Business Process Management (BPM) includes methods, techniques, and tools to support the design, enactment, management, and analysis of operational business processes. It can be considered as an extension of classical Workflow Management (WFM) systems and approaches. Although the practical relevance of BPM is undisputed, a clear definition of BPM and related acronyms such as BAM, BPA, and STP are missing. Moreover, a clear scientific foundation is missing. In this paper, we try to demystify the acronyms in this domain, describe the state-of-the-art technology, and argue that BPM could benefit from formal methods/languages (cf. Petri nets, process algebras, etc.).

Business Process Management: A Survey

Nowadays, health insurance has become an essential part of people’s lives as the number of health issues increases. Healthcare emergencies can be troublesome for people who can’t afford huge expenses. Health insurance helps people cover healthcare services expenses in case of a medical emergency and provides financial backup against indebtedness risk. Health insurance and its several benefits can face many security, privacy, and fraud issues. For the past few years, fraud has been a sensitive issue in the health insurance domain as it incurs high losses for individuals, private firms, and governments. So, it is essential for national authorities and private firms to develop systems to detect fraudulent cases and payments. A high volume of health insurance data in electronic form is generated, which is highly sensitive and attracts malicious users. Motivated by these facts, we present a systematic survey for Artificial Intelligence (AI) and blockchain-enabled secure health insurance fraud detection in this paper. This paper presents a taxonomy of various security issues in health insurance. We proposed a blockchain and AI-based secure and intelligent system to detect health insurance fraud. Then, a case study related to health insurance fraud is presented. Finally, the open issues and research challenges in implementing the blockchain and an AI-empowered health insurance fraud detection system is presented.

/pdf/blockchain-and-ai-empowered-healthcare-insurance-fraud-2r9ym6tz.pdf

Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: an Analysis, Architecture, and Future Prospects

A privacy server protects private information by substituting a token or an identifier for the private information. The privacy server recognizes that a communication includes private information and intercepts the communication. The privacy server replaces the private information with a random or pseudo-random token or identifier. The privacy server maintains the private information in a local database and associates the private information for a particular person with the token or identifier for that person.

Privacy server for protecting personally identifiable information

Techniques described herein provide data access and data anonymity management within various implementations of content distribution networks. In some embodiments, a data anonymity management system may include multiple different data stores configured to store identity data, user data, and/or linking data, as well as a data anonymity server configured to support data anonymity features such as active user data anonymity, one-way linking and permanently breakable links between user identity data and associated user data. In some embodiments, storage systems and techniques may be used for storing identity data, user data, and link data in multiple different data stores, with different data storage requirements and different processes and policies for data availability, data backup, online disaster recovery, offline storage archiving, and the like. Additionally, cryptographic hash functions may be used to implement one-way encryption between identity data and user data.

Data access and anonymity management

A method comprises receiving a first cryptographic token for one search term and a second cryptographic token is generated using the one search term and at least another search term. A first search is conducted using the first cryptographic token to generate a first result set, and the second cryptographic token is used for computing a subset of results of the first result set.

Conjunctive search in encrypted data

The average costs of data leakage are steadily on the rise. As a consequence, several data security and access control mechanisms have been introduced, ranging from data encryption to intrusion detection or role-based access control, doing a great work in protecting sensitive information. However, the majority of these concepts are centrally controlled by administrators, who are one of the major threats to corporate security. This work presents a security protocol for data privacy that is strictly controlled by the data owner. Therefore, we integrate pseudonymization and encryption techniques to create a methodology that uses pseudonyms as access control mechanism, protects secret cryptographic keys by a layer-based security model, and provides privacy-preserving querying.

/pdf/pseudonymization-with-metadata-encryption-for-privacy-4l0rh05gih.pdf

Pseudonymization with Metadata Encryption for Privacy-Preserving Searchable Documents

In this article we define a new type of integrity constraint in XML, called an XML inclusion constraint (XIND), and show that it extends the semantics of a relational inclusion dependency. This property is important in areas such as XML publishing and `data-centric' XML, and is one that is not possessed by other proposals for XML inclusion constraints. We also investigate the implication and consistency problems for XINDs in complete XML documents, a class of XML documents that generalizes the notion of a complete relation, and present an axiom system that we show to be sound and complete.

Inclusion Dependencies in XML: Extending Relational Semantics

The average costs of data leakage are steadily on the rise. Especially in healthcare, the disclosure of sensitive information may have unfavorable consequences for the patient. As a consequence, several data security and access control mechanisms have been introduced, ranging from data encryption to intrusion detection or role-based access control, doing a great work in protecting sensitive information. However, the majority of these concepts are centrally controlled by administrators who are a major threat to the patients’ privacy. Apart from administrators, other internal persons, such as hospital staff members, may exploit their access rights to snoop around in private health data. This work presents PERiMETER, a security protocol for data privacy that is strictly controlled by the data owner. It integrates pseudonymization and encryption to create a methodology that uses pseudonyms as access control mechanism, protects secret cryptographic keys by a layer-based security model, and provides privacy-preserving querying.

https://link.springer.com/content/pdf/10.1057%2Fhs.2012.5.pdf

PERiMETER – pseudonymization and personal metadata encryption for privacy-preserving searchable documents

Federated Health Information Systems (FHIS) integrate autonomous information systems of participating health care providers to facilitate the exchange of Electronic Health Records (EHR), which improve the quality and efficiency of patients’ care. However, the main problem with collecting and maintaining the sensitive data in electronic form is the issue of preserving data confidentiality and patients’ privacy. Although multiple technical measures to restrict access to only authorized persons are implemented, they are usually aimed against external attackers. In this work, we propose to integrate pseudonymization and encryption to a hybrid approach which not only protects against external attackers, but also ensures that even potential internal attackers with full data access, like administrators, cannot gain any useful information.

/pdf/a-hybrid-approach-integrating-encryption-and-19vatulu3u.pdf

A hybrid approach integrating encryption and pseudonymization for protecting electronic health records

Schema-aware labelling of XML documents for efficient query and update processing in SemCrypt.

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