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Detecting Fault Injection Attacks Based on Compressed Sensing and integer linear programming

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2019年第3期16卷 476-483页

作者： Li, Huiyun Shao, Cuiping Wang, Zheng Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Univ Chinese Acad Sci Shenzhen Coll Adv Technol Shenzhen 518055 Peoples R China Chinese Univ Hongkong Shenzhen 518055 Peoples R China

Cryptographic ICs have been widely applied to numerous security-critical environments nowadays. Fault injection has become a serious attack on cryptographic IC, especially soft-errors or single event upsets (SEUs) by fine-resolution fault injection attacks. Detection and tamper evidence of these attacks become important. Traditional SEU diagnose methods usually require special sensors embedded into the circuits. However, these methods require non-trivial design and test effort, and usually just yield statistic results. In this paper, we formulate the detection fault injection attacks as a compressed sensing problem, due to sparsity of soft errors. Besides, due to the binary characteristic of the coefficient matrix and the variables, integer linear programming is adopted to reconstruct the soft error signals. Simulation results on a cryptographic IC demonstrate that the proposed method is capable to accurately detect the locations of soft-errors caused by fault injection attacks with negligible hardware overhead. The abnormal test output of scan-chains can be tamper evidence of the fault injection attacks.

关键词： Fault injection attacks compressed sensing integer linear programming soft-errors detection tamper evidence

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The Loading Optimization: A Novel integer linear programming Model

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ENTERPRISE INFORMATION SYSTEMS 2019年第10期13卷 1471-1482页

作者： Wang, Lei Ni, Mingfang Gao, Jie Shen, Qingguo Jia, Yongxing Yao, Changhua PLA Army Engn Univ Coll Commun Engn Nanjing Jiangsu Peoples R China JiLin Univ Zhuhai Coll Sch Disciplinary Bacs & Appl Stat Zhuhai Peoples R China

This paper establishes a new integer linear programming model for container loading problem. This model can be used to calculate the optimal loading plan for each container. To solve the model, in this paper, the model problem is decomposed into two easy to solve sub-problems: auxiliary problem (AP) and transportation problem, and prove by solving the two sub-problems can quickly and efficiently to find the optimal solution of the model. Finally, an example is given to illustrate the solution process, which shows that the algorithm can give the optimal stowage scheme quickly and effectively.

关键词： integer linear programming distribution optimisation transportation container

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Lowest thermal transmittance of an external wall under budget, material and thickness restrictions: An integer linear programming approach

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ENERGY AND BUILDINGS 2018年 158卷 222-233页

作者： Soler, David Salandin, Andrea Mico, Joan C. Univ Politecn Valencia Inst Univ Matemat Multidisciplinar Cami Vera S-N E-46022 Valencia Spain Univ Politecn Valencia Ctr Tecnol Fis Cami Vera S-N E-46022 Valencia Spain

This paper deals with the minimization of a building's external wall thermal transmittance, with the aim of improving the energy efficiency of the building. The wall's thermal transmittance must abide by the current legislation, but also suit the limitations of other construction parameters, mainly budget and thickness, but also time limit, workforce, number and thickness of the layers and availability of materials depending on the approach. The optimization is achieved formulating an integer linear programming (ILP) problem involving the parameters mentioned above. Therefore, any available ILP solver can be run to obtain the best combination of the different materials and thicknesses for the layers, in order to minimize the thermal transmittance. This paper presents a case study of a common but representative external wall consisting of 6 layers, with more than 670,000 possible combinations of materials and their thicknesses. The study concludes with a comparison of the lowest thermal transmittance obtained for a selection of budget and thickness combinations for the mentioned wall. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Thermal transmittance Building envelope External wall integer linear programming Building process Budget

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Using integer linear programming for instruction scheduling and register allocation in multi-issue processors

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 1997年第9期34卷 1-14页

作者： Chang, CM Chen, CM King, CT Department of Computer Science National Tsing Hua University Hsinchu Taiwan 300 R.O.C.

