In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

The strong and controllable chemical sensitivity of organic semiconductors (OSCs) and the amplification capability of transistors in circuits make use of OSC-based field-effect transistors compelling for chemical sensors. Analytes detected and assayed range from few-atom gas-phase molecules that may have adverse health and security implications to biomacromolecules (proteins, nucleic acids) that may be markers for physiological processes and medical conditions. This review highlights recent progress in organic field-effect transistor (OFET) chemical sensors, emphasizing advances from the past 5 years and including aspects of OSC morphology and the role of adjacent dielectrics. Design elements of the OSCs and various formats for the devices are illustrated and evaluated. Challenges associated with the present state of the art and future opportunities are also discussed.

Chemical and Biomolecule Sensing with Organic Field-Effect Transistors

Security and privacy issues in e-health cloud-based system: A comprehensive content analysis

Background: Blockchain has the potential to disrupt the current modes of patient data access, accumulation, contribution, exchange, and control. Using interoperability standards, smart contracts, and cryptographic identities, patients can securely exchange data with providers and regulate access. The resulting comprehensive, longitudinal medical records can significantly improve the cost and quality of patient care for individuals and populations alike. Objective: This work presents HealthChain, a novel patient-centered blockchain framework. The intent is to bolster patient engagement, data curation, and regulated dissemination of accumulated information in a secure, interoperable environment. A mixed-block blockchain is proposed to support immutable logging and redactable patient blocks. Patient data are generated and exchanged through Health Level-7 Fast Healthcare Interoperability Resources, allowing seamless transfer with compliant systems. In addition, patients receive cryptographic identities in the form of public and private key pairs. Public keys are stored in the blockchain and are suitable for securing and verifying transactions. Furthermore, the envisaged system uses proxy re-encryption (PRE) to share information through revocable, smart contracts, ensuring the preservation of privacy and confidentiality. Finally, several PRE improvements are offered to enhance performance and security. Methods: The framework was formulated to address key barriers to blockchain adoption in health care, namely, information security, interoperability, data integrity, identity validation, and scalability. It supports 16 configurations through the manipulation of 4 modes. An open-source, proof-of-concept tool was developed to evaluate the performance of the novel patient block components and system configurations. To demonstrate the utility of the proposed framework and evaluate resource consumption, extensive testing was performed on each of the 16 configurations over a variety of scenarios involving a variable number of existing and imported records. Results: The results indicate several clear high-performing, low-bandwidth configurations, although they are not the strongest cryptographically. Of the strongest models, one’s anticipated cumulative record size is shown to influence the selection. Although the most efficient algorithm is ultimately user specific, Advanced Encryption Standard–encrypted data with static keys, incremental server storage, and no additional server-side encryption are the fastest and least bandwidth intensive, whereas proxy re-encrypted data with dynamic keys, incremental server storage, and additional server-side encryption are the best performing of the strongest configurations. Conclusions: Blockchain is a potent and viable technology for patient-centered access to and exchange of health information. By integrating a structured, interoperable design with patient-accumulated and generated data shared through smart contracts into a universally accessible blockchain, HealthChain presents patients and providers with access to consistent and comprehensive medical records. Challenges addressed include data security, interoperability, block storage, and patient-administered data access, with several configurations emerging for further consideration regarding speed and security.

/pdf/a-blockchain-framework-for-patient-centered-health-records-1o8jbjhvwp.pdf

A Blockchain Framework for Patient-Centered Health Records and Exchange (HealthChain): Evaluation and Proof-of-Concept Study

Distributed machine learning cloud teleophthalmology IoT for predicting AMD disease progression

Cost-effective secure E-health cloud system using identity based cryptographic techniques

