3,983 research outputs found
Translating HOL to Dedukti
Dedukti is a logical framework based on the lambda-Pi-calculus modulo
rewriting, which extends the lambda-Pi-calculus with rewrite rules. In this
paper, we show how to translate the proofs of a family of HOL proof assistants
to Dedukti. The translation preserves binding, typing, and reduction. We
implemented this translation in an automated tool and used it to successfully
translate the OpenTheory standard library.Comment: In Proceedings PxTP 2015, arXiv:1507.0837
Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph
As the security landscape evolves over time, where thousands of species of
malicious codes are seen every day, antivirus vendors strive to detect and
classify malware families for efficient and effective responses against malware
campaigns. To enrich this effort, and by capitalizing on ideas from the social
network analysis domain, we build a tool that can help classify malware
families using features driven from the graph structure of their system calls.
To achieve that, we first construct a system call graph that consists of system
calls found in the execution of the individual malware families. To explore
distinguishing features of various malware species, we study social network
properties as applied to the call graph, including the degree distribution,
degree centrality, average distance, clustering coefficient, network density,
and component ratio. We utilize features driven from those properties to build
a classifier for malware families. Our experimental results show that
influence-based graph metrics such as the degree centrality are effective for
classifying malware, whereas the general structural metrics of malware are less
effective for classifying malware. Our experiments demonstrate that the
proposed system performs well in detecting and classifying malware families
within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201
First-Class Subtypes
First class type equalities, in the form of generalized algebraic data types
(GADTs), are commonly found in functional programs. However, first-class
representations of other relations between types, such as subtyping, are not
yet directly supported in most functional programming languages.
We present several encodings of first-class subtypes using existing features
of the OCaml language (made more convenient by the proposed modular implicits
extension), show that any such encodings are interconvertible, and illustrate
the utility of the encodings with several examples.Comment: In Proceedings ML 2017, arXiv:1905.0590
Characterization of the transcriptome, nucleotide sequence polymorphism, and natural selection in the desert adapted mouse Peromyscus eremicus
As a direct result of intense heat and aridity, deserts are thought to be among the most harsh of environments, particularly for their mammalian inhabitants. Given that osmoregulation can be challenging for these animals, with failure resulting in death, strong selection should be observed on genes related to the maintenance of water and solute balance. One such animal, Peromyscus eremicus, is native to the desert regions of the southwest United States and may live its entire life without oral fluid intake. As a first step toward understanding the genetics that underlie this phenotype, we present a characterization of the P. eremicus transcriptome. We assay four tissues (kidney, liver, brain, testes) from a single individual and supplement this with population level renal transcriptome sequencing from 15 additional animals. We identified a set of transcripts undergoing both purifying and balancing selection based on estimates of Tajima’s D. In addition, we used the branch-site test to identify a transcript—Slc2a9, likely related to desert osmoregulation—undergoing enhanced selection in P. eremicus relative to a set of related non-desert rodents
Relational parametricity for higher kinds
Reynolds’ notion of relational parametricity has been extremely influential and well studied for polymorphic programming languages and type theories based on System F. The extension of relational parametricity to higher kinded polymorphism, which allows quantification over type operators as well as types, has not received as much attention. We present a model of relational parametricity for System Fω, within the impredicative Calculus of Inductive Constructions, and show how it forms an instance of a general class of models defined by Hasegawa. We investigate some of the consequences of our model and show that it supports the definition of inductive types, indexed by an arbitrary kind, and with reasoning principles provided by initiality
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