KLEIN: A New Family of Lightweight Block Ciphers

Resource-efficient cryptographic primitives become fundamental for realizing both security and efficiency in embedded systems like RFID tags and sensor nodes. Among those primitives, lightweight block cipher plays a major role as a building block for security protocols. In this paper, we describe a new family of lightweight block ciphers named KLEIN, which is designed for resource-constrained devices such as wireless sensors and RFID tags. Compared to the related proposals, KLEIN has advantage in the software performance on legacy sensor platforms, while in the same time its hardware implementation can also be compact

Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks

While the use of bottom-up local operators in convolutional neural networks (CNNs) matches well some of the statistics of natural images, it may also prevent such models from capturing contextual long-range feature interactions. In this work, we propose a simple, lightweight approach for better context exploitation in CNNs. We do so by introducing a pair of operators: gather, which efficiently aggregates feature responses from a large spatial extent, and excite, which redistributes the pooled information to local features. The operators are cheap, both in terms of number of added parameters and computational complexity, and can be integrated directly in existing architectures to improve their performance. Experiments on several datasets show that gather-excite can bring benefits comparable to increasing the depth of a CNN at a fraction of the cost. For example, we find ResNet-50 with gather-excite operators is able to outperform its 101-layer counterpart on ImageNet with no additional learnable parameters. We also propose a parametric gather-excite operator pair which yields further performance gains, relate it to the recently-introduced Squeeze-and-Excitation Networks, and analyse the effects of these changes to the CNN feature activation statistics.Comment: NeurIPS 201

NASA helicopter transmission system technology program

The purpose of the NASA Helicopter Transmission System Technology Program is to improve specific mechanical components and the technology for combining these into advanced drive systems to make helicopters more viable and cost competitive for commerical applications. The history, goals, and elements of the program are discussed

Smart Ticket Protection: An Architecture for Cyber-Protecting Physical Tickets Using Digitally Signed Random Pattern Markers

In order to counter forgeries of tickets for public transport or mass events, a method to validate them, using printed unique random pattern markers was developed. These markers themselves are unforgeable by their physically random distribution. To assure their authenticity, however, they have to be cryptographically protected and equipped with an environment for successful validation, combining physical and cyber security protection. This paper describes an architecture for cryptographically protecting these markers, which are stored in Aztec codes on physical tickets, in order to assure that only an authorized printer can generate a valid Aztec code of such a pattern, thus providing forge protection in combination with the randomness and uniqueness of the pattern. Nevertheless, the choice of the signature algorithm is heavily constrained by the sizes of the pattern, ticket provider data, metadata and the signature confronted by the data volume the code hold. Therefore, this paper also defines an example for a signature layout for the proposed architecture. This allows for a lightweight ticket validation system that is both physically and cryptographically secured to form a smart solution for mass access verification for both shorter to longer periods at relatively low cost.Comment: 4 pages, 2 figure