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检索条件"机构=Ivannikov Institute for System Programming"

共 374 条记录，以下是31-40 订阅

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MAJORCA: Multi-Architecture JOP and ROP Chain Assembler

MAJORCA: Multi-Architecture JOP and ROP Chain Assembler

引用

2021 ivannikov Ispras Open Conference, ISPRAS 2021

作者： Nurmukhametov, Alexey Vishnyakov, Alexey Logunova, Vlada Kurmangaleev, Shamil Ivannikov Institute For System Programming Of The Ras Russia Moscow Institute Of Physics And Technology Moscow Russia

ISBN: (纸本)9781665423304

Nowadays, exploits often rely on a code-reuse approach. Short pieces of code called gadgets are chained together to execute some payload. Code-reuse attacks can exploit vul-nerabilities in the presence of operating system protection that prohibits data memory execution. The ROP chain construction task is the code generation for the virtual machine defined by an exploited executable. It is crucial to understand how powerful ROP attacks can be. Such knowledge can be used to improve software security. We implement MAJORCA that generates ROP and JOP payloads in an architecture agnostic manner and thoroughly consider restricted symbols such as null bytes that terminate data copying via strcpy. The paper covers the whole code-reuse payloads construction pipeline: cataloging gadgets, chaining them in DAG, scheduling, linearizing to the ready-to-run payload. MAJORCA automatically generates both ROP and JOP payloads for x86 and MIPS. MAJORCA constructs payloads respecting restricted symbols both in gadget addresses and data. We evaluate MAJORCA performance and accuracy with rop-benchmark and compare it with open-source compilers. We show that MAJORCA outperforms open-source tools. We propose a ROP chaining metric and use it to estimate the probabilities of successful ROP chaining for different operating systems with MAJORCA as well as other ROP compilers to show that ROP chaining is still feasible. This metric can estimate the efficiency of OS defences. © 2021 IEEE.

关键词： Benchmarking

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Deriving Distinguishing Sequences for Input/Output Automata

Deriving Distinguishing Sequences for Input/Output Automata

引用

2020 IEEE East-West Design and Test Symposium, EWDTS 2020

作者： Yevtushenko, Nina Burdonov, Igor Kossachev, Alexandr Ivannikov Institute for System Programming of Ras Software Engineering Department Moscow Russia

ISBN: (纸本)9781728198996

Input/Output (I/O) automata are widely used when deriving high quality tests for (components of) complex discrete systems based on so called distinguishing sequences. For I/O automata, the number of distinguishability relations is much bigger than for classical deterministic Finite State Machines (FSM). In order to avoid submitting the same test sequence several number of times, i.e., avoid the "all weather conditions"assumption, the separability relation can be considered. If two Input/Output automata are separable then there exists an input sequence such that after submitting this sequence and observing produced outputs it can be uniquely concluded which automaton is under testing. In this paper, we modify the discipline of applying input sequences and discuss the derivation of separating sequences for automata with mixed states, i.e., states where transitions both under inputs and under outputs are defined, as well as with cycles labeled by outputs. We also illustrate how an adaptive separating sequence can be derived when both automata are input-enabled. © 2020 IEEE.

关键词： Automata theory

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LingvoDoc: Phonology Option Features (Using theExample of the Forest Nenets Languages)

LingvoDoc: Phonology Option Features (Using theExample of th...

引用

2023 ivannikov ISPRAS Open Conference, ISPRAS 2023

作者： Koshelyuk, Natalia Ivannikov Institute for System Programming of the Ras Linguistic Platforms Laboratory Moscow Russia

ISBN: (纸本)9798350349993

The article presents the results of a study of the field material of the Purovsky dialect of the Forest Nenets language. His experimental phonological analysis was conducted using the LingvoDoc data processing algorithms. A comparison of the vowel sound system obtained as a result of this analysis with other phonetic systems of the Forest Nenets language proposed by linguists of the XX-XXI centuries, and its four separate native speakers, allowed us to conclude that this dialect is unique and further research is necessary, taking into account data on contact languages for the Forest Nenets. © 2023 IEEE.

