Secure Message Research Articles

Expanding Naloxone Coprescribing at a Regional VA Medical Center.

Veterans are disproportionately affected by chronic pain and are more likely to be prescribed opioids. As a means of risk mitigation, the Centers for Disease Control and Prevention and Department of Defense recommend naloxone for patients on opioids with risk factors, including use of ≥50 morphine milligram equivalents daily, concurrent benzodiazepine/sedative use, and pulmonary or liver disease. An interprofessional quality improvement team consisting of 6 residents, a pharmacist, a nurse educator, and a faculty mentor was formed to increase naloxone coprescriptions at a regional VA medical center Continuity of Care Clinic. Primary intervention identified eligible patients via the VA Primary Care Almanac's Opioid Therapy Risk Report and alerted providers by email and secure messaging. Naloxone coprescription rates increased from 42% initially in June 2022 to 82% by June 2023 (29/69 to 41/50 patients, P < 0.0001). This project demonstrates that notifying providers of high-risk patients can significantly increase naloxone coprescriptions.

The Impact and Future of Teletherapy in Mental Health Support

Teletherapy, a digital form of mental health support, has become an essential aspect of psychological care, driven by technological advancements and evolving societal needs. This paper examines the evolution, benefits, and challenges of teletherapy, emphasizing its accessibility, especially for underserved populations. It highlights innovations such as artificial intelligence (AI) and secure messaging and discusses ethical considerations like confidentiality and informed consent. Despite limitations, such as technical barriers and reduced non-verbal communication, teletherapy is poised to grow, offering flexible, accessible mental health services. The future of teletherapy will likely see further integration with emerging technologies, potentially reshaping the landscape of mental health care. Keywords: Teletherapy, mental health support, digital therapy, online therapy, telehealth, accessibility.

Message Authentication Scheme on Light Weight Parallel Encryption Model With Digit Artithmetic of Covertext using Secure Hash Algorithm

This research aims to enhance message security by developing a Light Weight Parallel Digit Arithmetic of Covertext (PDAC) encryption-based authentication scheme that adopts the Secure Hash Algorithm (SHA) algorithm to ensure message integrity and authentication aspects. Through experiments, tests are conducted on two main aspects: entropy and collision resistance. The experimental results show that the average entropy generated reaches 4.992, or 62.41% of the optimal entropy value. While this result shows a good randomness, there is room for further improvement to reach the optimal level. Collision resistance testing using Google's SHAttered tool showed very positive results. No collisions were found in any of the samples tested, indicating that the PDAC scheme combined with SHA can maintain message integrity well. This indicates that PDAC has strong resistance to hash-based attacks, ensuring that messages remain authentic and safe from manipulation. Thus, this study concludes that PDAC schemes offer a good balance between efficiency, security, and low power consumption, making it suitable for use in resource-constrained environments such as IoT devices and mobile applications

Enhancing network security with hybrid feedback systems in chaotic optical communication

This paper presents a pioneering approach to bolstering network security and privacy by implementing chaotic optical communication with a hybrid optical feedback system (HOFS). The current baseline methods in network security are often less feasible for hybrid feedback systems, including limited robustness, compromised security, and synchronization challenges. Therefore, this paper proposes a hybrid approach to address these shortcomings by integrating the HOFS into chaotic optical communication systems (HOFS-COCS) to overcome the baseline challenges. This paper aims to improve network security while significantly maintaining efficient communication channels. Moreover, We designed two algorithms, one for chaotic maps generation and another for text encryption and decryption, to improve security in the hybrid feedback system. Our findings demonstrate through rigorous experimentation and analysis that the proposed (HOFS-COCS) method significantly improves network security by enabling reliable chaos generation, synchronization, and secure message transmission in chaotic optical communication systems. This research represents a significant advancement towards enhanced secrecy and synchronization in chaotic optical communication systems, promising a paradigm shift in network security protocols.

