One-way Hash Algorithm Research Articles

Abstract P365: Prevalence of Hypertension in Minnesota Adults in 2023 Using Data from a Statewide Electronic Health Record Consortium

Background: Data on prevalence of hypertension in the United States come primarily from in-person data collected by the National Health and Nutrition Examination Survey and self-reports in the Behavioral Risk Factor Surveillance Survey. Electronic phenotypic algorithms for hypertension that include diagnosis codes, blood pressure values, and antihypertensive treatment have been proposed and tested. Objective: To describe prevalence of hypertension in Minnesota adults using data from a statewide electronic health record (EHR) consortium, the Minnesota EHR Consortium (MNEHRC). Methods: Data from 11 health systems participating in the MNEHRC were standardized to a common data model allowing for distributed querying of EHR data. Data were de-duplicated using a one-way hash algorithm. Preliminary prevalence of hypertension in 2023 was estimated in Minnesota residents with ≥ 1 encounter in the past 3 years who had ≥1 diagnosis of hypertension in the past 5 years. Medicaid insurance status was determined via linkage with state enrollment files. Residential addresses of patients were geocoded to census tracts and social vulnerability index (SVI) of census tracts was determined. Results: Among 4,369,470 Minnesotan age 18 and older in 2023, 23.6% had hypertension based on ≥1 diagnosis code. Prevalence increased with age, was higher in men (26% vs. 22% in women), and adjusted for age and sex was highest in Black (30%) and Native American (27%) compared with White (23%) and Hispanic (21%) Minnesotans. Within each race/ethnic group, those insured by Medicaid had a higher adjusted hypertension prevalence than those with other insurance types. The prevalence of hypertension in census tracts with moderate to high SVI ranged from 3% to 43%, but on average was similar to the statewide prevalence of 24% (see image 1). Prevalence of hypertension in race/ethnicity, sex, and age subgroups in higher SVI census tracts was similar to the statewide prevalence in those subgroups. Conclusions: The prevalence of hypertension in Minnesota was described in detail by demographic characteristics, geography and social vulnerability. Future work will expand the electronic hypertension phenotype and examine quality of care.

A privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing

To ensure the image security, a large number of ciphertext image retrieval methods have been studied and applied, such as homomorphic encryption and multi-key encryption. However, most of these algorithms do not consider the protection of image copyright, user information and traitor tracking. For this reason, this paper proposes a privacy-preserving and traitor tracking content-based image retrieval scheme in cloud computing. This method introduces the DenseNet network to strengthen statistical features. One-way hash algorithm and XOR operation are used to protect copyright and user information, and reversible information hiding algorithm is accessed for traitor tracking. Experimental results show that compared with other algorithms that support leak tracking, our method achieves higher retrieval precision, higher retrieval efficiency and simpler architecture.

A lightweight cryptography (LWC) framework to secure memory heap in Internet of Things

The extensive networking of devices and the large amount of data generated from the Internet of Things (IoT) has brought security issues to the attention of the researcher. Java is the most common platform for embedded applications such as IoT, Wireless Sensors Networks (WSN), Near Field Communications (NFC) and Radio Frequency Identification (RFID). The object programming languages such as Java, SWIFT, PHP and C++ use garbage collection after any object run which creates security loophole for attacks such as Next Memory Address Occupation (NMAO), memory replay, Learning Tasks Behaviors (LTB). The security risk increases in IoT when attacks exceeds the target device to the surrounding connected devices. Inappropriate or wrong operations causes energy loss and increased costs. In this paper, a security method to protect IoT system operation from memory heap penetration and address modification attack is proposed. The proposed method prevents directed attack by encrypting the object Garbage Collection at run time. To form a unique signature mechanism, the Cryptographic Hash Function (CHF) which employs a specific one-way hash algorithm. The proposed framework uses L-function based ECC and one-time Key (OTK) to secure the memory heap. Our method is used with open system where the effect on the operating system is not considered. The proposed method proved to be powerful and efficient which can help in achieving higher levels of security across several IoT applications, by enabling better detection of malicious attacks.

Analytical Performance of Modified One-Way Hash Algorithm for Data Integrity Verification in Cloud Computing

Cloud computing is a revolution in the IT industry due to its characteristics of scalability, efficiency, and availability. Along with these benefits, cloud computing comes with certain security issues that a user has to take into consideration. Security of data and its integrity verification in the cloud are major issues that act as a barrier to the adoption of cloud computing. In the authors' previously published work, a one-way hash function was proposed to verify the data integrity at the cloud storage site. This article further extends prior work. In this article, the modified one-way hash algorithm is implemented by using a Hadoop distributed file system (HDFS) service of Hadoop environment and analytical testing is performed to ascertain its performance. Statistical and experimental results reveal the proposed algorithm is robust, which ensures data integrity and fulfills mostly all essential features of a secure hash function.

