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Survey of Methods for Automated Code-Reuse Exploit Generation

programming AND COMPUTER SOFTWARE 2021年第4期47卷 271-297页

作者： Vishnyakov, A. V. Nurmukhametov, A. R. Russian Acad Sci Ivannikov Inst Syst Programming Moscow 109004 Russia

This paper provides a survey of methods and tools for automated code-reuse exploit generation. Such exploits use code that is already contained in a vulnerable program. The code-reuse approach allows one to exploit vulnerabilities in the presence of operating system protection that prohibits data memory execution. This paper contains a description of various code-reuse methods: return-to-libc attack, return-oriented programming, jump-oriented programming, and others. We define fundamental terms: gadget, gadget frame, gadget catalog. Moreover, we show that, in fact, a gadget is an instruction, and a set of gadgets defines a virtual machine. We can reduce an exploit creation problem to code generation for this virtual machine. Each particular executable file defines a virtual machine instruction set. We provide a survey of methods for gadgets searching and determining their semantics (creating a gadget catalog). These methods allow one to get the virtual machine instruction set. If a set of gadgets is Turing-complete, then a compiler can use a gadget catalog as a target architecture. However, some instructions can be absent. Hence we discuss several approaches to replace missing instructions with multiple gadgets. An exploit generation tool can chain gadgets by pattern searching (regular expressions) or considering gadgets semantics. Furthermore, some chaining methods use genetic algorithms, while others use SMT-solvers. We compare existing open-source tools and propose a testing system rop-benchmark that can be used to verify whether a generated chain successfully opens a shell.

关键词： Computer Science general Software Engineering/programming and Operating systems Operating systems Software Engineering Artificial Intelligence

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Modeling of input signals reflected from coastal zones and observed by small-sized radar systems from UAVs

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JOURNAL OF APPLIED REMOTE SENSING 2022年第1期16卷

作者： Nenashev, Vadim A. Shepeta, Dmitry A. Isakov, Viktor I. St Petersburg State Univ Aerosp Instrumentat Inst Comp Syst & Programming Dept Major Problem Oriented Comp Complexes St Petersburg Russia

When developing modern unmanned aerial vehicle-based onboard small-sized radar systems, which are used for monitoring of coastal zones for their operational and environmental purposes, adequate mathematical models are needed of reflections from the corresponding resolution elements of the underlying surfaces, located on the water-land interface. We consider the development of some mathematical models for such applications. We analyze two modern approaches used in developing mathematical models for input signals reflected both separately from the terrestrial and marine surfaces and simultaneously from two aforementioned surfaces at once. A statistical approach and two families of distributions are chosen for modeling the signals, which enable synthesis of efficient algorithms for modeling the fluxes of random variables. The input signals of sea surface reflections are approximated by the log-normal law, while the reflections from the land surface are approximated by the Weibull distribution. For edge-coastal modeling, it is proposed to use the law of distribution of the vector sum of the flux of random variables comprising the input signals reflected from elementary land and sea areas that simultaneously fall within the corresponding resolution element. A highlight of the models developed is the consideration of both the probability distribution laws of the reflected signals and their correlation-spectral characteristics between resolution elements, as well as the anisotropy of reflections when monitoring surfaces from several angles. The presented mathematical models are consistent with experimental data sets of reflections, obtained from coastal zones. The development of coastal reflection models and corresponding modeling algorithms reduces the required number of actual field tests and saves time for implementation of monitoring systems, and hence, limits the overhead of this implementation. (C) 2021 Society of Photo-Optical instrumentation Engineers (SPIE)

关键词： coastal zone remote sensing small-sized radar system distribution law modeling algorithm UAV

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On domain generators for the evaluation of action reversibility in STRIPS

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2024年 1-28页

作者： Schwartz, Tobias Boockmann, Jan H. Martin, Leon Univ Bamberg Fac Informat Syst & Appl Comp Sci Weberei 5 D-96045 Bamberg Germany Univ Lubeck Inst Software Engn & Programming Languages Ratzeburger Allee 160 D-23562 Lubeck Germany