关键词： Data handling

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Scalable thread-modular approach for data race detection 1st

Scalable thread-modular approach for data race detection

引用

1st International Workshop on Frontiers in Software Engineering Education, FISEE 2019

作者： Andrianov, Pavel Mutilin, Vadim Ivannikov Institute for System Programming of the RAS Moscow Institute of Physics and Technology Moscow Russia

ISBN: (纸本)9783030576622

Most of the state-of-the-art verifiers do not scale well on complicated software. Concurrency benchmarks from SV-COMP based on Linux device drivers cause significant difficulties for any software model checker tool. We suggest a method, which is based on the Thread-Modular approach and Configurable Program Analysis theory. It overapproximates a potential thread iteration by a "worst case" assumption, that the threads may change the shared data in any way. The suggestion allows to avoid construction of a precise thread environment and simplifies the analysis. For data race detection we use an extension of the Lockset algorithm based on compatibility of partial states. A BnB memory model allows to deal with complicated data structures without a precise alias analysis. The approach was evaluated on benchmarks set, based on Linux device drivers. The approach allows verifying industrial software, as it was shown on the Linux drivers benchmarks. Predicate abstraction keeps false alarms rate on a reasonable level. © Springer Nature Switzerland AG 2020.

关键词： Linux

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Adaptation of the TOSCA standard model for the Kubernetes container environment

Adaptation of the TOSCA standard model for the Kubernetes co...

引用

2020 ivannikov Memorial Workshop, IVMEM 2020

作者： Borisova, Alexandra Shvetcova, Valeriya Borisenko, Oleg Higher School of Economics Ivannikov Institute for System Programming of the Ras Moscow Russia

ISBN: (纸本)9781728190884

The main difference between container-based and virtualization-based cloud environments is the way of the virtualization methods for OS and auxiliary resources. Software applications can be both deployed in a cloud on virtual machines or in local data centres on physical machines. Containers are based on OS-level virtualization. So, container applications can be deployed on a virtual machine in the cloud too. To deal with the growth of various, but functionally similar cloud environments, the TOSCA [1] (Topology and Orchestration for Cloud Applications) standard was created. It allows to describe deployment resources in a TOSCA Domain-specific language that does not depend on the provider. Kubernetes [8] is an open-source system for deployment automation, scaling, and management of containerized applications. TOSCA standard was created to describe cloud applications, but the model may be suitable for describing container applications that Kubernetes orchestrate. This paper considers Kubernetes as a cloud provider and examines the applicability of the TOSCA standard for unifying deployment and orchestration not only of resources provided by virtualization-based clouds but also of containerized ones. © 2020 IEEE.

关键词： Containers

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Make social networks clean again: Graph embedding and stacking classifiers for bot detection

Make social networks clean again: Graph embedding and stacki...

引用

2018 Conference on Information and Knowledge Management Workshops, CIKM 2018

作者： Skorniakov, Kirill Turdakov, Denis Zhabotinsky, Andrey Ivannikov Institute for System Programming Russian Academy of Sciences Moscow Institute of Physics and Technology State University Moscow Russia Ivannikov Institute for System Programming Russian Academy of Sciences National Research University Higher School of Economics Moscow Russia Ivannikov Institute for System Programming Russian Academy of Sciences Lomonosov Moscow State University Moscow Russia

The paper introduces a novel approach to the detection of social bots using ensembling of classifiers. We also studied the impact of different feature sets and demonstrated the power of graph embedding which is underused by the existing methods. The main contribution of this work is a creating of a stacking based ensemble, which effectively exploits text and graph features. Empirical evaluation proved the effectiveness of the proposed method for bots detection and showed improvement in comparison to existing solutions by 4-9 points of AUC. Copyright © CIKM 2018.

关键词： Knowledge management

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Detection of variable misuse using static analysis combined with machine learning

Detection of variable misuse using static analysis combined ...

