Zenodo (CERN European Organization for Nuclear Research), Jun 29, 2023
Software development security refers to the practice of integrating security measures and conside... more Software development security refers to the practice of integrating security measures and considerations throughout the software development lifecycle to ensure the confidentiality, integrity, and availability of software systems. It involves identifying, mitigating, and eliminating security vulnerabilities and threats that could be exploited by attackers. The goal of this paper is to survey the various concepts and methodologies directed towards software security, and the identification of any missing gaps. Based on the findings, it is noted that the development of secure software requires a proactive and comprehensive approach. It begins with establishing secure design principles and incorporating security requirements from the initial stages of development. Here, secure coding practices, such as input validation, output encoding, and secure authentication and authorization mechanisms, are employed to prevent common security vulnerabilities. In addition, regular security testing, including penetration testing and vulnerability scanning, helps identify and address potential weaknesses in the software. Normally, code reviews and security audits are conducted to ensure adherence to secure coding practices and identify any security flaws. It is important that security training and awareness programs be provided to developers and other stakeholders to foster a security-conscious culture. To minimize potential vulnerabilities, secure configuration management, which involves properly configuring servers, networks, and dependencies may be utilized. On the other hand, regular updates and patching are essential to address known security vulnerabilities in software components. To guide their software development security practices, organizations may follow established security standards and frameworks such as ISO 27001 or NIST Cybersecurity Framework. By prioritizing software development security, organizations can protect sensitive data, prevent unauthorized access, and mitigate the risk of security breaches and incidents. In the long run, this helps build trust with users and stakeholders, enhances the reputation of the software, and reduces the potential impact of security incidents on the organization.
Zenodo (CERN European Organization for Nuclear Research), Feb 28, 2023
A huge percentage of people especially in developed countries spend a good chunk of their wealth ... more A huge percentage of people especially in developed countries spend a good chunk of their wealth in managing their health conditions. In order to adequately administer healthcare, governments and various organizations have embraced advanced technology for automating the health industry. In recent past, electronic health records have largely been managed by Enterprise Resource Planning and legacy systems. Big data framework steadily emerge as the underlying technology in healthcare, which offers solutions that limits capacity of others systems in terms of storage and reporting. Automation through cloud services supported by storage of structured and unstructured health data in heterogeneous environment has improved service delivery, efficiency, medication, diagnosis, reporting and storage in healthcare. The argument support the idea that big data healthcare still face information security concern, for instance patient image sharing, authentication of patient, botnet, correlation attacks, man-in-the-middle, Distributed Denial of Service (DDoS), blockchain payment gateway, time complexities of algorithms, despite numerous studies conducted by scholars in security management for big data in smart healthcare. Some security technique include digital image encryption, steganography, biometrics, rule-based policy, prescriptive analysis, blockchain contact tracing, cloud security, MapReduce, machine-learning algorithms, anonymizations among others. However, most of these security solutions and analysis performed on structured and semi-structured data as opposed to unstructured data. This may affect the output of medical reporting of patients' condition particularly on wearable devices and other examinations such as computerized tomography (CT) Scans among others. A major concern is how to identify inherent security vulnerabilities in big healthcare, which generate images for transmission and storage. Therefore, this paper conducted a comparative survey of solutions that specifically safeguards structured and unstructured data using systems that run on big data frameworks. The literature highlights several security advancements in cryptography, machine learning, anonymization and protocols. Most of these security frameworks lacks implementation evidence. A number of studies did not provide comprehensive performance metrics (accuracy, error, recall, precision) of the models besides using a single algorithm without validated justification. Therefore, a critique on the contribution, performance and areas of improvements discussed and summarized in the paper.
Software development security refers to the practice of integrating security measures and conside... more Software development security refers to the practice of integrating security measures and considerations throughout the software development lifecycle to ensure the confidentiality, integrity, and availability of software systems. It involves identifying, mitigating, and eliminating security vulnerabilities and threats that could be exploited by attackers. The goal of this paper is to survey the various concepts and methodologies directed towards software security, and the identification of any missing gaps. Based on the findings, it is noted that the development of secure software requires a proactive and comprehensive approach. It begins with establishing secure design principles and incorporating security requirements from the initial stages of development. Here, secure coding practices, such as input validation, output encoding, and secure authentication and authorization mechanisms, are employed to prevent common security vulnerabilities. In addition, regular security testing, ...
World Journal of Advanced Engineering Technology and Sciences
Software security is one of the most critical concerns in modern software development, especially... more Software security is one of the most critical concerns in modern software development, especially in safety-critical systems whose failure can lead to environmental damage, substantial property, or loss of human lives. In addition, flawed applications have been shown to exhibit unpredictable behavior while software products with numerous vulnerabilities present attack vectors that can be exploited by attackers. To address some of these problems, vulnerability prediction has been deployed for early detection of security risks in the software development lifecycle (SDLC). This can potentially facilitate decision making during the SDLC, resulting in the production of more secure software. Prioritizing security during SDLC permits developers and stakeholders to identify and resolve possible security concerns early on in the process. The aim of this paper is therefore to offer some in-depth review of software systems security issues. In addition, the various measures that have been put i...
