SEABASS: Symmetric-keychain Encryption and Authentication for Building Automation Systems

There is an increasing security risk in Building Automation Systems (BAS) in that its communication is unprotected, resulting in the adversary having the capability to inject spurious commands to the actuators to alter the behaviour of BAS. The communication between the Human-Machine-Interface (HMI) and the controller (PLC) is vulnerable as there is no secret key being used to protect the authenticity, confidentiality and integrity of the sensor data and commands. We propose SEABASS, a lightweight key management scheme to distribute and manage session keys between HMI and PLCs, providing a secure communication channel between any two communicating devices in BAS through a symmetric-key based hash-chain encryption and authentication of message exchange. Our scheme facilitates automatic renewal of session keys periodically based on the use of a reversed hash-chain. A prototype was implemented using the BACnet/IP communication protocol and the preliminary results show that the symmetric keychain approach is lightweight and incurs low latency

Characterizing urban landscapes using fuzzy sets

Characterizing urban landscapes is important given the present and future projections of global population that favor urban growth. The definition of “urban” on a thematic map has proven to be problematic since urban areas are heterogeneous in terms of land use and land cover. Further, certain urban classes are inherently imprecise due to the difficulty in integrating various social and environmental inputs into a precise definition. Social components often include demographic patterns, transportation, building type and density while ecological components include soils, elevation, hydrology, climate, vegetation and tree cover. In this paper, we adopt a coupled human and natural system (CHANS) integrated scientific framework for characterizing urban landscapes. We implement the framework by adopting a fuzzy sets concept of “urban characterization” since fuzzy sets relate to classes of object with imprecise boundaries in which membership is a matter of degree. For dynamic mapping applications, user-defined classification schemes involving rules combining different social and ecological inputs can lead to a degree of quantification in class labeling varying from “highly urban” to “least urban”. A socio-economic perspective of urban may include threshold values for population and road network density while a more ecological perspective of urban may utilize the ratio of natural versus built area and percent forest cover. Threshold values are defined to derive the fuzzy rules of membership, in each case, and various combinations of rules offer a greater flexibility to characterize the many facets of the urban landscape. We illustrate the flexibility and utility of this fuzzy inference approach called the Fuzzy Urban Index for the Boston Metro region with five inputs and eighteen rules. The resulting classification map shows levels of fuzzy membership ranging from highly urban to least urban or rural in the Boston study region. We validate our approach using two experts assessing accuracy of the resulting fuzzy urban map. We discuss how our approach can be applied in other urban contexts with newly emerging descriptors of urban sustainability, urban ecology and urban metabolism.This research was partially supported by "Boston University Initiative on Cities Early Stage Urban Research Awards 2015-16" (Gopal & Phillips) and the Frederick S. Pardee Center for the Study of the Longer-Range Future at Boston University. We thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions. (Boston University Initiative on Cities Early Stage Urban Research Awards; Frederick S. Pardee Center for the Study of the Longer-Range Future at Boston University)https://doi.org/10.1016/j.compenvurbsys.2016.02.002Published versio

Degenerate Variational Integrators for Magnetic Field Line Flow and Guiding Center Trajectories

Symplectic integrators offer many advantages for the numerical solution of Hamiltonian differential equations, including bounded energy error and the preservation of invariant sets. Two of the central Hamiltonian systems encountered in plasma physics --- the flow of magnetic field lines and the guiding center motion of magnetized charged particles --- resist symplectic integration by conventional means because the dynamics are most naturally formulated in non-canonical coordinates, i.e., coordinates lacking the familiar $(q, p)$ partitioning. Recent efforts made progress toward non-canonical symplectic integration of these systems by appealing to the variational integration framework; however, those integrators were multistep methods and later found to be numerically unstable due to parasitic mode instabilities. This work eliminates the multistep character and, therefore, the parasitic mode instabilities via an adaptation of the variational integration formalism that we deem ``degenerate variational integration''. Both the magnetic field line and guiding center Lagrangians are degenerate in the sense that their resultant Euler-Lagrange equations are systems of first-order ODEs. We show that retaining the same degree of degeneracy when constructing a discrete Lagrangian yields one-step variational integrators preserving a non-canonical symplectic structure on the original Hamiltonian phase space. The advantages of the new algorithms are demonstrated via numerical examples, demonstrating superior stability compared to existing variational integrators for these systems and superior qualitative behavior compared to non-conservative algorithms