Application of Cryptography and Steganography Techniques to Improving the Security of Text Messages with RC4 Algorithm and MSB Method

This study discusses the application of cryptography and steganography techniques to improve the security of text messages using the Rivest Code 4 (RC4) algorithm and the Most Significant Bit (MSB) method. In the ever-growing digital era, data security is a top priority due to the increasing threat of cybercrime that can harm many parties. RC4 is a cryptography algorithm known for its encryption and decryption speed, while the MSB method is an effective steganography technique for hiding information in digital images. This study aims to develop an application that is able to encrypt text messages with the RC4 algorithm and hide them in digital images using the MSB method. With this combination, data is not only encrypted but also hidden, thus providing two layers of security to protect information from unauthorized access. The results of the study show that the combination of RC4 cryptography and MSB steganography techniques successfully improves data security well. The developed application is able to protect sensitive information from the risk of data theft and cyber attacks. In addition, this technique is also easy to implement and can be applied in various sectors, such as banking, health, and business communications, to protect sensitive data from unauthorized access. Keywords: Cryptography, Steganography, Most Significant Bit (MSB)

Churning the tides of care: when nurse turnover makes waves in patient access to primary care

BackgroundTeam-based primary care (PC) enhances the quality of and access to health care. The Veterans Health Administration (VHA) implements team-based care through Patient Aligned Care Teams (PACTs), consisting of four core members: a primary care provider, registered nurse (RN) care manager, licensed vocational nurse, and scheduling clerk. RNs play a central role: they coordinate patient care, manage operational needs, and serve as a patient point of contact. Currently, it is not known how varying levels of RN staffing on primary care teams impact patient outcomes.ObjectiveThis study aims to empirically assess how the stability of RN staffing within team-based primary care affects patient access to care.MethodsA retrospective database review using clinical and administrative data from the VHA over 24 months. Participants included 5,897 PC PACTs across 152 VHA healthcare facilities in the United States and its territories. The stability of personnel in the RN role was categorized as: RN continuous churn, RN staffing instability and RN vacancy. All 3 categories were compared to teams with RN stability (i.e., same person in the role for the entire 24-month period). Access measures included: average third-next-available appointment, established patient average wait time in days, urgent care utilization, emergency room utilization, and total inbound-to-outbound PC secure messages ratio.ResultsRN continuous churn within PACTs had a significant impact on third-next-available appointment (b = 3.70, p < 0.01). However, RN staffing instability and vacancy had no significant relationship with any of the access measures. Several risk adjustment variables, including team full-time equivalency, team stability, relative team size, and average team size, were significantly associated with access to health care.ConclusionsTeams are impacted by churn on the team. Adequate staffing and team stability significantly predict patient access primary care services. Healthcare organizations should focus on personnel retention and strategies to mitigate the impact(s) of continuous RN turnover. Future research should examine the relative impact of turnover and stability of other roles (e.g., clerks) and how team members adapt to personnel changes.

Enhancing Syslog Message Security and Reliability over Unidirectional Fiber Optics

Standard log transmission protocols do not offer a robust way of segregating the log network from potential threats. A secure log transmission system and the realization of a data diode using affordable components are proposed. Unidirectional data flow prevents unauthorized access and eavesdropping, ensuring the integrity and confidentiality of sensitive log data. The system uses an encryption protocol that requires that the upstream and the downstream of the data diode are perfectly synchronized, mitigating replay attacks. It has been shown that message amplification can mitigate UDP packet loss, but this is only required when the data diode traffic is congested. The implementation of the encryption algorithm is suitable for resource-constrained devices and it has been shown to produce random-looking output even on a reduced number of rounds when compared to the parent cipher. Several improvements have been made to the original encryption algorithm for which an actual implementation was missing. Free software and datasets have been made available to reproduce the results. The complete solution is easy to reproduce in order to secure the segregation of a log network inside any scenario where logging is required by the law and log tampering must be prevented.