World Journal of Advanced Engineering Technology and Sciences
Over the years, communication through Short Message Service (SMS) has been a primary tool for mob... more Over the years, communication through Short Message Service (SMS) has been a primary tool for mobile subscribers. SMS has varied applications in health, industry, finances, education and social networking among others. The growth of mobile devices and SMS usage has consequently increased the attack surface for cyber-criminals culminating to the proliferation of malicious activities introduced using SMS spam, phishing, spyware, malware etc. Ham messages are normal messages people trade with one another and are usually not unwanted by the recipient, while spam messages are unsolicited junk and redundant messages that may be sent to a large number of people at once and are usually unwanted. Various spam detection models have been developed using various traditional machine and deep learning techniques. However, most studies where comparison between deep and traditional machine learning algorithms is done, have unfortunately omitted K-Nearest Neighbors and Support Vector Machine (SVM) w...
World Journal of Advanced Engineering Technology and Sciences
Federated Learning (FL) is concept that has been adopted in medical field to analyze data in indi... more Federated Learning (FL) is concept that has been adopted in medical field to analyze data in individual devices through aggregation of machine learning model in global server. It also provides data privacy being that the sampled devices are not allowed to share data among themselves. Therefore, it minimizes computation costs and privacy risks to some extent compared to conventional methods of machine learning. However, federation learning provides a different use case in health as compared to other sectors. Preservation of patients’ sensitive information such as electronic health record (EHR) when sharing data among different medical practitioners is of greatest concern. So the question is, how should FL techniques be structured in the current clinical environment where heterogeneity is the order of the day? The EU’s General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act of 1996 (HIPPA) regulations recommends health providers to gain author...
Global Journal of Engineering and Technology Advances
A huge percentage of people especially in developed countries spend a good chunk of their wealth ... more A huge percentage of people especially in developed countries spend a good chunk of their wealth in managing their health conditions. In order to adequately administer healthcare, governments and various organizations have embraced advanced technology for automating the health industry. In recent past, electronic health records have largely been managed by Enterprise Resource Planning and legacy systems. Big data framework steadily emerge as the underlying technology in healthcare, which offers solutions that limits capacity of others systems in terms of storage and reporting. Automation through cloud services supported by storage of structured and unstructured health data in heterogeneous environment has improved service delivery, efficiency, medication, diagnosis, reporting and storage in healthcare. The argument support the idea that big data healthcare still face information security concern, for instance patient image sharing, authentication of patient, botnet, correlation atta...
Zenodo (CERN European Organization for Nuclear Research), Jun 29, 2023
Software development security refers to the practice of integrating security measures and conside... more Software development security refers to the practice of integrating security measures and considerations throughout the software development lifecycle to ensure the confidentiality, integrity, and availability of software systems. It involves identifying, mitigating, and eliminating security vulnerabilities and threats that could be exploited by attackers. The goal of this paper is to survey the various concepts and methodologies directed towards software security, and the identification of any missing gaps. Based on the findings, it is noted that the development of secure software requires a proactive and comprehensive approach. It begins with establishing secure design principles and incorporating security requirements from the initial stages of development. Here, secure coding practices, such as input validation, output encoding, and secure authentication and authorization mechanisms, are employed to prevent common security vulnerabilities. In addition, regular security testing, including penetration testing and vulnerability scanning, helps identify and address potential weaknesses in the software. Normally, code reviews and security audits are conducted to ensure adherence to secure coding practices and identify any security flaws. It is important that security training and awareness programs be provided to developers and other stakeholders to foster a security-conscious culture. To minimize potential vulnerabilities, secure configuration management, which involves properly configuring servers, networks, and dependencies may be utilized. On the other hand, regular updates and patching are essential to address known security vulnerabilities in software components. To guide their software development security practices, organizations may follow established security standards and frameworks such as ISO 27001 or NIST Cybersecurity Framework. By prioritizing software development security, organizations can protect sensitive data, prevent unauthorized access, and mitigate the risk of security breaches and incidents. In the long run, this helps build trust with users and stakeholders, enhances the reputation of the software, and reduces the potential impact of security incidents on the organization.
