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Cyber Security is protecting the information that makes your business unique. DataPattern’s Cyber Security Team know hackers and malware inside and out. Their wealth of information on the latest phishing and data breach methods guide their procedures for securing client information. We help organizations ranging from financial corporations to hospitals outsource their security operations and rest easy knowing their data is in good hands
Have executive level involvement and include both business and technology perspectives: This is easy to say, but in many organizations, it can be difficult for two main reasons. 1 – Many executives feel they are responsible for running the business and strategy and are not overly interested the details and complexity associated with solving cybersecurity issues. 2- Technologists and process engineers are not accustomed to communicating complex security solution options effectively to senior management.
Classify data risk across the enterprise and the entire value chain (e.g., where it is accessed by suppliers, partners, employees, customers). Developing a framework by which to evaluate and classify data is very achievable. Developing consensus with executives on whose data is more critical to the operation of the enterprise is often where the more difficult challenges arise. With the sensitive data identified, efforts can be focus on securing the highest risk data. This is where dis-aggregating data into less sensitive sub-components, such as separating credit card numbers and expiration dates into different databases, can greatly simplify the risk mitigation task.
Identify which business processes and process participants access sensitive data or make use of applications that use sensitive data. Changing the way, a business process accesses data can be the simplest, and least technical, approach to mitigating security issues. Separation of duties in financially significant processes is a common practice, such as the person who writes the checks cannot also sign them. The same concept can be applied more broadly to secure other types of sensitive data at the business process level.
Determine which applications have access to what data (at least for the high-risk data). A little used approach to reduce cybersecurity threats is separating application functionality and access rights to data based on security sensitivity. As the complexity and negative impact of these threats continue to increase, this application architecture approach will become more prevalent. Going back to the credit card example, an application subsystem that is highly secure from both a physical and a logical perspective could be the only application that accesses the credit card expiration date. That subsystem could then provide the core credit card processing application a “valid” or “invalid” judgment rather than the actual data.
Balance security effort, expense and impact on the business against the risk profile of the data. Focus remediation on the most critical data in the enterprise i.e., don’t polish acorns in the backyard. Many organizations apply common security techniques to vast amounts of information. For the initial basic layers of security, that’s ok, but the highest risk data should be addressed differently than the general business operation data.
Develop a comprehensive security architecture or model by looking holistically across business processes, application and data architectures, roles, access/authority rights, and perimeter security. The layered approach works well for the majority of data in a large enterprise. At the center, multiple approaches should be used to secure the most sensitive data. That way, a perpetrator may figure out how to access one element of sensitive data, but the techniques are useless to wreak broader havoc.
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