Hash-based signatures for the internet of things

While numerous digital signature schemes exist in the literature, most real-world system rely on RSA-based signature schemes or on the digital signature algorithm (DSA), including its elliptic curve cryptography variant ECDSA. In this position paper we review a family of alternative signature schemes, based on hash functions, and we make the case for their application in Internet of Things (IoT) settings. Hash-based signatures provide postquantum security, and only make minimal security assumptions, in general requiring only a secure cryptographic hash function. This makes them extremely flexible, as they can be implemented on top of any hash function that satisfies basic security properties. Hash-based signatures also feature numerous parameters defining aspects such as signing speed and key size, that enable trade-offs in constrained environments. Simplicity of implementation and customization make hash based signatures an attractive candidate for the IoT ecosystem, which is composed of a number of diverse, constrained devices

VerSum: Verifiable Computations over Large Public Logs

VerSum allows lightweight clients to outsource expensive computations over large and frequently changing data structures, such as the Bitcoin or Namecoin blockchains, or a Certificate Transparency log. VerSum clients ensure that the output is correct by comparing the outputs from multiple servers. VerSum assumes that at least one server is honest, and crucially, when servers disagree, VerSum uses an efficient conflict resolution protocol to determine which server(s) made a mistake and thus obtain the correct output. VerSum's contribution lies in achieving low server-side overhead for both incremental re-computation and conflict resolution, using three key ideas: (1) representing the computation as a functional program, which allows memoization of previous results; (2) recording the evaluation trace of the functional program in a carefully designed computation history to help clients determine which server made a mistake; and (3) introducing a new authenticated data structure for sequences, called SeqHash, that makes it efficient for servers to construct summaries of computation histories in the presence of incremental re-computation. Experimental results with an implementation of VerSum show that VerSum can be used for a variety of computations, that it can support many clients, and that it can easily keep up with Bitcoin's rate of new blocks with transactions.United States. Defense Advanced Research Projects Agency. Clean-slate design of Resilient, Adaptive, Secure Hosts (CRASH) Program (Contract N66001-10-2-4089)National Science Foundation (U.S.) (Award CNS-1053143)National Science Foundation (U.S.) (Award CNS-1413920

Unifying Parsimonious Tree Reconciliation

Evolution is a process that is influenced by various environmental factors, e.g. the interactions between different species, genes, and biogeographical properties. Hence, it is interesting to study the combined evolutionary history of multiple species, their genes, and the environment they live in. A common approach to address this research problem is to describe each individual evolution as a phylogenetic tree and construct a tree reconciliation which is parsimonious with respect to a given event model. Unfortunately, most of the previous approaches are designed only either for host-parasite systems, for gene tree/species tree reconciliation, or biogeography. Hence, a method is desirable, which addresses the general problem of mapping phylogenetic trees and covering all varieties of coevolving systems, including e.g., predator-prey and symbiotic relationships. To overcome this gap, we introduce a generalized cophylogenetic event model considering the combinatorial complete set of local coevolutionary events. We give a dynamic programming based heuristic for solving the maximum parsimony reconciliation problem in time O(n^2), for two phylogenies each with at most n leaves. Furthermore, we present an exact branch-and-bound algorithm which uses the results from the dynamic programming heuristic for discarding partial reconciliations. The approach has been implemented as a Java application which is freely available from http://pacosy.informatik.uni-leipzig.de/coresym.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

SAVING LIVES FROM ABOVE: PERSON DETECTION IN DISASTER RESPONSE USING DEEP NEURAL NETWORKS

This paper focuses on person detection in aerial and drone imagery, which is crucial for various operations such as situational awareness, search and rescue, and safe delivery of supplies. We aim to improve disaster response efforts by enhancing the speed, safety, and effectiveness of the process. Therefore, we introduce a new person detection dataset comprising 311 annotated aerial and drone images, acquired from helicopters and drones in different scenes, including urban and rural areas, and for different scenarios, such as estimation of damage in disaster-affected zones, and search and rescue operations in different countries. The amount of data considered and level of detail of the annotations resulted in a total of 10,050 annotated persons. To detect people in aerial and drone images, we propose a multi-stage training procedure to improve YOLOv3’s ability. The proposed procedure aims at addressing challenges such as variations in scenes, scenarios, people poses, as well as image scales and viewing angles. To evaluate the effectiveness of our proposed training procedure, we split our dataset into a training and a test set. The latter includes images acquired during real search and rescue exercises and operations, and is therefore representative for the challenges encountered during operational missions and suitable for an accurate assessment of the proposed models. Experimental results demonstrate the effectiveness of our proposed training procedure, as the model’s average precision exhibits a relevant increase with respect to the baseline value

Long-Range and Short-Range Structure of Proton-Conducting Y:BaZrO3

Yttrium-doped barium zirconate (BZY) is the most promising candidate for proton-conducting ceramics and has been extensively studied in recent years. The detailed features of the crystal structure, both short-range and long-range, as well as the crystal chemistry driving the doping process, are largely unknown. We use very high resolution X-ray diffraction (HR-XRD) to resolve the crystal structure, which is very slightly tetragonally distorted in BZY, while the local environment around Zr4+ and Y3+ is probed with extended X-ray absorption fine structure (EXAFS), and the symmetry and vibrations are investigated by using Raman spectroscopy. It is found that barium zirconate shows some degree of local deviation from the cubic arystotype even if undoped, which upon substitution by the perceptibly larger Y3+, playing the role of a rigid inclusion, is further increased. This distortion is one limiting factor concerning the Y3+ solubility. The effects are correlated to the proton conduction properties of BZY

Sharing Science Through Shared Values, Goals, and Stories: An Evidence-Based Approach to Making Science Matter

Scientists in and beyond academia face considerable challenges to effectively sharing science, including lack of time and training, systemic disincentives, and the complexity of the modern media/attention landscape. Considering these constraints, 3 achievable shifts in mindset and practice can substantively enhance science communication efforts. Here, we provide evidence-based and experientially informed advice on how to center shared values, articulate science communication goals, and leverage the power of stories to advance our communication goals in connection with the values we share with our stakeholders. In addition to a discussion of relevant, foundational principles in science communication, we provide actionable recommendations and tools scientists can immediately use to articulate their values, identify shared values between stakeholders, set science communication goals, and use storytelling as a means of building and reinforcing relationships around shared values, thereby working productively to achieve those goals