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Research Article
Chatbot-Enhanced Mental Health First Aid in Corporate Settings: Addressing Risks, Implementing Crisis Management, and Promoting Employee Well-Being
Sourav Banerjee*,
Ayushi Agarwal,
Ayush Kumar Bar
Issue:
Volume 12, Issue 1, June 2024
Pages:
1-4
Received:
18 December 2023
Accepted:
29 December 2023
Published:
11 January 2024
Abstract: This research rigorously explores the implementation of Chatbot-Enhanced Mental Health First Aid (MHFA) within corporate contexts, presenting an innovative paradigm for mitigating mental health risks and bolstering employee well-being. Amidst increasing recognition of the pervasive nature of mental health challenges in the workplace, this research elucidates the potential of AI-driven chatbots to augment conventional MHFA methodologies. These sophisticated chatbot systems offer an accessible, stigma-free avenue for support, facilitating early detection and preliminary counselling in instances of mental health crises. The study meticulously evaluates the efficacy of chatbots in crisis intervention and their seamless integration into holistic corporate wellness frameworks. These encompass a spectrum of initiatives, including proactive health promotion programs, adaptable work policies, and comprehensive employee assistance schemes. The research also navigates the intricacies of embedding MHFA programs in organisational structures, addressing challenges like resistance to technological and procedural shifts and concerns around data privacy. Strategic methodologies are proposed to navigate and surmount these barriers effectively. A pivotal aspect of this research is the ethical deployment and privacy preservation in the utilisation of chatbots. The paper provides a thorough critique of the ethical considerations and privacy safeguards essential in the management of sensitive mental health information, ensuring adherence to ethical standards and confidentiality. Concludingly, the study posits that the integration of chatbot-enhanced MHFA can substantially reduce workplace mental health stigma, align with legal compliance mandates, and facilitate cost-efficiency. This innovative approach supports the development of a more comprehensive and accessible mental health infrastructure within corporate settings. Looking ahead, the paper advocates for further empirical research to assess the longitudinal impacts of chatbot-enhanced MHFA, explore diverse employee interactions with these systems, and advance AI algorithms for tailored mental health support. The infusion of AI-driven chatbots in MHFA programs is heralded as a pivotal advancement, signifying a major stride towards fostering more resilient, supportive, and mentally healthy workplace environments.
Abstract: This research rigorously explores the implementation of Chatbot-Enhanced Mental Health First Aid (MHFA) within corporate contexts, presenting an innovative paradigm for mitigating mental health risks and bolstering employee well-being. Amidst increasing recognition of the pervasive nature of mental health challenges in the workplace, this research ...
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Research Article
Prioritization of Application Security Vulnerability Remediation Using Metrics, Correlation Analysis, and Threat Model
Santanam Kasturi*,
Xiaolong Li,
John Pickard,
Peng Li
Issue:
Volume 12, Issue 1, June 2024
Pages:
5-13
Received:
8 February 2024
Accepted:
23 February 2024
Published:
13 March 2024
Abstract: As part of a continuing research for evaluating threats posed for exposed attack surface, this study will provide a consolidated view of exploitability of vulnerable applications presenting a web attack surface of an organization exposed to an attacker. While testing and scanning technologies like Static Analysis Security Testing (SAST), Dynamic Analysis Security Testing (DAST), Application Ethical Hack (Penetration Testing), a monitoring technology like the Web Application Firewall (WAF) provides web traffic information of the number of transaction requests for every application under study. To ensure validity, reliability, and completeness of observation multiple applications must be observed. Research from a prior study is referenced that shows correlation between incoming WAF requests and existing vulnerabilities. Using correlation analysis, vulnerabilities metrics, and a threat model analysis help identify pathways to an attack. A vulnerability map-based attack tree can be developed using Common Weakness Enumeration (CWE) and Common Vulnerabilities and Exposures (CVE) information. The threat model analysis and vulnerability-based attack tree can help in simulation studies of possible attacks. This attack tree will show the linkages between vulnerabilities and a lineage pointing to how an attack could travel from the incoming WAF requests to deep down into the application code of exposed and existing, open vulnerabilities travelling laterally to create a more expanded attack crossing trust boundaries using application data flow.
Abstract: As part of a continuing research for evaluating threats posed for exposed attack surface, this study will provide a consolidated view of exploitability of vulnerable applications presenting a web attack surface of an organization exposed to an attacker. While testing and scanning technologies like Static Analysis Security Testing (SAST), Dynamic An...