Academic hospitalist perspectives on the benefits and challenges of secure messaging: A mixed methods analysis.

Hospitals and patients rely on effective clinician communication. Asynchronous electronic secure messaging (SM) systems are a common way for hospitalists to communicate, but few studies have evaluated how hospitalists are navigating the adoption of SM and the benefits and challenges they are encountering. The objective of this study is to assess academic hospitalist perspectives on SM to guide future research and quality improvement initiatives. This was a mixed methods study utilizing an embedded REDCap survey and six virtual semistructured focus groups. It took place during a Hospital Medicine ReEngineering Network Zoom meeting on October 13, 2023. Rapid qualitative methods were used to define major themes. There were 28 hospitalists and one patient representative across 24 separate academic institutions. There was a 71% survey completion rate (N = 20). SM was felt to be an effective and efficient communication modality but was associated with a large amount of multitasking and interruptions. Perspectives around SM clustered around three main themes: SM has been widely but variably adopted; there is a lack of institutional guidance about how to best engage with SM; and SM is changing the landscape of hospitalist work by increasing ease but decreasing depth of communication, increasing cognitive load, and changing interpersonal relationships. Recommendations for SM improvements included the need for institutions to work with frontline workers to develop and implement clear usage guidelines. SM is likely contributing to both positive and negative effects for clinicians and patients. Understanding hospitalist perspectives on SM will help guide future research and quality improvement initiatives.

Ensuring precision medicine for veterans with lung cancer: A randomized clinical trial.

178 Background: National guidelines recommend molecular testing for patients with non-small cell lung cancer, yet this is not routinely completed in practice. In prior work, we identified barriers to testing in the Veterans Affairs. First, physicians are unaware if and when testing has occurred. Second, patients are unaware of testing and the implications on treatment and clinical outcomes. In response, in collaboration with a Veteran and Caregiver Advisory Board, we created a multilevel intervention led by a peer volunteer who: 1) provides tailored education of molecular testing for 1 month for Veterans newly diagnosed with lung cancer and, 2) alerts clinicians via secure messaging if tumor samples have not been tested. We conducted this randomized clinical trial to assess whether the intervention improves patient knowledge of molecular testing and patient activation and increases receipt of molecular genomic testing compared with usual care. Methods: All veterans &gt;18 years old with a new diagnosis of any stage non-small cell lung cancer were eligible. Exclusions included inability to consent. All participants completed baseline assessments at randomization and at 1-month follow-up comprised of a 3-question validated precision medicine knowledge questionnaire and a 13-question validated patient activation measure. Genomic testing was assessed by chart review at 6-months follow-up. We used regression models to assess differences in mean knowledge and activation scores over time between groups and compared rates of genomic testing. Results: 75 Veterans were screened with 46 eligible. All 46 consented to participate, with 23 in each group. All were male (100%), had mean age of 76.3+/-5.54 years; 31 (67.4%) were Latinx; 2 (4.4%) Asian; 11 (23.9%) Black; 1 (2.2%) Native Hawaiian; 32 (69.6%) White; 32 (69.6%) had Stage 4 disease. At 1 month follow-up mean knowledge scores increased over time in the intervention group and remained stable in the control group (mean score 2.30 +/- 0.97 versus 1.16 +/- 1.15, p=0.014). At 1-month follow-up, patient activation increased for the intervention group more than the control group (46.7 +/- 11.3 versus 37.6 +/- 9.26, p=0.002). There were no significant differences in tumor testing between groups (intervention: 95.6% versus control: 86.9%, p=0.62) or time to first treatment course from biopsy (intervention: 28.2 days versus control 36.2 days). Conclusions: A volunteer led effort improved patient education regarding precision medicine and patient activation among Veterans as compared with usual care alone. Interventions that include volunteers and other support can enhance care and clinical outcomes among veterans with lung cancer. Clinical trial information: NCT05795959 .

