• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2084-2100
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• 2020

Operating system (OS) kernel function call graphs have been widely used in OS analysis and defense. However, most existing methods and tools for generating function call graphs are designed for application programs, and cannot be used for generating OS kernel function call graphs. This paper proposes a virtualization-based call graph generation method called Acquire in Trap (AIT). When target kernel functions are called, AIT dynamically initiates a system trap with the help of a virtualization technique. It then analyzes and records the calling relationships for trap handling by traversing the kernel stacks and the code space. Our experimental results show that the proposed method is feasible for both Linux and Windows OSs, including 32 and 64-bit versions, with high recall and precision rates. AIT is independent of the source code, compiler and OS kernel architecture, and is a universal method for generating OS kernel function call graphs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.3076-3092
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• 2020

An IKPCA-ELM-based intrusion detection method is developed to address the problem of the low accuracy and slow speed of intrusion detection caused by redundancies and high dimensions of data in the network. First, in order to reduce the effects of uneven sample distribution and sample attribute differences on the extraction of KPCA features, the sample attribute mean and mean square error are introduced into the Gaussian radial basis function and polynomial kernel function respectively, and the two improved kernel functions are combined to construct a hybrid kernel function. Second, an improved particle swarm optimization (IPSO) algorithm is proposed to determine the optimal hybrid kernel function for improved kernel principal component analysis (IKPCA). Finally, IKPCA is conducted to complete feature extraction, and an extreme learning machine (ELM) is applied to classify common attack type detection. The experimental results demonstrate the effectiveness of the constructed hybrid kernel function. Compared with other intrusion detection methods, IKPCA-ELM not only ensures high accuracy rates, but also reduces the detection time and false alarm rate, especially reducing the false alarm rate of small sample attacks.

• 대한임베디드공학회논문지
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• 제2권3호
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• pp.145-154
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• 2007

Dynamic update of kernel can change kernel functionality and fix bugs in runtime. Dynamic update is important because it leverages availability, reliability and flexibility of kernel. An instruction-granularity update technique has been used for dynamic update. However, it is difficult to apply update technique for a commodity operating system kernel because development and maintenance of update code must be performed with assembly language. To overcome this difficulty, we design the function-granularity dynamic update system which uses high-level language such as C language. The proposed update system makes the development and execution of update convenient by providing the development environment for update code which is same for kernel development. We implement this system for Linux and demonstrate an example of update for do_coredump() function which is reported it has a vulnerable point for security. The update was successfully executed.

• 한국정보통신학회논문지
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• 제11권1호
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• pp.173-180
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• 2007

본 논문은 리눅스 커널 운영체제에서 커널 개발자의 실수나 의도하지 않은 오류 및 시스템 오류로 인하여 발생되는 시스템 정지 현상을 줄이기 위해서 커널 스택의 복구를 통한 커널 하드닝 기능을 구현한다. 본 논문에서 제안하는 커널 하드닝 기능은 panic이 발생한 커널 주소에 대해서 커널 스택 내의 값들을 정상적인 값으로 복구함으로써 정상적인 시스템 동작을 보장한다 본 논문에서 제안한 커널 하드닝 기능을 리눅스 커널 중에서 많이 사용하는 네트워크 모듈에 적용하였다. 커널 스택 복구를 통한 커널 하드닝 기능의 실험을 위하여 네트워크 모듈에 강제적인 panic 현상을 유발시키고, 잘못된 스택 값의 복구를 통해서 정상 동작을 실험하였다.

• 호남수학학술지
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• 제35권2호
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• pp.235-249
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• 2013

It is well known that each kernel function defines primal-dual interior-point method (IPM). Most of polynomial-time interior-point algorithms for linear optimization (LO) are based on the logarithmic kernel function ([9]). In this paper we define new eligible kernel function and propose a new search direction and proximity function based on this function for LO problems. We show that the new algorithm has $\mathcal{O}(({\log}\;p)^{\frac{5}{2}}\sqrt{n}{\log}\;n\;{\log}\frac{n}{\epsilon})$ and $\mathcal{O}(q^{\frac{3}{2}}({\log}\;p)^3\sqrt{n}{\log}\;\frac{n}{\epsilon})$ iteration complexity for large- and small-update methods, respectively. These are currently the best known complexity results for such methods.

• 대한공간정보학회지
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• 제21권2호
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• pp.19-25
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• 2013

최근 고해상도 위성영상은 자연자원이나 환경 관리에 필요로 하는 토지 피복 및 이용 현황자료 분석 등에 유용하게 사용되고 있다. 영상처리 알고리즘 중 SVM 알고리즘은 최근 다양한 분야에서 이용되고 있다. 그러나 SVM 알고리즘은 다양한 커널 함수 및 매개변수에 의해 그 정확도가 달라진다. 따라서 본 논문에서는 SVM 알고리즘의 대표적 커널 함수를 KOMPSAT-2의 영상자료에 적용하고 토지피복결과를 검사점을 이용하여 정확도 분석을 실시하였다. 또한 대상지의 토지피복분류에 적합한 SVM의 커널 함수 선정하기 위해 분석을 실시하였다. 그 결과 전체 분류 정확도에는 Polynomial 커널 함수가 가장 높은 정확도를 보였으며 분류 항목별 정확도에서의 가장 적절한 커널 함수는 Polynomial, RBF 커널 함수임을 알 수 있었다.

• 음성과학
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• 제12권4호
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• pp.17-29
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• 2005

Time-frequency representation reveals some useful information about instantaneous frequency, instantaneous bandwidth and boundary of each AM-FM component of a speech signal. In many cases, the instantaneous frequency of each component is not constant. The variability of instantaneous frequency causes degradation of resolution in time-frequency representation. This paper presents a method of adaptively adjusting the transform kernel for preventing degradation of resolution due to time-varying instantaneous frequency. The transform kernel is the form of frequency modulated function. The modulation function in the transform kernel is determined by the estimate of instantaneous frequency which is approximated by first order polynomial at each time instance. Also, the window function is modulated by the estimated instantaneous. frequency for mitigation of fringing. effect. In the proposed method, not only the transform kernel but also the shape and the length of. the window function are adaptively adjusted by the instantaneous frequency of a speech signal.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.1045-1046
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• 2015

When using the Support Vector Machine in the online signature verification, SVM kernel function should be chosen to use non-linear SVM and the constant parameters in the kernel functions should be adjusted to appropriate values to reduce the error rate of signature verification. Non-linear SVM which is built on a strong mathematical basis shows better performance of classification with the higher discrimination power. However, choosing the kernel function and adjusting constant parameter values depend on the heuristics of the problem domain. In the signature verification, this paper deals with the problems of selecting the correct kernel function and constant parameters' values, and shows the kernel function and coefficient parameter's values with the minimum error rate. As a result of this research, we expect the average error rate to be less than 1%.

• Journal of applied mathematics & informatics
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• 제27권1_2호
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• pp.419-426
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• 2009

In expansion of function by special basis functions, properties of expansion kernel are very important. In the Fourier series, the series are expressed by the convolution with Dirichlet kernel. We investigate some of properties of kernel in wavelet expansions both in one and higher dimensions.

• 대한수학회보
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• 제31권1호
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• pp.115-123
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• 1994

The Bergman kernel is closely connected to mapping problems in complex analysis. For example, the Riemann mapping function is witten down in terms of the Bergman kernel. Hence, information about the bergman kernel gives information about mappings. In this note, we prove the following theorem.