Robustness is a crucial requirement for the deployment of AI systems in real-world scenarios. In the context of AI planning, the concept of action reversibility, i.e., the ability to undo the effects of an action using a reverse plan, is a promising direction for achieving robust plans. Plans composed exclusively of reversible actions exhibit resilience against goal changes during the execution of the plan. However, the evaluation of action reversibility systems in STRIPS planning presents a challenge, given that standard planning benchmarks are often not suitable. Early experiments using a naive implementation of an action reversibility algorithm show that the available domain generation approach is susceptible to bias. Building on this existing domain generator, we introduce two slight variations that exhibit entirely different search space characteristics. We assess these domain generators using the naive action reversibility implementation and existing ASP implementations, and demonstrate that different generators indeed favor different implementations. As a follow-up to this line of research, we present a generalized domain generator facilitating the creation of domains with diverse search space characteristics. To finally reduce the utilization of contrived generation patterns, we propose another domain generator based on the Barab & aacute;si-Albert model yielding less rigid domains. Our experiments demonstrate that these new domain generators can produce a variety of domains with diverse search space characteristics, enabling a less biased evaluation of action reversibility systems.

关键词： STRIPS planning Action reversibility Benchmark PDDL domain generation

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LAGNet: better electron density prediction for LCAO-based data and drug-like substances

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JOURNAL OF CHEMINFORMATICS 2025年第1期17卷 1-24页

作者： Ushenin, Konstantin Khrabrov, Kuzma Tsypin, Artem Ber, Anton Rumiantsev, Egor Kadurin, Artur AIRI Moscow 121170 Russia Ural Fed Univ Mira St Ekaterinburg 620002 Russia Ecole Polytech Fed Lausanne EPFL Stn Z CH-1015 Lausanne Switzerland Inst Syst Programming Alexander Solzhenitsyn St Moscow 109004 Russia

The electron density is an important object in quantum chemistry that is crucial for many downstream tasks in drug design. Recent deep learning approaches predict the electron density around a molecule from atom types and atom positions. Most of these methods use the plane wave (PW) numerical method as a source of ground-truth training data. However, the drug design field mostly uses the Linear Combination of Atomic Orbitals (LCAO) for computation of quantum properties. In this study, we focus on prediction of the electron density for drug-like substances and training neural networks with LCAO-based datasets. Our experiments show that proper handling of large amplitudes of core orbitals is crucial for training on LCAO-based data. We propose to store the electron density with the standard grids instead of the uniform grid. This allowed us to reduce the number of probing points per molecule by 43 times and reduce storage space requirements by 8 times. Finally, we propose a novel architecture based on the DeepDFT model that we name LAGNet. It is specifically designed and tuned for drug-like substances and del 2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\nabla <^>2$$\end{document}DFT dataset.

关键词： Electron density Deep learning Quantum chemistry Linear combination of atomic orbitals

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Adversarial Attacks and Defenses in Fault Detection and Diagnosis: A Comprehensive Benchmark on the Tennessee Eastman Process

IEEE OPEN JOURNAL OF THE INDUSTRIAL ELECTRONICS SOCIETY

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IEEE OPEN JOURNAL OF THE INDUSTRIAL ELECTRONICS SOCIETY 2024年 5卷 428-440页

作者： Pozdnyakov, Vitaliy Kovalenko, Aleksandr Makarov, Ilya Drobyshevskiy, Mikhail Lukyanov, Kirill AIRI Moscow 121170 Russia ISP RAS Res Ctr Trusted Artificial Intelligence Moscow 109004 Russia Russian Acad Sci Ivannikov Inst Syst Programming Moscow 109004 Russia Natl Res Univ Moscow Inst Phys & Technol Moscow 141700 Russia

Integrating machine learning into Automated Control systems (ACS) enhances decision-making in industrial process management. One of the limitations to the widespread adoption of these technologies in industry is the vulnerability of neural networks to adversarial attacks. This study explores the threats in deploying deep learning models for Fault Detection and Diagnosis (FDD) in ACS using the Tennessee Eastman Process dataset. By evaluating three neural networks with different architectures, we subject them to six types of adversarial attacks and explore five different defense methods. Our results highlight the strong vulnerability of models to adversarial samples and the varying effectiveness of defense strategies. We also propose a new defense strategy based on combining adversarial training and data quantization. This research contributes several insights into securing machine learning within ACS, ensuring robust FDD in industrial processes.