The Medium is the Message: How Secure Messaging Apps Leak Sensitive Data to Push Notification Services

Like most modern software, secure messaging apps rely on thirdparty components to implement important app functionality. Although this practice reduces engineering costs, it also introduces the risk of inadvertent privacy breaches due to misconfiguration errors or incomplete documentation. Our research investigated secure messaging apps' usage of Google's Firebase Cloud Messaging (FCM) service to send push notifications to Android devices. We analyzed 21 popular secure messaging apps from the Google Play Store to determine what personal information these apps leak in the payload of push notifications sent via FCM. Of these apps, 11 leaked metadata, including user identifiers (10 apps), sender or recipient names (7 apps), and phone numbers (2 apps), while 4 apps leaked the actual message content. Furthermore, none of the data we observed being leaked to FCM was specifically disclosed in those apps' privacy disclosures. We also found several apps employing strategies to mitigate this privacy leakage to FCM, with varying levels of success. Of the strategies we identified, none appeared to be common, shared, or well-supported. We argue that this is fundamentally an economics problem: incentives need to be correctly aligned to motivate platforms and SDK providers to make their systems secure and private by default.

The Educational Experience Improvement Collective for Inpatient Medicine Healthcare Professional Trainees at a University-Affiliated Veterans Affairs Medical Center

Background: Rotation evaluations reflect the resident-perceived value of clinical experiences in graduate medical education. In this study, we sought to improve the quality of education for internal medicine residents during their inpatient medicine rotation. Methods: Program stakeholders critically appraised a core medicine rotation at a university-affiliated U.S. Veterans Affairs Medical Center utilizing end-of-rotation evaluations by residents. Thematic analysis identified three areas for improvement: culture, communication, and workload. Solutions were developed to address each theme: (1) site-specific orientation was provided to new trainees, (2) real-time notification of admissions occurred via secure messaging platform, and (3) an assistive rounding tool was integrated into the electronic medical record. Outcome measures of education were obtained via end-of-rotation evaluations by residents. Results: This study included 198 pre-intervention and 58 post-intervention evaluations by trainees from October 2022 through December 2023. Using a 5-point Likert scale, the quality of education improved from good to very good (3.26 to 4.02, +15%, p &lt; 0.001) over the course of one year. All four subcategories also improved: diversity/quality of pathology (0.33; +7%), supervision (0.50; +10%), workload (0.42; +8%), and learning value (0.51; +10%). When the five categories are compared immediately pre-intervention (fourth quarter of 2022-2023 academic year) to full post-intervention (second quarter of 2023-2024 academic year) using a paired t-test, the change was statistically significant (p = 0.007). Conclusions: Significant educational enhancements were achieved over time for a core rotation in a residency program using solutions developed from interconnected themes found in learner evaluations.

Information hiding using approximate POSIT representation

AbstractPOSIT is a numerical system consists of sign, regime, exponential, and fraction bits to overcome some limitations of the IEEE‐754 floating point (FP) representation. This work proposes a technique to hide critical information in the least significant bits (LSBs) of the POSIT FP representation by exploiting approximate computing (AC). The proposed technique, called information hiding using POSIT and LSB (IHUPL), explores the opportunities offered by both the POSIT representation and the AC to hide information with a minimum loss in accuracy and other performance metrics. IHUPL offers two options for hiding information: either by embedding one digit of each character into each pixel or by embedding all the digits of the character at the same time into each pixel of the alpha‐red, green, blue, or black/white image. Experimental results are evaluated for benchmark images and showed that IHUPL enhanced the accuracy of embedding data into LSB of POSIT FP by an average of 5%, the image quality improvement rates of IHUPL are 19% and 16% for options 1 and 2, respectively. Besides the encoding method using IHUPL, the paper outlines an extraction decoding technique that saves the original replacement bits in a key‐image to recover the hidden security message.

Secure messaging telehealth billing in the digital age: moving beyond time-based metrics.

