more on maintaining graph connectivity and breadth of capture, rather than on fine-grained/detailed capture as in other works. We implement each technique in the PLUS system, test its real-time efficiency, and describe the results.

A computer system intrusion is seen as any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. The introduction to networks and the Internet caused great concern about the protection of sensitive information and have resulted in many computer security research efforts during the past few years. This paper highlights a novel approach for detecting intrusion based on bio-inspired algorithm. The intrusion detection model combines the fuzzy ants clustering algorithm and artificial immune recognition algorithm to maximize detection accuracy and minimize computational complexity. The implemented system has been tested on the training data set from DARPA DATA SET by MIT Lincoln Laboratory on intrusion. The applicability of the proposed method and the enhanced security it provides are discussed

Centralized access control architectures demonstrate serious scalability problems and vulnerability to single points of failure along with privacy risks during IoT network expansion. The recently developed Blockchain and Federated Learning based Access Control Technology (BFL-ACT) serves as a distributed access control solution for IoT networks that uses blockchain technology combined with federated learning and cryptographic methods to enhance participant privacy protection and manage vast network sizes effectively. The protection of sensitive information and model updates during both training and inference phases utilizes integrated homomorphic encryption alongside lightweight cryptographic primitives. This paper demonstrates the system design and protocol flows for BFL-ACT and develops its threat model before constructing a prototype IoT testbed for performance benchmarking. The BFL-ACT approach demonstrates superior intrusion detection capabilities and increased robustness against attacks by malicious actors compared to standard centralized and non-blockchain federated learning systems while maintaining low communication costs and near real-time inference speeds ideal for practical IoT systems.

As Geographic Information Systems (GIS) increasingly facilitate the analysis and sharing of geospatial data, the protection of sensitive information becomes paramount. This research explores the implementation of anonymization and differential privacy techniques to enhance security in GIS. Anonymization methods effectively remove or obscure personally identifiable information from geospatial datasets, while differential privacy introduces a mathematical framework that allows for the sharing of aggregate data without compromising individual privacy. This study evaluates the strengths and weaknesses of these techniques, demonstrating their effectiveness in maintaining the utility of geospatial data while safeguarding sensitive information. Through case studies and comparative analysis, we provide insights into best practices for integrating these privacy-preserving strategies into GIS applications, ensuring compliance with legal regulations and fostering public trust in geospatial technologies.

The on-site inspection provisions in many current and proposed arms control agreements require extensive preparation and training on the part of both the Inspected Party and the Inspection Team. Current training techniques include table-top inspections and practice inspections. The Augmented Computer Exercise for Inspection Training (ACE-IT), an interactive computer training tool, increases the utility of table-top inspections. ACE-IT has been designed to provide training for a hypothetical challenge inspection under the Chemical Weapons Convention (CWC); however, this training tool can be modified for other inspection regimes. Although ACE-IT provides training from notification of an inspection through post-inspection activities, the primary emphasis of ACE-IT is in the inspection itself--particularly with the concept of managed access. ACE-IT also demonstrates how inspection provisions impact compliance determination and the protection of sensitive information. The Exercise Manual supplements the ACE-IT software by providing general information on on-site inspections and detailed information for the CWC challenge inspection exercise. The detailed information includes the pre-inspection briefing, maps, list of sensitive items, medical records, and shipping records.

The protection of sensitive information is very important, but also a difficult task. It usually requires a centralised access policy management and control system. However, such solution is often not acceptable in the era of users’ mobility. In the paper we propose a certificate-based group-oriented encryption scheme with an effective secret sharing scheme based on general access structure. The special design of the scheme ensures that the shared secret (encryption key information), a collection of shareholders, and the access structure can be dynamically changed without the need to update the long-term keys and shares owned by shareholders. It is also possible to delegate the access rights to another member of the qualified subgroup or to a new entity from outside the current access structure.KeywordsInformation protectiongeneral access structurecryptographic access controlcertificate-based cryptosystems

This research examines the communication strategies implemented by PT DMGP in dealing with community rejection of their geothermal project on Mount Pangrango using a relational dialectic theory approach. The constructivist paradigm is used to understand that PT DMGP builds shared perceptions and understanding through dynamic interactions with stakeholders. This study uses qualitative methods with in-depth interviews with key stakeholders, including company representatives, local government, police, military and community. Analysis of PT DMGP's corporate communications (corcom) shows that their strategy consists of elements of contradiction, movement, totality and praxis which have proven effective in creating constructive dialogue. Contradictory strategy in the form of an information strategy that successfully manages the tension between transparency (openness) and the protection of sensitive information (closedness) by providing information through online portals, periodic reports and open dialogue forums. The strategic movement, in the form of a persuasive strategy, balances predictable information (predictability) and interesting new information (novelty) through regular meetings, thereby increasing community understanding and support for the project. Stakeholder mapping is also used to identify the needs and roles of each stakeholder, so that communication strategies can be adjusted to their expectations. The strategy of totality and praxis, through dialogue strategies, maintains certainty and brings uncertainty closer by involving a neutral third party for mediation, ensuring fair and transparent communication. The research results show that this communication strategy strengthens relationships between companies and communities and creates a solid foundation for the success of geothermal projects