关键词： Training Neural networks Industrial electronics Glass box Predictive models Fault detection Data models Adversarial attacks automated control systems (ACS) defense methods fault detection and diagnosis (FDD) Tennessee Eastman Process

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CASR: Analysis of Core Dump Files in Linux and Error Reporting

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programming AND COMPUTER SOFTWARE 2021年第8期47卷 866-870页

作者： Fedotov, A. N. Kurmangaleev, Sh F. Russian Acad Sci Ivannikov Inst Syst Programming Moscow 109004 Russia

Even though software development uses various technologies and approaches to diagnose bugs in the early stages of development and testing, some bugs are discovered only during operation. To the end user, bugs often look like a program crash while running. To make reports about program crashes, a special analysis component is built into an operating system. Such a component is built into Windows and Linux-based operating systems, in particular, in Ubuntu. An important parameter is the severity of the detected bug, and this information is useful to both the developer of the distribution and the user. In particular, using such diagnostics, users can take organizational and technical measures before the software developer fixes the bug. The paper introduces CASR-a tool for analyzing the memory dump at the time of the process termination (coredump) and for error reporting. This tool helps assess the severity of the program crash by analyzing the memory dump and gather the necessary data for the developer that can help fix the error. This information includes the version of the distribution, the package version, process memory map, state of registers, values of environment variables, call stack, the number of the signal that led to the crash, etc. The severity assessment enables the software developer to fix the bugs that are the most dangerous in the first place. CASR can detect files and network connections that were open at the time of the crash. This information helps reproduce the bug and helps users and administrators take actions in the event of an attack on the system. The tool is designed to work under Linux and supports x86/64 and armv7 architectures and can be supplied as a package for Debian-based distributions. The tool was successfully tested with several bugs reported in open source projects.

关键词： Computer Science general Software Engineering/programming and Operating systems Operating systems Software Engineering Artificial Intelligence

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Sinkhorn Transformations for Single-Query Postprocessing in Text-Video Retrieval 23

Sinkhorn Transformations for Single-Query Postprocessing in ...

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46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

作者： Yakovlev, Konstantin Polyakov, Gregory Alimova, Ilseyar Podolskiy, Alexander Bout, Andrey Nikolenko, Sergey Piontkovskaya, Irina Huawei Noahs Ark Lab Moscow Russia RAS Ivannikov Inst Syst Programming Moscow Russia Steklov Inst Math St Petersburg Dept St Petersburg Russia

ISBN: (纸本)9781450394086

A recent trend in multimodal retrieval is related to postprocessing test set results via the dual-softmax loss (DSL). While this approach can bring significant improvements, it usually presumes that an entire matrix of test samples is available as DSL input. This work introduces a new postprocessing approach based on Sinkhorn transformations that outperforms DSL. Further, we propose a new postprocessing setting that does not require access to multiple test queries. We show that our approach can significantly improve the results of state of the art models such as CLIP4Clip, BLIP, X-CLIP, and DRL, thus achieving a new state-of-the-art on several standard text-video retrieval datasets both with access to the entire test set and in the single-query setting.

关键词： video-text retrieval dual-softmax loss Sinkhorn algorithm

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Complete Decision Procedure for the Theory of Bounded Pointer Arithmetic

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programming AND COMPUTER SOFTWARE 2022年第8期48卷 770-780页

作者： Sadykov, R. F. Mandrykin, M. U. Moscow MV Lomonosov State Univ Moscow 119991 Russia Russian Acad Sci Ivannikov Inst Syst Programming ul Solzhenitsyna 25 Moscow 109004 Russia