We proposed adopting billing models for secure messaging (SM) telehealth services that move beyond time-based metrics, focusing on the complexity and clinical expertise involved in patient care. We trained 8 classification machine learning (ML) models using providers' electronic health record (EHR) audit log data for patient-initiated non-urgent messages. Mixed effect modeling (MEM) analyzed significance. Accuracy and area under the receiver operating characteristics curve scores generally exceeded 0.85, demonstrating robust performance. MEM showed that knowledge domains significantly influenced SM billing, explaining nearly 40% of the variance. This study demonstrates that ML models using EHR audit log data can improve and predict billing in SM telehealth services, supporting billing models that reflect clinical complexity and expertise rather than time-based metrics. Our research highlights the need for SM billing models beyond time-based metrics, using EHR audit log data to capture the true value of clinical work.

Correction to: Secure and efficient message transmission in MANET using hybrid cryptography and multipath routing technique

Correction to: Secure and efficient message transmission in MANET using hybrid cryptography and multipath routing technique

Optimising Text Steganography with Alpha-Based Representative Binary: Analysing Contain Letter Used and Capacity Ratio

Text steganography has become essential for secure communication in the digital age, offering a method to hide messages within seemingly ordinary text. This paper introduces the Alpha-based Representative Binary technique, an advanced feature-based method for text steganography. It utilizes both capital and small letters to represent 2-bit binary values, embedding more information without altering the visual integrity of the text. By assigning different binary values to uppercase and lowercase letters, this technique optimizes the balance between information density and detectability. Embedding 2-bit values strikes an ideal balance, as it allows for a higher capacity of hidden information while maintaining a low profile. This study evaluates the performance of the Alpha-based Representative Binary technique against existing methods like QUAD and One-Flow-2-bit, focusing on two metrics performance: the total character count in the stego text (contain letter used) and the amount of data that can be embedded relative to the cover text size (capacity ratio). The findings underscore the technique's strengths in maintaining secure and undetectable hidden messages within text. This paper highlights the evolution and effectiveness of feature-based methods, emphasizing the need for continued innovation to address detection risks and content modification challenges. By providing a detailed analysis and potential improvements, this paper aims to contribute to the development of more robust and undetectable text steganography systems. The perceptions gained from this paper is expected as valuable for researchers and practitioners in the field of secure communication.

Efficient Lightweight Blockchain with Hybridized Consensus Algorithm for IoT Networks

Blockchain (BC) technology has attracted a lot of interest due to its excellent security and privacy features as well as its immutability. While BC can address security and privacy challenges in IoT, it is often computationally expensive, suffers from limited scalability, and introduces bandwidth overheads and delays, making it unsuitable for IoT applications. This paper proposes a novel lightweight and scalable blockchain (LIGHT-SB) designed specifically for IoT environments. In a smart IoT ecosystem, low-resource devices benefit from a centralized manager that handles communication keys and manages requests. LIGHT-SB enhances decentralization while maintaining robust privacy and security through a hybrid consensus algorithm combining permissionless proof-of-capacity and permissioned Byzantine fault tolerance (PoC-PBFT). Secure message delivery is achieved using SHA-256 and RSA cryptographic techniques. IoT device authentication, communication, and storage are safeguarded within the network. Distributed throughput management is implemented to monitor and adjust BC usage, ensuring it remains efficient. Qualitative evaluations demonstrate that LIGHT-SB effectively mitigates several security threats.

Evaluating the SEND eHealth Application to Improve Patients' Secure Message Writing.