Checking Questionable Entry of Personally Identifiable Information Encrypted by One-Way Hash Transformation.

BackgroundAs one of the several effective solutions for personal privacy protection, a global unique identifier (GUID) is linked with hash codes that are generated from combinations of personally identifiable information (PII) by a one-way hash algorithm. On the GUID server, no PII is permitted to be stored, and only GUID and hash codes are allowed. The quality of PII entry is critical to the GUID system.ObjectiveThe goal of our study was to explore a method of checking questionable entry of PII in this context without using or sending any portion of PII while registering a subject.MethodsAccording to the principle of GUID system, all possible combination patterns of PII fields were analyzed and used to generate hash codes, which were stored on the GUID server. Based on the matching rules of the GUID system, an error-checking algorithm was developed using set theory to check PII entry errors. We selected 200,000 simulated individuals with randomly-planted errors to evaluate the proposed algorithm. These errors were placed in the required PII fields or optional PII fields. The performance of the proposed algorithm was also tested in the registering system of study subjects.ResultsThere are 127,700 error-planted subjects, of which 114,464 (89.64%) can still be identified as the previous one and remaining 13,236 (10.36%, 13,236/127,700) are discriminated as new subjects. As expected, 100% of nonidentified subjects had errors within the required PII fields. The possibility that a subject is identified is related to the count and the type of incorrect PII field. For all identified subjects, their errors can be found by the proposed algorithm. The scope of questionable PII fields is also associated with the count and the type of the incorrect PII field. The best situation is to precisely find the exact incorrect PII fields, and the worst situation is to shrink the questionable scope only to a set of 13 PII fields. In the application, the proposed algorithm can give a hint of questionable PII entry and perform as an effective tool.ConclusionsThe GUID system has high error tolerance and may correctly identify and associate a subject even with few PII field errors. Correct data entry, especially required PII fields, is critical to avoiding false splits. In the context of one-way hash transformation, the questionable input of PII may be identified by applying set theory operators based on the hash codes. The count and the type of incorrect PII fields play an important role in identifying a subject and locating questionable PII fields.

An Energy Efficient Data Secrecy Scheme For Wireless Body Sensor Networks

Data secrecy is one of the key concerns for wireless body sensor networks (WBSNs). Usually, a data secrecy scheme should accomplish two tasks: key establishment and encryption. WBSNs generally face more serious limitations than general wireless networks in terms of energy supply. To address this, in this paper, we propose an energy efficient data secrecy scheme for WBSNs. On one hand, the proposed key establishment protocol integrates node IDs, seed value and nonce seamlessly for security, then establishes a session key between two nodes based on one-way hash algorithm SHA-1. On the other hand, a low-complexity threshold selective encryption technology is proposed. Also, we design a security selection patter exchange method with low-complexity for the threshold selection encryption. Then, we evaluate the energy consumption of the proposed scheme. Our scheme shows the great advantage over the other existing schemes in terms of low energy consumption.

One-way hash algorithm based on chaotic coupled dynamic parameters

Combining the advantages of chaotic coupled system and conventional one-way hash algorithm, a new keyed one-way hash function was presented. In the proposed approach, chaotic coupled system was made by Tent map and Logistic chaotic map, which produced chaotic data as dynamic parameters that replaced the fixed parameters of conventional hash function. The experimental results show that this method has large key space, strong one-way property, and sensitivity to the initial conditions and keys.

Threshold protocol for the exchange of confidential medical data.

BackgroundMedical researchers often need to share clinical data without violating patient confidentiality. Threshold cryptographic protocols divide messages into multiple pieces, no single piece containing information that can reconstruct the original message. The author describes and implements a novel threshold protocol that can be used to search, annotate or transform confidential data without breaching patient confidentiality.MethodsThe basic threshold protocol is: 1) Text is divided into short phrases; 2) Each phrase is converted by a one-way hash algorithm into a seemingly-random set of characters; 3) Threshold Piece 1 is composed of the list of all phrases, with each phrase followed by its one-way hash; 4) Threshold Piece 2 is composed of the text with all phrases replaced by their one-way hash values, and with high-frequency words preserved. Neither Piece 1 nor Piece 2 contains information linking patients to their records. The original text can be re-constructed from Piece 1 and Piece 2.ResultsThe threshold algorithm produces two files (threshold pieces). In typical usage, Piece 2 is held by the data owner, and Piece 1 is freely distributed. Piece 1 can be annotated and returned to the owner of the original data to enhance the complete data set. Collections of Piece 1 files can be merged and distributed without identifying patient records. Variations of the threshold protocol are described. The author's Perl implementation is freely available.ConclusionsThreshold files are safe in the sense that they are de-identified and can be used for research purposes. The threshold protocol is particularly useful when the receiver of the threshold file needs to obtain certain concepts or data-types found in the original data, but does not need to fully understand the original data set.