• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.1036-1042
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• 2011

This paper presents an algorithm that conducts automatic memory scrubbing operated by dedicated hardwares. The proposed algorithm is designed so that it can scrub entire memory in a given scrub period, while minimally affecting the execution of flight softwares. The scrub controller is constructed in a form of state machines, which have two execution modes - normal mode and burst mode. The deadline event generator and period tick generator are designed in a separate way to support the behavior of the scrub controller. The proposed controller is implemented in VHDL code to validate its applicability. A simple version of the controller is also applied to mass memory modules used in STSAT-3.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.435-446
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• 2011

Microprocessors are becoming increasingly vulnerable to soft errors due to the current trends of semiconductor technology scaling. Traditional redundant multi-threading architectures provide perfect fault tolerance by re-executing all the computations. However, such a full re-execution technique significantly increases the verification workload on the processor resources, resulting in severe performance degradation. This paper presents a pro-active verification management approach to mitigate the verification workload to increase its performance with a minimal effect on overall reliability. An anomaly-speculation-based filter checker is proposed to guide a verification priority before the re-execution process starts. This technique is accomplished by exploiting a value similarity property, which is defined by a frequent occurrence of partially identical values. Based on the biased distribution of similarity distance measure, this paper investigates further application to exploit similar values for soft error tolerance with anomaly speculation. Extensive measurements prove that the majority of instructions produce values, which are different from the previous result value, only in a few bits. Experimental results show that the proposed scheme accelerates the processor to be 180% faster than traditional fully-fault-tolerant processor with a minimal impact on overall soft error rate.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1197-1207
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• 2018

PowerShell is command line shell and scripting language, built on the .NET framework, and it has several advantages as an attack tool, including built-in support for Windows, easy code concealment and persistence, and various pen-test frameworks. Accordingly, malwares using PowerShell are increasing rapidly, however, there is a limit to cope with the conventional malware detection technique. In this paper, we propose an improved monitoring method to observe commands executed in the PowerShell and a deep learning based malware classification model that extract features from commands using Convolutional Neural Network(CNN) and send them to Recurrent Neural Network(RNN) according to the order of execution. As a result of testing the proposed model with 5-fold cross validation using 1,916 PowerShell-based malwares collected at malware sharing site and 38,148 benign scripts disclosed by an obfuscation detection study, it shows that the model effectively detects malwares with about 97% True Positive Rate(TPR) and 1% False Positive Rate(FPR).

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.559-570
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• 2003

Automation of programming-error detection is an important part of intelligent programming language tutoring systems. In this paper, a new programming error detection approach for novice programmers is proposed by plan matching and program execution. Program execution result is used to resolve the restricted programming plan representation and to provide a confirming evidence for the plan matching differences. By checking the values of shared variable between the related plans, we can detect the cause-effect relationship between the plans. With this relationship and the test data, we can explain the program's unexpected behaviors according to the bug's cause and resulting effects.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1287-1294
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• 2004

Recently relationships between reliability measures and the coverage have been developed for evaluation of software reliability. Particularly the mean value function of the coverage-based software reliability growth model is important because of its key role in rep-resenting the software reliability growth. In this paper, we first review the problems of the existing mean value functions with respect to the assumptions on which they are based. Then a new mean value function is proposed. The new mean value function is developed for a general testing environment in which imperfect fault detection and repeated construct execution are allowed. Finally performance of the proposed model is empirically evaluated by applying it to a real data set.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.517-522
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• 2002

Mobile agent systems offer a new paradigm for distributed computation and a one of solution for limitation of existent Client-server model. Mobile agent systems provide interface that can migrate from host to host in a heterogenous network. For secure execution, it must solve security problem of mobile code before. In this paper, we are propose the protocol that applied signature technique and hash chain technique. This protocol enable one to offer forward integrity, non-repudiation, and forgery detection, when mobile agents are perform the task by migrating a network.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.55-64
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• 2010

This paper proposes a face detection method using Free Rectangle feature which possesses a quick execution time and a high efficiency. The proposed mask of Free Rectangle feature is composed of two separable rectangles with the same area. In order to increase the feature diversity, Haar-like feature generally uses a complex mask composed of two or more rectangles. But the proposed feature mask can get a lot of very efficient features according to any position and scale of two rectangles on the feature window. Moreover, the Free Rectangle feature can largely reduce the execution time since it is defined as the only difference of the sum of pixels of two rectangles irrespective of the mask type. Since it yields a quick detection speed and good detection rates on real world images, the proposed face detection method based on Adaboost algorithm is easily applied to detect another object by changing the training dataset.

• ETRI Journal
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• v.38 no.1
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• pp.206-215
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• 2016

The detection of gene-gene interactions during genetic studies of common human diseases is important, and the technique of multifactor dimensionality reduction (MDR) has been widely applied to this end. However, this technique is not free from the "curse of dimensionality" -that is, it works well for two- or three-way interactions but requires a long execution time and extensive computing resources to detect, for example, a 10-way interaction. Here, we propose a boosting method to reduce MDR execution time. With the use of pre-evaluation measurements, gene sets with low levels of interaction can be removed prior to the application of MDR. Thus, the problem space is decreased and considerable time can be saved in the execution of MDR.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.473-479
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• 2013

This paper introduces user intervention to control simulation states during the execution of a simulation for military engagements. In an engagement simulation, it covers both a discrete event system and a continuous state system. Thus a system for the engagement simulation can have numerous simulation states, because there are lots of factors to decide states of an engagement that are derived during an execution of the simulation (e. g. detection probability, moving speed, moving path, and so on). It means both a result and progression of simulations are important outputs. Configuration of an engagement simulation scenario and expectation of simulation states, though, is hindered by the number of generate-able states. In order to solve the obstacle, the engagement simulation system should be controllable by user intervention during a simulation execution. This paper is to define objects of user intervention, and to design control processes of defined objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3885-3906
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• 2020

Hybrid fuzzing which combines fuzzing and concolic execution, has proved its ability to achieve higher code coverage and therefore find more bugs. However, current hybrid fuzzers usually suffer from inefficiency and poor scalability when applied to complex, real-world program testing. We observed that the performance bottleneck is the inefficient cooperation between the fuzzer and concolic executor and the slow symbolic emulation. In this paper, we propose a novel solution named EPfuzzer to improve hybrid fuzzing. EPfuzzer implements two key ideas: 1) only the hardest-to-reach branch will be prioritized for concolic execution to avoid generating uninteresting inputs; and 2) only input bytes relevant to the target branch to be flipped will be symbolized to reduce the overhead of the symbolic emulation. With these optimizations, EPfuzzer can be efficiently targeted to the hardest-to-reach branch. We evaluated EPfuzzer with three sets of programs: five real-world applications and two popular benchmarks (LAVA-M and the Google Fuzzer Test Suite). The evaluation results showed that EPfuzzer was much more efficient and scalable than the state-of-the-art concolic execution engine (QSYM). EPfuzzer was able to find more bugs and achieve better code coverage. In addition, we discovered seven previously unknown security bugs in five real-world programs and reported them to the vendors.