Cyberspace has reshaped the fabric of our society, in more ways than facilitating interactions via social platforms. Global systems within countless industries depend on this grid to function optimally, and as the amount of data they generate continues to grow exponentially, the digital and physical infrastructures of our ecosystem become increasingly interconnected.
The technological advances within AI, Big Data, IoT, and cloud-based infrastructures have vastly improved productivity across a range of disciplines, business infrastructures, and communication networks. However, there are immense risks associated with compiling and selling large data sets containing sensitive information due to the fact that most of the world’s generated data is not properly secured. Furthermore, the keepers of this sensitive information need to circumvent threat vectors that can lead to data becoming bad, spoofed, or stolen. This affects all facets of modern civilization including the most resourceful governments and militaries.
DLT for the DoD
The United States military has always been a leader in the development of state of the art technologies in many areas such as sensor systems, mechanical engineering, the mass adoption of global positioning systems (GPS) and even the internet. Today, every division within the U.S. Department of Defense (DoD) compiles complex data structures with billions of data points (satellites, ground troops, vehicles, aircrafts, supply chains, etc.). As such, securing big data is the greatest challenge for the DoD–with nearly one in five operational complications stemming from the inability to process or verify data for mission critical decision making.
The general increase of complexity within IT has led to an influx of bad data, which is deemed useless because aircraft readiness units or field operatives, for instance, cannot make time-sensitive decisions based on potentially compromised or spoofed data. The use of this data often results in avoidable monetary costs, and, in some cases, can also cost human lives. The core issue is the nature of centralized systems that create operational bottlenecks, resulting in slow security processes that are incapable of validating and managing the volume of data that is created. For instance, the United States Air Force in itself generates more than 1800TB of data each minute–a number that is growing exponentially–presenting a significant challenge for data security. Additionally, over 80% of the time is spent preparing the data before it can be used. This is the result of using disjointed platforms to store data and the limited metadata available to make quick decisions, which causes the need for manual integration.
Another significant issue is the lack of operational synergy across multiple command and control domains (e.g. Air Force to Navy or any military domain to civilian contractors), which impedes interoperability between data management systems. Moreover, data streams in centralized networks can be spoofed or corrupted, making it impossible to manage, validate or even process large datasets in transit with complex security clearance requirements. Essentially, this means that a data set might have one small piece of data within it that requires Top Secret clearance to view, and therefore cannot be placed on a public network, such as the internet.
Constellation for Government
As an integral part of Constellation’s distributed security infrastructure, servers are dispersed across the globe, mitigating the risk of cyberattacks geared towards centralized servers. Through consensus mechanisms, Constellation guarantees that faulty data and threat vectors are immediately identified, enabling the network to prevent malicious actors from manipulating sensitive information. With Constellation, government agencies are able to cryptographically secure complex data sets down to a specific data type, ensuring that data remains secure in contested network environments.
By enabling Constellation’s Hypergraph, these agencies can:
- Secure data transactions for command and control across multiple domains and agencies in a cross-functional yet encrypted network.
- Verify the integrity of streaming data, ensuring that it has not been spoofed or corrupted.
- Swiftly integrate all necessary data types and policies to the network–enabling relevant parties to make time-sensitive decisions on the fly.
By utilizing its directed acyclic graph (DAG) architecture and a novel consensus called Proof of Reputable Observation (PRO), Constellation’s Hypergraph is able to scale indefinitely by adding nodes to the network. The network is able to integrate all forms of data types from various sources through state channels (microservices)–a level of integration that is imperative when facilitating complex interactions with billions of IoT devices.
Click on the link below to learn more about how Constellation is quickly becoming the standard for processing, validating, and securing government data as it is being created and communicated across networks.