Zenodo (CERN European Organization for Nuclear Research), Feb 28, 2023
A huge percentage of people especially in developed countries spend a good chunk of their wealth ... more A huge percentage of people especially in developed countries spend a good chunk of their wealth in managing their health conditions. In order to adequately administer healthcare, governments and various organizations have embraced advanced technology for automating the health industry. In recent past, electronic health records have largely been managed by Enterprise Resource Planning and legacy systems. Big data framework steadily emerge as the underlying technology in healthcare, which offers solutions that limits capacity of others systems in terms of storage and reporting. Automation through cloud services supported by storage of structured and unstructured health data in heterogeneous environment has improved service delivery, efficiency, medication, diagnosis, reporting and storage in healthcare. The argument support the idea that big data healthcare still face information security concern, for instance patient image sharing, authentication of patient, botnet, correlation attacks, man-in-the-middle, Distributed Denial of Service (DDoS), blockchain payment gateway, time complexities of algorithms, despite numerous studies conducted by scholars in security management for big data in smart healthcare. Some security technique include digital image encryption, steganography, biometrics, rule-based policy, prescriptive analysis, blockchain contact tracing, cloud security, MapReduce, machine-learning algorithms, anonymizations among others. However, most of these security solutions and analysis performed on structured and semi-structured data as opposed to unstructured data. This may affect the output of medical reporting of patients' condition particularly on wearable devices and other examinations such as computerized tomography (CT) Scans among others. A major concern is how to identify inherent security vulnerabilities in big healthcare, which generate images for transmission and storage. Therefore, this paper conducted a comparative survey of solutions that specifically safeguards structured and unstructured data using systems that run on big data frameworks. The literature highlights several security advancements in cryptography, machine learning, anonymization and protocols. Most of these security frameworks lacks implementation evidence. A number of studies did not provide comprehensive performance metrics (accuracy, error, recall, precision) of the models besides using a single algorithm without validated justification. Therefore, a critique on the contribution, performance and areas of improvements discussed and summarized in the paper.
Software development security refers to the practice of integrating security measures and conside... more Software development security refers to the practice of integrating security measures and considerations throughout the software development lifecycle to ensure the confidentiality, integrity, and availability of software systems. It involves identifying, mitigating, and eliminating security vulnerabilities and threats that could be exploited by attackers. The goal of this paper is to survey the various concepts and methodologies directed towards software security, and the identification of any missing gaps. Based on the findings, it is noted that the development of secure software requires a proactive and comprehensive approach. It begins with establishing secure design principles and incorporating security requirements from the initial stages of development. Here, secure coding practices, such as input validation, output encoding, and secure authentication and authorization mechanisms, are employed to prevent common security vulnerabilities. In addition, regular security testing, ...
World Journal of Advanced Engineering Technology and Sciences
Software security is one of the most critical concerns in modern software development, especially... more Software security is one of the most critical concerns in modern software development, especially in safety-critical systems whose failure can lead to environmental damage, substantial property, or loss of human lives. In addition, flawed applications have been shown to exhibit unpredictable behavior while software products with numerous vulnerabilities present attack vectors that can be exploited by attackers. To address some of these problems, vulnerability prediction has been deployed for early detection of security risks in the software development lifecycle (SDLC). This can potentially facilitate decision making during the SDLC, resulting in the production of more secure software. Prioritizing security during SDLC permits developers and stakeholders to identify and resolve possible security concerns early on in the process. The aim of this paper is therefore to offer some in-depth review of software systems security issues. In addition, the various measures that have been put i...
World Journal of Advanced Engineering Technology and Sciences
Over the years, communication through Short Message Service (SMS) has been a primary tool for mob... more Over the years, communication through Short Message Service (SMS) has been a primary tool for mobile subscribers. SMS has varied applications in health, industry, finances, education and social networking among others. The growth of mobile devices and SMS usage has consequently increased the attack surface for cyber-criminals culminating to the proliferation of malicious activities introduced using SMS spam, phishing, spyware, malware etc. Ham messages are normal messages people trade with one another and are usually not unwanted by the recipient, while spam messages are unsolicited junk and redundant messages that may be sent to a large number of people at once and are usually unwanted. Various spam detection models have been developed using various traditional machine and deep learning techniques. However, most studies where comparison between deep and traditional machine learning algorithms is done, have unfortunately omitted K-Nearest Neighbors and Support Vector Machine (SVM) w...
World Journal of Advanced Engineering Technology and Sciences
Federated Learning (FL) is concept that has been adopted in medical field to analyze data in indi... more Federated Learning (FL) is concept that has been adopted in medical field to analyze data in individual devices through aggregation of machine learning model in global server. It also provides data privacy being that the sampled devices are not allowed to share data among themselves. Therefore, it minimizes computation costs and privacy risks to some extent compared to conventional methods of machine learning. However, federation learning provides a different use case in health as compared to other sectors. Preservation of patients’ sensitive information such as electronic health record (EHR) when sharing data among different medical practitioners is of greatest concern. So the question is, how should FL techniques be structured in the current clinical environment where heterogeneity is the order of the day? The EU’s General Data Protection Regulation (GDPR) and Health Insurance Portability and Accountability Act of 1996 (HIPPA) regulations recommends health providers to gain author...
Global Journal of Engineering and Technology Advances
A huge percentage of people especially in developed countries spend a good chunk of their wealth ... more A huge percentage of people especially in developed countries spend a good chunk of their wealth in managing their health conditions. In order to adequately administer healthcare, governments and various organizations have embraced advanced technology for automating the health industry. In recent past, electronic health records have largely been managed by Enterprise Resource Planning and legacy systems. Big data framework steadily emerge as the underlying technology in healthcare, which offers solutions that limits capacity of others systems in terms of storage and reporting. Automation through cloud services supported by storage of structured and unstructured health data in heterogeneous environment has improved service delivery, efficiency, medication, diagnosis, reporting and storage in healthcare. The argument support the idea that big data healthcare still face information security concern, for instance patient image sharing, authentication of patient, botnet, correlation atta...
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Papers by David Odera