The process of developing C programs is quite often prone to errors associated with the use of pointer arithmetic and operations on memory addresses. Hence, the need for various automated program verification tools arises. One of the techniques frequently employed by these tools is invocation of suitable decision procedures implemented within existing SMT solvers. However, both the SMT standard and the majority of existing SMT solvers lack relevant logics (combinations of logical theories) for the direct and precise modeling of the semantics of pointer operations in C. A possible way to support these logics is to implement them in an SMT solver. However, this approach can be time-consuming (as it requires modifying the source code of the solver), inflexible (because introducing any changes to the signature or semantics of the theory can be unreasonably hard), and limited (every solver has to be supported individually). Another way is to design and implement custom quantifier instantiation strategies. These strategies can then be used to translate formulas in selected theory combinations into formulas in well-supported decidable logics, e.g., QF_UFLIA. In this paper, we present an instantiation procedure for translating formulas in the theory of bounded pointer arithmetic into the QF_UFLIA logic. We formally prove the soundness and completeness of our instantiation procedure in Isabelle/HOL. The paper also presents an informal description of this proof for the proposed procedure. The theory of bounded pointer arithmetic itself is formulated based on known errors associated with the use of pointer arithmetic operations in C, as well as based on the semantics of these operations specified in the C standard. Similar procedure can also be defined for a practically relevant fragment of the theory of bit vectors (monotone propositional combinations of equalities between bitwise expressions). Our approach is sufficient to derive efficient decision procedures, implemented as

关键词： Semantics

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Enhancing Cloud Security through Efficient Polynomial Approximations for Homomorphic Evaluation of Neural Network Activation Functions 24

Enhancing Cloud Security through Efficient Polynomial Approx...

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24th IEEE/ACM International Symposium on Cluster, Cloud, and Internet Computing (CCGrid)

作者： Pulido-Gaytani, Bernardo Tchernykh, Andrei Babenko, Mikhail Cortes-Mendoza, Jorge M. Gonzalez-Velez, Horacio Avetisyan, Arutyun CICESE Res Ctr Ensenada Baja California Mexico North Caucasus Fed Univ Stavropol Russia Natl Coll Ireland Dublin Ireland RAS Inst Syst Programming Moscow Russia

ISBN: (纸本)9798350377521;9798350377514

Current security cloud practices can successfully protect stored data and data in transit, but they do not keep the same protection during data processing. The data value extraction requires decryption, creating critical exposure points. As a result, privacy-preserving techniques are emerging as a crucial consideration in cloud computing. The homomorphic processing of machine learning models in the cloud represents a central challenge. The activation function is fundamental in constructing a privacy-preserving Neural Network (NN) with Homomorphic Encryption (HE). Standard activation functions require operations not supported by HE, so it is necessary to find cryptographically compatible replacement functions to operate over encrypted data. Multiple approaches address the limitation of function compatibility with polynomial approximation. These functions should exhibit a trade-off between complexity and accuracy, limiting the efficiency of conventional approximation techniques. The current literature on polynomial approximation of NN activation functions still lacks a thorough review. In this paper, we comprehensively review the standard activation functions of modern NN models and current polynomial approximation approaches. We highlight fundamental features to consider in the activation function and the approximation technique to operate over encrypted data.

关键词： cloud security homomorphic encryption neural networks polynomial approximation privacy-preserving

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Approaches to Cross-Language Retrieval of Similar Legal Documents Based on Machine Learning

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SCIENTIFIC AND TECHNICAL INFORMATION PROCESSING 2023年第5期50卷 494-499页

作者： Zhebel, V. V. Devyatkin, D. A. Zubarev, D. V. Sochenkov, I. V. Technol Syst Anal LLC Moscow 117312 Russia Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow 119333 Russia Innopolis Univ Innopolis 420500 Russia Russian Acad Sci Ivannikov Inst Syst Programming Moscow 109004 Russia

In order to study global experience for legislation changing and rule-making necessitates, tools for information retrieval of regulatory documents written in different languages become increasingly necessary. One of the aspects of information identification is retrieval of thematically similar documents for a given input document. In this context, an important task of cross-lingual search arises when the user of an information system specifies a reference document in one language, and the search results contain relevant documents in other languages. The article describes different approaches to solving this problem: from classic mediator-based methods to more modern solutions, based on distributional semantics. The test collection used in the study was taken from the United Nations Digital Library, which provides legal documents in both the original English and their Russian translations.

关键词： cross-language document retrieval distributional semantics legal information retrieval

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