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The world is currently facing the era of Cyberbiosecurity, also known as Biocybersecurity, or Digital Biosecurity, which poses a few unique security vulnerabilities. A significant percentage of the scientific, agricultural, and health communities are still unaware of the unique security complexities that have resulted from fusion of the supply chain, infrastructure, cyber, and life and medical sciences. Measurement, analysis, and mitigation of cyberattacks on biological systems are the goals of Cyberbiosecurity. Data mining is a promising avenue for further investigation as a means of mitigating cyber-attacks for research purposes. Data mining is the process of extracting useful patterns, information, and expertise from massive datasets. In the domain of Cyberbiosecurity, data mining techniques have received little attention. The purpose of this survey on data mining in cybersecurity is to determine the state of the art in cybersecurity issues, including different types of assaults and data mining methods that could be used to address these issues. This review's findings shed insight on the characteristics of security issues as well as gaps in Cyberbiosecurity. Furthermore, the review's conclusions show that most responses to Cyberbiosecurity attacks advocate for national or international government/private organizations to raise public awareness of these attacks and equip their clients/dealers with secure methods to transmit data online. These attempts to raise awareness can be divided into four distinct levels, each with its own set of techniques and objectives, resulting in a holistic strategy to addressing the difficulties of Cyberbiosecurity. A notable gap found in this review is the absence of appropriate countermeasures against cyberattacks employing data mining in the biological systems domain such as healthcare, agriculture, biomedical research, and other domains. The goal of this review is to increase knowledge among Cyberbiosecurity experts and to develop