引用

2019 ivannikov Ispras Open Conference, ISPRAS 2019

作者： Morgachev, Gleb Ignatyev, Valery Belevantsev, Andrey Ivannikov Institute for System Programming RAS Moscow Institute of Physics and Technology Moscow Russia

ISBN: (纸本)9781728160559

Industrial static analyzers are able to detect only several narrow classes of algorithmic errors, for example actual arguments order swapped with formal parameters, forgotten renaming of variable after copy-paste. However, even for these categories essential part of errors is lost because of heuristical design of a checker. We propose the generalization of specified errors in the form of variable misuse problem and deal with it using machine learning. The proposed method uses message propagation through the program model represented as a graph, combining data from multiple analysis levels, including AST, dataflow. We introduce several error criteria, which were evaluated on the set of open source projects with millions of LoC. Testing in close to industrial conditions shows good false positive and missed errors ratio comparable with remaining detectors and allows to include developed checker (after a minor rework) into a general purpose production static analyzer for error detection. © 2019 IEEE.

关键词： Error detection

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Three-step Algorithms for Detection of High Degree Nodes in Online Social Networks

Three-step Algorithms for Detection of High Degree Nodes in ...

引用

2020 ivannikov Memorial Workshop, IVMEM 2020

作者： Shaikhelislamov, Danil Drobyshevskiy, Mikhail Turdakov, Denis Yatskov, Alexander Varlamov, Maksim Aivazov, Denis Moscow Russia Ivannikov Institute for System Programming Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781728190884

This paper considers the problem of influential users detection in online social networks. Identifying of such key entities is of interest in many areas: marketing, politics, information security, business. The degree of the node of the corresponding graph is used as a popularity indicator in this work. Network query limitation is the main challenge in discovering their structure. Therefore, our task is to detect a percentage of the highest degree network nodes under a budget restriction. We propose a three-step crawling algorithm in two versions to solve the problem. We experimentally show its efficiency at various budget limits and superiority over known crawling strategies. For example, to detect top-1% of hubs with 90% precision, one needs to crawl 5% of graph nodes in average with our 3-StepBatch algorithm. We also show that our algorithm performs well for different target set sizes, from 0.01% to 10% of the graph. © 2020 IEEE.

关键词： Social networking (online)

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A Survey of Open-source Tools for FPGA-based Inference of Artificial Neural Networks

A Survey of Open-source Tools for FPGA-based Inference of Ar...

引用

2021 ivannikov Memorial Workshop, IVMEM 2021

作者： Lebedev, Mikhail Belecky, Pavel Plekhanov Russian University of Economics Ivannikov Institute for System Programming RAS Moscow Russia

ISBN: (纸本)9781665423274

During the recent years artificial neural networks have become a great part of everyday life. One of the big problems in AI is acceleration of neural network inference using different hardware: from CPUs and GPUs to FPGAs and ASICs. Many open-source tools have been proposed for this purpose. This article contains a review of a range of open-source tools for neural network optimization, acceleration and hardware synthesis. Tools of three types have been chosen for evaluation: 1) translating neural network models into synthesizable C;2) accelerating neural network models using custom hardware accelerators;3) synthesizing Verilog from neural network models. Some of the tools have been tested using five simple neural network examples. Intel CPU, NVIDIA GPU and Cyclone V FPGA hardware platforms have been used for evaluation. Results show that the tested tools can successfully process neural network models and optimize them for CPU and GPU execution, whereas FPGA execution results are controversial. © 2021 IEEE.

关键词： Neural network models

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Using Lingvodoc platform for researching genetic and areal semantic shifts: the case of Ob-Ugric basic vocabulary

Using Lingvodoc platform for researching genetic and areal s...

引用

2022 ivannikov Open Conference, ISPRAS 2022

作者： Fedotova, Idaliya Hse University Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9798350398533

Typology of semantic shifts has been in the focus of linguistic typology for the last 20 years. Emergence of cross-linguistic databases and linguistic platforms has taken the study of semantic changes to the new level, as it enlarged the sample of the languages under investigation. Yet the languages of Russia are only scarcely represented in the global databases and do not make a substantial contribution to this field. The LingvoDoc platform, which stores unique materials on the languages of Russia, upon certain enhancements can fill in this gap. © 2022 IEEE.

关键词： Semantics

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