Summary
Private set intersection (PSI) protocols enable 2 parties to compute the intersection of their inputs without compromising anything about the datasets beyond the intersection. With the advent of cloud computing, outsourcing computation has been attracted wide range of attention from research community and applied widely in the industry. The cloud computing allows resources restrained devices to outsource their expensive computation to the cloud. Based on Abadi's O-PSI, we present a variant of delegated private set intersection protocol secure in the semi-honest model under RSA assumption, and we also give an efficient and secure outsourcing computation algorithm for RSA cryptosystem. Depending on this algorithm, we transform a variant of delegated private set intersection protocol into an improved outsourced one. It enables the clients only to perform simple modular multiplication for computing what they want during the execution of protocol. Besides, the variant of delegated protocol can be easily extended to multiple clients. Compared with the state of the art, our proposed protocol has great advantage in efficiency. We finally evaluate these protocols and prove their security in the semi-honest model.

Improved outsourced private set intersection protocol based on polynomial interpolation

Nowadays, it is very popular to make friends, share photographs, and exchange news throughout social networks. Social networks widely expand the area of people’s social connections and make communication much smoother than ever before. In a social network, there are many social groups established based on common interests among persons, such as learning group, family group, and reading group. People often describe their profiles when registering as a user in a social network. Then social networks can organize these users into groups of friends according to their profiles. However, an important issue must be considered, namely many users’ sensitive profiles could have been leaked out during this process. Therefore, it is reasonable to design a privacy-preserving friends-finding protocol in social network. Toward this goal, we design a fuzzy interest matching protocol based on private set intersection. Concretely, two candidate users can first organize their profiles into sets, then use Bloom filters to generate new data structures, and finally find the intersection sets to decide whether being friends or not in the social network. The protocol is shown to be secure in the malicious model and can be useful for practical purposes.

/pdf/a-privacy-preserving-fuzzy-interest-matching-protocol-for-5ay1lsmdzj.pdf

A privacy-preserving fuzzy interest matching protocol for friends finding in social networks

The invention relates to a privacy set intersection calculation method capable of resisting a hostile attack. The method comprises the following steps of that 1), a client and a server establishes parameters; 2), the client sends a request to the server, and the server verifies an identity of the client; 3), the server sends data to the client according to the request of the client; and 4), the client calculates an intersection part with a data set of the server according to a protocol. According to the method, confidentiality, completeness and availability are satisfied at the same time. According to privacy set intersection (PSI) provided by the invention, on the premise of ensuring the privacy security of two parties, an intersection of data sets of the two parties is calculated, only one party can calculate intersection elements, the other party cannot calculate the intersection, both of the two parties cannot obtain or speculate any set element except the intersection of the opposite party, and the security and secrecy participating in the sensitive information of the two parties are ensured.

Privacy set intersection calculation method capable of resisting hostile attack

Whereas existing ecology of crime research frequently uses a cross-sectional design, an open question is whether theories underlying such studies will operate similarly in longitudinal research. Using latent trajectory models and longitudinal data in half-mile egohoods from the Southern California region over a 10-year period (2000–2010), we explore this question and assess whether the changes in key measures of social disorganization theory are related to changes in violent or property crime through three possible relationships: 1) a monotonic relationship, 2) an asymmetric relationship, and 3) a perturbation relationship in which any change increases crime. We find evidence that measures can exhibit any of these three possible relationships, highlighting the importance of not assuming monotonic relationships. Most frequently observed are asymmetric relationships, which we posit are simultaneously capturing more than one theoretical process of neighborhoods and crime. Specific findings include asymmetric relationships between change in concentrated disadvantage, racial/ethnic minority composition, or population and violent crime, as well as relationships between change in Asian composition or population and property crime. We consider how this strategy opens a needed area of future research assessing how measures for other theories operate as environments change. 

/pdf/improving-or-declining-what-are-the-consequences-for-changes-2hfgjhaw.pdf

Xiaoshuang Luo

Papers

Cost-effective secure E-health cloud system using identity based cryptographic techniques

Improved outsourced private set intersection protocol based on polynomial interpolation

A privacy-preserving fuzzy interest matching protocol for friends finding in social networks

Privacy set intersection calculation method capable of resisting hostile attack

Improving or declining: What are the consequences for changes in local crime?*