Instruction scheduling and register allocation are two very important optimizations in modern compilers for advanced processors. These two optimizations must be performed simultaneously in order to maximize the instruction-level parallelism and to fully utilize the registers [1]. In this paper, we solve register allocation and instruction scheduling simultaneously using integer linear programming (ILP). We have successfully worked out the ILP formulations for the problem with and without register spilling. Two kinds of optimizations are considered: (1) fix the number of free registers and then solve the minimum number of cycles to execute the instructions, or (2) fix the maximum execution cycles for the instructions and solve the minimum number of registers needed. Besides being theoretically interesting, our solution serves as a reference point for other heuristic solutions. The formulations are also applicable to high-level synthesis of ASICs and designs for embedded processors. In these application domains, the code quality is more important than the compilation time.

关键词： integer linear programming compiler optimization instruction scheduling register allocation processor architecture

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Static and dynamic locality optimizations using integer linear programming

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2001年第9期12卷 922-941页

作者： Kandemir, M Banerjee, P Choudhary, A Ramanujam, J Ayguadé, E Penn State Univ Dept Comp Sci & Engn University Pk PA 16802 USA Northwestern Univ Dept Elect & Comp Engn Evanston IL 60208 USA Louisiana State Univ Dept Elect & Comp Engn Baton Rouge LA 70803 USA Univ Politecn Cataluna Dept Arquitectura Comp Ctr Europeu Parallelisme Barcelona 08034 Spain

The delivered performance on modern processors that employ deep memory hierarchies is closely related to the performance of the memory subsystem. Compiler optimizations aimed at improving cache locality are critical in realizing the performance potential of powerful processors. For scientific applications, several loop transformations have been shown to be useful in improving both temporal and spatial locality. Recently, there has been some work in the area of data layout optimizations, i.e., changing the memory layouts of multidimensional arrays from the language-defined default such as column-major storage in Fortran. The effect of such memory layout decisions is on the spatial locality characteristics of loop nests. While data layout transformations are not constrained by data dependences, they have no effect on temporal locality. On the other hand, loop transformations are not readily applicable to imperfect loop nests and are constrained by data dependences. More importantly, loop transformations affect the memory access patterns of all the arrays accessed in a loop nest and, as a result, the locality characteristics of some of the arrays may worsen. This paper presents a technique based on integer linear programming (ILP) that attempts to derive the best combination of loop and data layout transformations. Prior attempts to unify loop and data layout transformations for programs consisting of a sequence of loop nests have been based on heuristics not only for transformations for a single loop nest but also for the sequence in which loop nests will be considered. The ILP formulation presented here obviates the need for such heuristics and gives us a bar against which the heuristic algorithms can be compared, More importantly, our approach is able to transform memory layouts dynamically during program execution. This is particularly useful in applications whose disjoint code segments demand different layouts for a given array. In addition, we show how this formu

关键词： data reuse cache locality memory layouts compiler optimizations cache miss estimation integer linear programming

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Combining variable neighborhood search with integer linear programming for the generalized minimum spanning tree problem

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JOURNAL OF HEURISTICS 2008年第5期14卷 473-499页

作者： Hu, Bin Leitner, Markus Raidl, Guenther R. Vienna Univ Technol Inst Comp Graph & Algorithms A-1040 Vienna Austria

We consider the generalized version of the classical Minimum Spanning Tree problem where the nodes of a graph are partitioned into clusters and exactly one node from each cluster must be connected. We present a Variable Neighborhood Search (VNS) approach which uses three different neighborhood types. Two of them work in complementary ways in order to maximize search effectivity. Both are large in the sense that they contain exponentially many candidate solutions, but efficient polynomial-time algorithms are used to identify best neighbors. For the third neighborhood type we apply Mixed integer programming to optimize local parts within candidate solution trees. Tests on Euclidean and random instances with up to 1280 nodes indicate especially on instances with many nodes per cluster significant advantages over previously published metaheuristic approaches.