Secure messaging (SM) is an important aspect of communication for patients with cancer. SM fosters patient-clinician communication and helps patients with symptom management and treatment support. However, patients are uncertain about how to phrase messages appropriately and have expressed the need for guidance. In response, we designed a user-centered, web-based application named SEND The application focuses on specificity, expression, needs, and directness through interactive video tutorials and quizzes. Our objective was to comprehensively evaluate SEND based on its levels of engagement, satisfaction, acceptability, and appropriateness. We recruited 101 patients with various cancer diagnoses to use SEND and then fill out a survey 1 to 2weeks later about their experience. Patients' mean age was 64years; most were male (55%), white (83%), diagnosed with cancer in 2020 with high levels of self-efficacy, and 51% had a bachelor's degree or higher. 65% were engaged in the application, and respondents spent an average of 15min interacting with SEND Satisfaction was 90.4%, 85.4% found it acceptable, and 88.6% appropriate. There were no statistically significant differences across age, sex, race, education, or year of diagnosis. Results underscore the potential of eHealth interventions, like SEND, in enhancing patient-clinician communication in cancer care. By empowering patients with effective message-writing techniques, SEND has the potential to improve the quality of SM, which can lead to faster response times and more patient-centered responses.

Protocol for Designing a Model to Predict the Likelihood of Psychosis From Electronic Health Records Using Natural Language Processing and Machine Learning.

Rapid identification of individuals developing a psychotic spectrum disorder (PSD) is crucial because untreated psychosis is associated with poor outcomes and decreased treatment response. Lack of recognition of early psychotic symptoms often delays diagnosis, further worsening these outcomes. The proposed study is a cross-sectional, retrospective analysis of electronic health record data including clinician documentation and patient-clinician secure messages for patients aged 15-29 years with ≥ 1 primary care encounter between 2017 and 2019 within 2 Kaiser Permanente regions. Patients with new-onset PSD will be distinguished from those without a diagnosis if they have ≥ 1 PSD diagnosis within 12 months following the primary care encounter. The prediction model will be trained using a trisourced natural language processing feature extraction design and validated both within each region separately and in a modified combined sample. This proposed model leverages the strengths of the large volume of patient-specific data from an integrated electronic health record with natural language processing to identify patients at elevated chance of developing a PSD. This project carries the potential to reduce the duration of untreated psychosis and thereby improve long-term patient outcomes.

Layered security model through integration of Vigenere and Hill Cipher in digital message encryption

The rapid development of digitalization has a significant impact on data and information protection. One approach to protecting data and information is through the use of cryptography. The research aims to combine the use of Vigenere and Hill Cipher algorithms in modeling to maintain the security and confidentiality of digital messages. The focus of this research is on the process of encrypting digital text messages. The layered security in this study takes advantage of the advantages of each algorithm. The combination of the two is designed to increase the complexity of encryption and reduce vulnerability to cryptanalytic attacks. The encryption process starts with using Vigenere Cipher for initial message encrypting, then the results are re-encrypted using Hill Cipher. Research shows that this layered security model can improve data security and make it more difficult for uninterested parties to decipher it. The combination of Vigenere's and Hill Cipher's algorithms could be one of the layered security alternatives to digital message encryption in an effort to protect information and data from security threats in the digital age.

Improving cyber risk governance through storytelling

This paper addresses the critical challenge of cyber risk governance faced by executives, security committees and boards of directors in the rapidly changing digital landscape. Cyber security complexity, characterised by data deluges and the translational gap between technical jargon and business risk, significantly hinders effective cyber risk messaging and governance. Drawing on five years of research and interviews with chief information security officers (CISOs), the paper highlights the struggle in establishing trust and confidence in governance bodies due to these complexities. It introduces three constructs that aim to simplify cyber security messaging to enhance cyber risk governance: the intelligence to risk (I2R) pyramid, five risk impacts, and resilience and proximity graph. Each construct, illustrated with practical examples, is designed to provide clarity and foster understanding between cyber security professionals and governance bodies, ensuring a cohesive approach to cyber risk management. Readers can expect to gain valuable insights into overcoming the limitations of traditional risk communication tools such as risk registers. By adopting the presented storytelling approach, the paper promises strategies for building trust through transparency and accountability, bridging the communication gap between technical and executive levels, and facilitating informed decision making for improved governance outcomes in the face of cyber security threats.