Numerical data is valuable and sensitive information that needs to be protected from unauthorized access, manipulation, or loss. Whether you work with financial, scientific, or personal data, you need to apply analytical skills to ensure its security and integrity. In this article, you will learn some basic principles and practices of how to secure numerical data in different contexts and scenarios.
The first step to secure your numerical data is to define what kind of data you have, who owns it, who needs it, and how it is used. This will help you identify the risks, regulations, and requirements that apply to your data. For example, if you handle personal data, you need to comply with data protection laws and ethical standards. If you work with confidential or proprietary data, you need to follow the policies and agreements of your organization or clients. If you use public data, you need to respect the licenses and sources of the data.
The best practice is that while you define your data, you document it and compile Data Catalog, this can be done as granular possible (can be done even on attribute level) defining parameters like: classification of data, source, retention period, access restriction, regulatory/compliance requirements, etc.
The second step to secure your numerical data is to encrypt it, which means transforming it into a code that only authorized parties can decipher. Encryption protects your data from being intercepted, stolen, or tampered with while it is stored or transmitted. There are different types of encryption methods and tools, depending on the level of security and complexity you need. For example, you can use symmetric encryption, where the same key is used to encrypt and decrypt the data, or asymmetric encryption, where different keys are used for each process. You can also use encryption software, such as VeraCrypt or BitLocker, to encrypt your data on your devices or cloud storage.
It is recommended that you encrypt data that is in transit (i.e. form being posted, data is being collected or data is being uploaded or downloaded) and data being stored also know with the term data at rest (i.e. data is being saved for later use, data is being archived in tape or other media, data is being transformed and saved in different format, etc.
The third step to secure your numerical data is to backup it, which means creating copies of your data and storing them in different locations or media. Backup protects your data from being lost or damaged due to accidents, disasters, or malicious attacks. There are different types of backup methods and strategies, depending on the frequency, size, and importance of your data. For example, you can use full backup, where you copy all your data at once, or incremental backup, where you copy only the changes since the last backup. You can also use backup software, such as Acronis or EaseUS, to automate and manage your backup processes.
The fourth step to secure your numerical data is to audit it, which means monitoring and reviewing your data activities and events. Audit helps you detect and prevent any unauthorized or suspicious access, modification, or deletion of your data. It also helps you evaluate and improve your data security policies and practices. There are different types of audit methods and tools, depending on the scope, depth, and frequency of your data analysis. For example, you can use log files, where you record the details of your data transactions, or audit trails, where you track the history and changes of your data. You can also use audit software, such as Splunk or LogRhythm, to collect and analyze your audit data.
The fifth step to secure your numerical data is to update it, which means keeping your data current and accurate. Update helps you avoid errors, inconsistencies, or redundancies in your data. It also helps you comply with the latest standards, regulations, or expectations of your data stakeholders. There are different types of update methods and tools, depending on the source, format, and frequency of your data changes. For example, you can use manual update, where you edit or delete your data by yourself, or automatic update, where you use scripts or programs to update your data. You can also use update software, such as Excel or R, to manipulate and transform your data.
The sixth and final step to secure your numerical data is to educate yourself and others, which means learning and sharing the best practices and principles of data security. Education helps you raise your awareness and skills of how to protect your data from various threats and challenges. It also helps you foster a culture of data security and responsibility among your colleagues, partners, or clients. There are different types of education methods and resources, depending on the level, topic, and format of your data security learning. For example, you can use online courses, such as Coursera or Udemy, to learn the basics or advanced concepts of data security. You can also use blogs, podcasts, or webinars, such as Security Weekly or Data Security Podcast, to stay updated and informed about the latest trends and issues of data security.
Certainly, utilizing masking techniques to protect sensitive numerical data is a smart approach to maintain security and privacy. For instance, a credit card number "1234 5678 9012 3456" could be masked as "1234 **** **** 3456". This approach safeguards the critical middle digits, while the first and last segments remain visible for user identification. As a result, authorized personnel can fulfill their tasks without being exposed to the full credit card number.
Data Masking: When and if possible, use masking techniques to replace sensitive numerical data. This way, even authorised users can only see a masked version of the actual data. For instance, the middle figures on a credit card are masked in such a way that allows authorised employees to perform their duties without being exposed to complete credit card number.
While data masking is good practice to apply it on-fly while showing particular data i.e. credit card number by showing first and last 4 digits while replacing the middle 8 digits with X or * (i.e. 1234 5678 9012 3456 to mask it to 1234 XXXX XXXX 3456) this may not be very useful if you want to use that field for machine learning purposes (ML) since there me by more that one credit card that will be masked like 1234 XXXX XXXX 3456. In this or similar circumstance where must be used depersonalized data but later to be able to know to whom that result belong, my personal preference is to use one-way encryption of hushing i.e. SHA-1, SHA-2,etc. Hushing algorithm method is used for password encryptions.