confidentiality, integrity, and availability (CIA triad)

Confidentiality

Confidentiality is roughly equivalent to privacy. Measures undertaken to ensure confidentiality are designed to prevent sensitive information from reaching the wrong people, while making sure that authorized people can access it. It is common for data to be categorized according to the amount and type of damage that could be done should it fall into unintended hands. More or less stringent measures can then be implemented according to those categories.

Sometimes safeguarding data confidentiality involves special training for those privy to sensitive documents. Such training would typically include security risks that could threaten this information. Training can help familiarize authorized people with risk factors and how to guard against them. Further aspects of training may include strong passwords and password-related best practices and information about social engineering methods, to prevent users from bending data-handling rules with good intentions and potentially disastrous results.

A good example of methods used to ensure confidentiality is an account number or routing number when banking online. Data encryption is a common method of ensuring confidentiality. User IDs and passwords constitute a standard procedure; two-factor authentication is becoming the norm. Other options include biometric verification and security tokens, key fobs or soft tokens. In addition, users can take precautions to minimize the number of places where the information appears and the number of times it is actually transmitted to complete a required transaction. Extra measures might be taken in the case of extremely sensitive documents, such as storing only on air gapped computers, disconnected storage devices or, for highly sensitive information, in hard copy form only.

Integrity

Integrity involves maintaining the consistency, accuracy, and trustworthiness of data over its entire life cycle. Data must not be changed in transit, and steps must be taken to ensure that data cannot be altered by unauthorized people (for example, in a breach of confidentiality). These measures include file permissions and user access controls. Version control may be used to prevent erroneous changes or accidental deletion by authorized users from becoming a problem. In addition, some means must be in place to detect any changes in data that might occur as a result of non-human-caused events such as an electromagnetic pulse (EMP) or server crash. Some data might include checksums, even cryptographic checksums, for verification of integrity. Backups or redundancies must be available to restore the affected data to its correct state.

Availability 

Availability is best ensured by rigorously maintaining all hardware, performing hardware repairs immediately when needed and maintaining a correctly functioning operating system environment that is free of software conflicts. It’s also important to keep current with all necessary system upgrades. Providing adequate communication bandwidth and preventing the occurrence of bottlenecks are equally important. Redundancy, failover, RAID even high-availability clusters can mitigate serious consequences when hardware issues do occur.  Fast and adaptive disaster recovery is essential for the worst case scenarios; that capacity is reliant on the existence of a comprehensive disaster recovery plan (DRP). Safeguards against data loss or interruptions in connections must include unpredictable events such as natural disasters and fire. To prevent data loss from such occurrences, a backup copy may be stored in a geographically-isolated location, perhaps even in a fireproof, waterproof safe. Extra security equipment or software such as firewalls and proxy servers can guard against downtime and unreachable data blocked by malicious denial-of-service (DoS) attacks and network intrusions.

Special challenges for the CIA triad

Big data poses extra challenges to the CIA paradigm because of the sheer volume of information that needs to be safeguarded, the multiplicity of sources it comes from and the variety of formats in which it exists. Duplicate data sets and disaster recovery plans can multiply the already high costs. Furthermore, because the main concern of big data is collecting and making some kind of useful interpretation of all this information, responsible data oversight is often lacking. Whistleblower Edward Snowden brought that problem to the public forum when he reported on the NSA’s collection of massive volumes of American citizens’ personal data.

Internet of Things privacy is the special considerations required to protect the information of individuals from exposure in the IoT environment, in which almost any physical or logical entity or object can be given a unique identifier and the ability to communicate autonomously over the Internet or a similar network. The data transmitted by a given endpoint might not cause any privacy issues on its own. However, when even fragmented data from multiple endpoints is gathered, collated and analyzed, it can yield sensitive information. 

Internet of Things security is also a special challenge because the IoT consists of so many Internet-enabled devices other than computers, which often go unpatched and are often configured with default or weak passwords. Unless adequately protected, IoT things could be used as separate attack vectors or part of a thingbot.  In a recent proof-of-concept exploit, for example, researchers demonstrated that a network could be compromised through a Wi-Fi-enabled light bulb. In December 2013, a researcher at Proofpoint, an enterprise security firm, discovered that hundreds of thousands of spam emails were being logged through a security gateway. Proofpoint traced the attacks to a botnet made up of 100,000 hacked appliances. As more and more products develop with the capacity to be networked, it’s important to routinely consider security in product development.