Quantitative Information Flow (QIF) and Differential Privacy (DP) are both concerned with the protection of sensitive information, but they are rather different approaches. In particular, QIF considers the expected probability of a successful attack, while DP (in both its standard and local versions) is a max-case measure, in the sense that it is compromised by the existence of a possible attack, regardless of its probability. Comparing systems is a fundamental task in these areas: one wishes to guarantee that replacing a system A by a system B is a safe operation that is the privacy of B is no worse than that of A. In QIF, a refinement order provides strong such guarantees, while, in DP, mechanisms are typically compared w.r.t. the privacy parameter ε in their definition. In this paper, we explore a variety of refinement orders, inspired by the one of QIF, providing precise guarantees for max-case leakage. We study simple structural ways of characterising them, the relation between them, efficient methods for verifying them and their lattice properties. Moreover, we apply these orders in the task of comparing DP mechanisms, raising the question of whether the order based on ε provides strong privacy guarantees. We show that, while it is often the case for mechanisms of the same “family” (geometric, randomised response, etc.), it rarely holds across different families.

Shamir’s encryption method is to share a secret image by n number of shadow images and then r shadow images can be used to obtain the original secret image. In proposed method, the size of secret image is greater than the size of the shadow image used for the encryption. Such shadow image is beneficial to process in image hiding, transmission, or storage. For this purpose Shamir’s encryption technique is used in this proposed work. In Shamir’s encryption technique, author used the equation to encrypt the data into multiple parts. In the equation, time required for the multiplication and division of the input components of the data is more than addition and subtraction. Hence, the encryption time is little bit high. To reduce this encryption and decryption time, Shamir’s equation is modified by converting all the multiplication part into addition and division parts into subtraction in this proposed work.

Cet article decrit, du point de vue d'un clinicien generaliste, une solution pour l'implementation de dossiers concernant les patients en toute securite, ainsi que les strategies mises en place pour cette implementation. Cet article souligne donc l'importance de la securite pour la confidentialite de ces dossiers, mais aussi la difficulte de mettre en place un systeme de protection de l'information sur

Privacy-preserving data science in healthcare has become increasingly important as the industry shifts towards data-driven decision-making. Privacy refers to the protection of sensitive patient information from unauthorized access, misuse, or disclosure. Maintaining confidentiality while allowing meaningful analysis poses a significant challenge as the healthcare data volume and complexity keep rising. Traditional privacy protection methods such as encryption, anonymization, and access control have been widely used but often fail to maintain data utility or prevent advanced re-identification attacks. Emerging privacy-preserving techniques such as federated learning, homomorphic encryption, differential privacy, and secure multi-party computation provide innovative solutions by enabling collaborative model training and analysis without compromising individual data privacy. These models are important in the healthcare domain, where decentralized data and strict privacy regulations limit data sharing. The objective of this study is to systematically review and analyze these privacy-preserving techniques in healthcare, identify their strengths and limitations, and suggest directions for future improvement. The findings indicate that while these methods enhance confidentiality and enable distributed analytics, they still face challenges related to computational overhead, interoperability, and scalability. This literature-based study explores the development of privacy-preserving data science methods, discusses the limitations of existing techniques, and highlights the need for robust, secure, and ethical data science frameworks in healthcare.

The MPEG-21 Multimedia Framework provides for controlled distribution of multimedia works through its Intellectual Property Management and Protection (IPMP) Components and Rights Expression Language (MPEG REL). The IPMP Components provide a framework by which the components of an MPEG-21 digital item can be protected from undesired access, while MPEG REL provides a mechanism for describing the conditions under which a component of a digital item may be used and distributed. This chapter describes how the IPMP Components and MPEG REL were used to implement a series of digital rights management applications at the Cooperative Research Centre for Smart Internet Technology in Australia. While the IPMP Components and MPEG REL were initially designed to facilitate the protection of copyright, the applications also show how the technology can be adapted to the protection of private personal information and sensitive corporate information.