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Research Article
Implementation of RDBMS in Establishing a Digital Repository for Schizophyllum Commune (Kurakding) Regional Knowledge
Shane Catolico Briones*
,
Salvador Villar Briones II
Issue:
Volume 12, Issue 1, June 2024
Pages:
14-22
Received:
17 April 2024
Accepted:
7 May 2024
Published:
24 May 2024
Abstract: Developing a relational database management system offers benefits such as organized data storage, efficient querying, data integrity, scalability, security, and enhanced collaboration. These advantages can collectively contribute to a comprehensive and reliable resource for Kurakding (Schizophyllum Commune) related information, catering to the needs of farmers, researchers, educators, enthusiasts, and other stakeholders. Kurakding, as known by the locals, is an edible and medicinally important mushroom, particularly popular in the Bicol Region of the Philippines, Southeast Asia. Rapid urbanization and growing populations threaten the mushroom’s natural habitat, leading to its scarcity and increased market value. Recognizing the potential benefits of Information Technology (IT) for agricultural development, a digital repository for Kurakding regional knowledge was implemented. The study employs a developmental and experimental research design, creating a DBMS from scratch and comparing its effectiveness against existing systems. The database development life cycle, which comprises five phases: requirements analysis, initial design, prototyping, data entry management, and full-pledged development, was strictly adopted during the design and development of the digital repository. Secondary data, research outputs, and interviews with stakeholders contributed to data gathering. Results include a conceptual framework and logical design for a KIS Repository, represented through Entity-Relationship Diagram (ERD). The ERD depicts entities such as User, Content, research, and statistics, facilitating user interaction, data management, and forum engagement. Database tables are designed to store user information, Kurakding statistics, research data, content, and forum interactions. Improving the database framework for integrating scientific data enhances its usefulness for diverse stakeholders in the Kurakding industry. This study emphasizes the importance of a digital repository in broadening knowledge about Kurakding and fostering stakeholder involvement. Ultimately, this study created a comprehensive and user-friendly resource for Kurakding-related information, facilitating its sustainable cultivation and utilization.
Abstract: Developing a relational database management system offers benefits such as organized data storage, efficient querying, data integrity, scalability, security, and enhanced collaboration. These advantages can collectively contribute to a comprehensive and reliable resource for Kurakding (Schizophyllum Commune) related information, catering to the nee...
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Research Article
Predicting Attack Paths from Application Security Vulnerabilities Using a Multi-Layer Perceptron
Santanam Kasturi*,
Xiaolong Li,
Peng Li,
John Pickard
Issue:
Volume 12, Issue 1, June 2024
Pages:
23-35
Received:
5 February 2024
Accepted:
30 April 2024
Published:
30 May 2024
Abstract: This paper is in the series of continuing research and proposes an approach to predicting possible attack paths from application security vulnerability-based attack trees. The attack trees are formed by stringing together weaknesses discovered in an application code and a group of applications within a domain. The Common Weakness Enumeration (CWE) and Common Vulnerabilities and Exposures (CVE) linked together as a string of vulnerabilities in the attack trees can be visualized as pathways for attacks. These pathways become potential attacks that can spread vertically and horizontally leading to a multi-path attack that can involve multiple software applications. With more data, and huge number of vulnerabilities, it will become impossible to identify all attack paths unless a full-scale implementation of an autonomous processing mechanism is in place. Machine Learning (ML) and Deep Learning (DL) techniques have been adopted in the cybersecurity space for decades, however all the studies have been around networks, endpoints, and device monitoring. This paper focuses on application security and building on earlier work cited, the use of a vulnerability map that uses attack vectors in a Deep Learning (DL) method implementing a Multi-Layer Perceptron (MLP) forms the basis for developing a predictive model that relates a set of linked vulnerabilities to an attack path. The results are encouraging, and this approach will help in identifying successful or failed attack paths involving multiple applications, isolated or grouped, and will help focus on the right applications and the vulnerabilities associated as priority for remediation.
Abstract: This paper is in the series of continuing research and proposes an approach to predicting possible attack paths from application security vulnerability-based attack trees. The attack trees are formed by stringing together weaknesses discovered in an application code and a group of applications within a domain. The Common Weakness Enumeration (CWE) ...
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Research Article
Software Testing Framework for the Financial Market
David Ademola Oyemade*
Issue:
Volume 12, Issue 1, June 2024
Pages:
36-43
Received:
23 May 2024
Accepted:
6 June 2024
Published:
19 June 2024
Abstract: A well designed, developed and tested software is usually reliable and it produces the same consistent outputs for a set of inputs. However, financial markets software is different because it can produce different results for the same periods of back-testing with the same input historical data, usually downloaded from the financial market broker’s trading server. These inconsistency of results can confuse a financial market software developer when testing for the profitability of developed expert advisors because a profitable expert advisor can be wrongly discarded as unprofitable, leading to frustrations. This problem can be addressed when new software testing processes and indicators are added to the conventional ones such as functional testing, performance testing, usability testing, etc., associated with normal software development. This paper proposes a software testing framework for the financial market with novel software testing processes and indicators. The proposed software testing framework integrates six software testing processes namely, brokers test, currency pairs test, spread test, weekday-weekend test, back testing-live test and time and space overhead test. The paper further analyzes the problem of time and space overheads associated with the financial market software during back-testing and real life implementation. The framework was applied to real life trading in the Forex financial market. The results show that the proposed framework improves the profitability of the financial market software when applied in different scenarios.
Abstract: A well designed, developed and tested software is usually reliable and it produces the same consistent outputs for a set of inputs. However, financial markets software is different because it can produce different results for the same periods of back-testing with the same input historical data, usually downloaded from the financial market broker’s ...
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