Government agencies such as Federal Motor Carrier Safety Administration (FMCSA) and other public/private organizations rely on secure data sharing platforms to prevent critical information from falling into the hands of malicious attackers. This information can be a motor carrier's safety performance, Social Security Numbers, medical reports of drivers, etc.

The attackers can utilize this critical information to disrupt the secure and smooth operations of various critical FMCSA processes. However, the current data storage and exchange platforms are unable to securely meet the security requirements for both data-at-rest and data-in-transit. InfoBeyond advocates FMCSA-SAFE for secure, scalable, and efficient safety data exchange using blockchain. FMCSA-SAFE is a blockchain design to record the data information exchanged among various entities with integrity and immutability. For blockchain efficiency, clouds are utilized to store large volumes of data and the block only saves the data hash values. It employs a Proof-of-Vote consensus mechanism for transaction efficiency and scalability. Further, it implements Attribute/Role-based Access Control mechanism to ensure only the authorized parties can access the data resources when needed via the cloud. FMCSA-SAFE achieves data confidentiality, integrity, privacy, access control, and security through the following:

• End-to-end data security between FMCSA or other systems and the blockchain.
• Data feeding security in/out of the blockchain.
• Data integrity and immutability within the blockchain ecosystem.

A range segment upgrade for Air Force satellite control network (AFSCN) will significantly improve system effectiveness via spectrum sharing and seamless interoperation. However, the upgraded system requires new capabilities such as real-time and accurate RF interference detection and mitigation, array antenna backlobe/sidelobe suppressions, accurate performance degradation prediction, robust link power budget under uncertainty, etc. Accomplishing those goals are the main keys to enabling a range segment upgrade for AFSCN, however, the existing techniques provide only limited capabilities. InfoBeyond advocates an Efficient Range Segment Upgrade (ERSU) for AFSCN using stochastic interference prediction and context-aware smart antenna control to address these challenges. Firstly, ERSU provides a robust and accurate statistical interference estimation algorithm based on the tools of the Gaussian Markov Random Field. The proposed algorithm offers a real-time interference estimation given erroneous/corrupted spatial-temporal observations. Secondly, a hidden semi-Markov model-based channel prediction algorithm is proposed for robust and accurate channel prediction. It is able to predict not only channel states but also the state duration. Finally, ERSU offers a context-aware stochastic decision making given the input uncertainties. The proposed scheme allows the transmitter efficient selects and controls array antenna enabling reliable multi-satellite receptions.

Due to the scarcity of spectrum, Dynamic Spectrum Access (DSA) becomes a needed technology to improve the utilization of the electromagnetic spectrum for DoD satellite communication. However, current DSA approaches are developed for terrestrial communications without addressing the unique challenges for SATCOM environments such as error-prone spectrum sensing, high mobility, and large coverage. InfoBeyond proposes novel Efficient and Robust Dynamic Spectrum Access under Uncertainty (ERDSAU) algorithms. ERDSAU models the DSA in the SATCOM environment as a problem of Partially Observable Markov Decision Process (POMDP). Partial observation indicates that a LEO satellite is only able to sense a part of spectrum channel. Under partial observation and imperfection awareness of channel, POMDP is an optimization problem that allows a LEO satellite to optimally take action on the spectrum channel. In a collaborative way, ERDSAU tracks each spectrum channel by a probability distribution over the set of possible states that are evaluated on a set of observations and observation probabilities and the underlying Markov decision process, providing high accuracy on decision making. Furthermore, ERDSAU prioritizes the LEO satellites in detecting spectrum holes to improve the resource allocation between multiple satellites. ERDSAU also provides computational efficiency in response to the change of spectrum status.

Building a reliable, high-bandwidth, and low-latency network are crucial to a distributed mission defense system in which the sensors are operated from thousand-mile distances. This is more significant for satellite links which connect sensors distributed in a large area. In this project, we propose Reducing Data Latency and Increasing Network Bandwidth and Reliability (RDLINBR) for missile defenses using network coding. Network coding is a proven technology, and with this technology, RDLINBR can effectively reduce communication latency and increase bandwidth without modification to hardware while also maintaining reliable and secure communications.