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 in place to mitigate security issues during SDLC are discussed.
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.
Smart agriculture is an emerging technology that has been developed from innovative information technologies such as AI, IoT, ML, smart vehicles in order to maximize outputs while optimizing farm inputs for better production and profit. However, these innovations have several vulnerabilities, especially, given that most of agriculture is practiced in open fields, exposed to harsh, unprotected environments. Studies have been conducted on its security issues and how to mitigate the threats from the vulnerabilities along with some studies in data privacy in smart agriculture. However, studies on trust issues of farmers on these technologies are absent. This paper looks at the security issues and how they impact on farmers’ trust on these technologies. It finally offers direction on hoe to enhance their trust on the smart farming technologies.
Smart agriculture, enabled by advanced technologies such as internet of things, artificial intelligence and data analytics, offers immense potential for optimizing farming practices and increasing agricultural productivity. However, as the adoption of smart agriculture systems continues to grow, it brings forth various security issues that need to be addressed to protect farming operations, data integrity, and privacy. This paper provides an overview of the security issues in smart agriculture, including vulnerabilities in internet of things devices, lack of standardized security protocols, limited security awareness among farmers, and challenges in securing data and communication networks. In addition, it highlights the need for robust security measures to mitigate risks such as unauthorized access, data breaches, and disruption of operations. Moreover, emphasis should be laid on the importance of collaborative efforts between technology providers, agricultural stakeholders, researchers, and policymakers to develop effective security solutions and standards that ensure the trustworthiness and resilience of smart agriculture systems.
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