关键词： generalized minimum spanning tree variable neighborhood search dynamic programming integer linear programming

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Computational performance evaluation of two integer linear programming models for the minimum common string partition problem

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OPTIMIZATION LETTERS 2016年第1期10卷 189-205页

作者： Blum, Christian Raidl, Gunther R. Ikerbasque Basque Fdn Sci E-48011 Bilbao Spain Univ Basque Country UPV EHU San Sebastian Spain TU Wien Inst Comp Graph & Algorithms Vienna Austria

In the minimum common string partition (MCSP) problem two related input strings are given. "Related" refers to the property that both strings consist of the same set of letters appearing the same number of times in each of the two strings. The MCSP seeks a minimum cardinality partitioning of one string into non-overlapping substrings that is also a valid partitioning for the second string. This problem has applications in bioinformatics e.g. in analyzing related DNA or protein sequences. For strings with lengths less than about 1000 letters, a previously published integer linear programming (ILP) formulation yields, when solved with a state-of-the-art solver such as CPLEX, satisfactory results. In this work, we propose a new, alternative ILP model that is compared to the former one. While a polyhedral study shows the linear programming relaxations of the two models to be equally strong, a comprehensive experimental comparison using real-world as well as artificially created benchmark instances indicates substantial computational advantages of the new formulation.

关键词： Minimum common string partition Bioinformatics integer linear programming Computational comparison

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Gamma deployment problem in grids: hardness and new integer linear programming formulation

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2020年第6期27卷 2740-2759页

作者： Faraj, Marcelo Fonseca Urrutia, Sebastian Sarubbi, Joao F. M. Univ Fed Minas Gerais Comp Sci Dept BR-31270901 Belo Horizonte MG Brazil Univ Vienna Fac Comp Sci A-1010 Vienna Austria Molde Univ Coll Fac Logist N-6410 Molde Norway Fed Ctr Technol Educ Minas Gerais Comp Dept BR-30510000 Belo Horizonte MG Brazil

Vehicular networks are mobile networks designed for the domain of vehicles and pedestrians. These networks are an essential component of intelligent transportation systems and have the potential to ease traffic management, lower accident rates, and offer other solutions to smart cities. One of the most challenging aspects in the design of a vehicular network is the distribution of its infrastructure units, which are called roadside units (RSUs). In this work, we tackle the gamma deployment problem that consists of deploying the minimum number of RSUs in a vehicular network in accordance with a quality of service metric called gamma deployment. This metric defines a vehicle as covered if it connects to some RSUs at least once in a given time interval during its whole trip. Then, the metric parameterizes the minimum percentage of covered vehicles necessary to make a deployment acceptable or feasible. In this paper, we prove that the decision version of the gamma deployment problem in grids is NP-complete. Moreover, we correct the multiflow integer linear programming formulation present in the literature and introduce a new formulation based on set covering that is at least as strong as the multiflow formulation. In experiments with a commercial solver, the set covering formulation widely outperforms the multiflow formulation with respect to running time and linear programming relaxation gap.

关键词： gamma deployment complexity integer linear programming

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Ensemble Segmentation Using Efficient integer linear programming

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2012年第10期34卷 1966-1977页

作者： Alush, Amir Goldberger, Jacob Bar Ilan Univ Fac Engn IL-52900 Ramat Gan Israel

We present a method for combining several segmentations of an image into a single one that in some sense is the average segmentation in order to achieve a more reliable and accurate segmentation result. The goal is to find a point in the "space of segmentations" which is close to all the individual segmentations. We present an algorithm for segmentation averaging. The image is first oversegmented into superpixels. Next, each segmentation is projected onto the superpixel map. An instance of the EM algorithm combined with integer linear programming is applied on the set of binary merging decisions of neighboring superpixels to obtain the average segmentation. Apart from segmentation averaging, the algorithm also reports the reliability of each segmentation. The performance of the proposed algorithm is demonstrated on manually annotated images from the Berkeley segmentation data set and on the results of automatic segmentation algorithms.

关键词： Image segmentation ensemble segmentation integer linear programming correlation clustering EM algorithm

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Solving Rummikub problems by integer linear programming

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COMPUTER JOURNAL 2006年第6期49卷 665-669页

作者： den Hertog, D. Hulshof, P. B. Tilburg Univ NL-5000 LE Tilburg Netherlands

The Rummikub problem of finding the maximal number or value of the tiles that can be placed from your rack onto the table is very difficult, since the number of possible combinations are enormous. We show that this problem can be modeled as an integer linear programming problem. In this way solutions can be found in 1 s. We extend the model such that unnecessary changes of the existing sets on the table are minimized.

关键词： Rummikub game integer linear programming

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