When Does Relay Transmission Give a More Secure Connection in Wireless Ad Hoc Networks?

Relay transmission can enhance coverage and throughput, while it can be vulnerable to eavesdropping attacks due to the additional transmission of the source message at the relay. Thus, whether or not one should use relay transmission for secure communication is an interesting and important problem. In this paper, we consider the transmission of a confidential message from a source to a destination in a decentralized wireless network in the presence of randomly distributed eavesdroppers. The source-destination pair can be potentially assisted by randomly distributed relays. For an arbitrary relay, we derive exact expressions of secure connection probability for both colluding and non-colluding eavesdroppers. We further obtain lower bound expressions on the secure connection probability, which are accurate when the eavesdropper density is small. By utilizing these lower bound expressions, we propose a relay selection strategy to improve the secure connection probability. By analytically comparing the secure connection probability for direct transmission and relay transmission, we address the important problem of whether or not to relay and discuss the condition for relay transmission in terms of the relay density and source-destination distance. These analytical results are accurate in the small eavesdropper density regime.Comment: Accepted for publication in IEEE Transactions On Information Forensics and Securit

FLuRKA: Fast fused Low-Rank & Kernel Attention

Many efficient approximate self-attention techniques have become prevalent since the inception of the transformer architecture. Two popular classes of these techniques are low-rank and kernel methods. Each of these methods has its own strengths. We observe these strengths synergistically complement each other and exploit these synergies to fuse low-rank and kernel methods, producing a new class of transformers: FLuRKA (Fast Low-Rank and Kernel Attention). FLuRKA provide sizable performance gains over these approximate techniques and are of high quality. We theoretically and empirically evaluate both the runtime performance and quality of FLuRKA. Our runtime analysis posits a variety of parameter configurations where FLuRKA exhibit speedups and our accuracy analysis bounds the error of FLuRKA with respect to full-attention. We instantiate three FLuRKA variants which experience empirical speedups of up to 3.3x and 1.7x over low-rank and kernel methods respectively. This translates to speedups of up to 30x over models with full-attention. With respect to model quality, FLuRKA can match the accuracy of low-rank and kernel methods on GLUE after pre-training on wiki-text 103. When pre-training on a fixed time budget, FLuRKA yield better perplexity scores than models with full-attention.Comment: 9 pages, 4 figure

2-Dicyclo­hexyl­amino-3-phenyl-5,6-di­hydro-8H-thio­pyrano[4′,3′:4,5]thieno[2,3-d]pyrimidin-4(3H)-one

In the title compound, C27H33N3OS2, the dihedral angle between the two fused rings of the thieno[3,2-d]pyrimidine system is 3.73 (9)°. The phenyl ring is twisted with respect to the pyrimidine ring [dihedral angle = 71.60 (10)°] and the thio­pyran ring shows an envelope conformation with the S atom as the flap. An intra­molecular C—H⋯O inter­action occurs. In the crystal, inversion dimers linked by pairs of C—H⋯O hydrogen bonds occur