• Journal of Korea Multimedia Society
• /
• v.16 no.6
• /
• pp.735-745
• /
• 2013

The emergence of Web 2.0 technologies, such as blogs and wiki, enable even naive users to easily create and share content on the Web using freely available content sharing tools. Wide availability of almost free data and promiscuous sharing of content through social networking platforms created a content borrowing phenomenon, where the same content appears (in many cases in the form of extensive quotations) in different outlets. An immediate side effect of this phenomenon is that identifying which content is re-used by whom is becoming a critical tool in social network analysis, including expert identification and analysis of information flow. Internet-scale reuse detection, however, poses extremely challenging scalability issues: considering the large size of user created data on the web, it is essential that the techniques developed for content-reuse detection should be fast and scalable. Thus, in this paper, we propose a $qSign_{lsh}$ algorithm, a mechanism for identifying multi-sentence content reuse among documents by efficiently combining sentence-level evidences. The experiment results show that $qSign_{lsh}$ significantly improves the reuse detection speed and provides high recall.

• International journal of advanced smart convergence
• /
• v.5 no.4
• /
• pp.54-56
• /
• 2016

Code-reuse attacks are very dangerous in various systems. This is because they do not inject malicious codes into target systems, but reuse the instruction sequences in executable files or libraries of target systems. Moreover, code-reuse attacks could be more harmful to IoT systems in the sense that it may not be easy to devise efficient and effective mechanism for code-reuse attack detection in resource-restricted IoT devices. In this paper, we propose a detection scheme with using Kullback-Leibler (KL) divergence to combat against code-reuse attacks in IoT. Specifically, we detect code-reuse attacks by calculating KL divergence between the probability distributions of the packets that generate from IoT devices and contain code region addresses in memory system and the probability distributions of the packets that come to IoT devices and contain code region addresses in memory system, checking if the computed KL divergence is abnormal.

• Journal of Korean Medical classics
• /
• v.34 no.1
• /
• pp.37-45
• /
• 2021

Objectives : The purpose of this paper was to examine quantitative methods for estimating and detecting local text reuse in the texts of East Asian Traditional Medicine. Methods : We introduce techniques that estimate the volume of local text reuse with n-gram and those that directly detect the reuse with the Smith-Waterman algorithm (SW algorithm). Based on this, the estimation and detection of local text reuse were carried out for 『Donguibogam』 and 『Huangdineijing·Suwen』. Results : Estimates with n-gram had more errors than methods with SW algorithms. SW algorithms detected suspected strings directly with local text reuse, resulting in more accurate results. Conclusions : Although n-gram does not accurately find local text reuse, its high speed makes it a preferable method for certain purposes, such as screening similar documents. On the other hand, SW algorithms have the advantage of being relatively good at finding similar phrases suspected as local text reuse even if the strings do not completely match. However, due to its excessive consumption of time and computing resources, its benefits are limited to cases where precise results are required.

• Journal of Communications and Networks
• /
• v.10 no.2
• /
• pp.127-136
• /
• 2008

For mobile wireless systems with full frequency reuse, co-channel interference near the cell coverage boundaries has a significant impact on the signal reception performance. This paper addresses an approach to efficiently mitigate the effect of downlink co-channel interference when multi-antenna terminals are used in cellular environments, by proposing a signal detection strategy combined with a system-level coordination for dynamic frequency reuse. We demonstrate the utilization of multi-antennas to perform spatial demultiplexing of both the desired signal and interfering signals from adjacent cells results in significant improvement of spectral efficiency compared to the maximal ratio combining (MRC) performance, especially when an appropriate frequency reuse based on the traffic loading condition is coordinated among cells. Both analytic expressions for the capacity and experimental results using the adaptive modulation and coding (AMC) are used to confirm the performance gain. The robustness of the proposed scheme against varying operational conditions such as the channel estimation error and shadowing effects are also verified by simulation results.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.04a
• /
• pp.424-427
• /
• 2015

근래 들어 모바일 기기의 시스템을 장악하여 사용자의 기밀 정보를 빼내는 악성 행위의 한 방법으로 Code Reuse Attack (CRA)이 널리 사용되고 있다. 이와 같은 CRA를 막기 위하여 call-return이 일어날 때마다 이들 address를 비교해 보는 shadow stack과 branch에 대한 몇 가지 규칙을 두어 CRA 를 탐지하는 branch regulation과 같은 방식이 연구되었다. 우리는 shadow stack과 branch regulation을 종합하여 여러 종류의 CRA를 적은 성능 오버헤드로 탐지할 수 있는 CRA Detection System을 만들고자 한다. 이를 위하여 반드시 선행 되어야 할 연구인 바이너리 파일 분석과 meta-data 생성 및 압축 기술을 제안한다. 실험 결과 생성된 meta-data는 압축 기술을 적용하기 전보다 1/2에서 1/3 가량으로 그 크기가 줄어들었으며 CRA Detection System의 탐지가 정상적으로 동작하는 것 또한 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.6
• /
• pp.2576-2590
• /
• 2020

The fundamental reason why most SQL injection detection methods are difficult to use in practice is the low reusability of the implementation code. This paper presents a reusable SQL injection detection method for Java Web applications based on AOP (Aspect-Oriented Programming) and dynamic taint analysis, which encapsulates the dynamic taint analysis processes into different aspects and establishes aspect library to realize the large-grained reuse of the code for detecting SQL injection attacks. A metamodel of aspect library is proposed, and a management tool for the aspect library is implemented. Experiments show that this method can effectively detect 7 known types of SQL injection attack such as tautologies, logically incorrect queries, union query, piggy-backed queries, stored procedures, inference query, alternate encodings and so on, and support the large-grained reuse of the code for detecting SQL injection attacks.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.04a
• /
• pp.502-505
• /
• 2014

최근 들어, 모바일 기기의 시스템을 장악하여 중요 정보를 빼내는 등의 악성 행위를 위해 Code Reuse Attack (CRA) 이 널리 사용되고 있다. 이러한 CRA 를 막기 위한 방법으로 branch 의 trace 를 분석하여 CRA 고유의 특성을 찾아내는 Signature 기반 탐지 기술이 있다. 이러한 탐지 기술을 효율적으로 지원하기 위하여, 본 논문에서는 ARM 프로세서용 바이너리를 분석하여, signature 분석을 위해 필수적으로 분석되어야 하는 gadget 의 크기를 빠르게 접근할 수 있는 meta-data 를 생성하는 기술을 제안한다. 이러한 meta-data 를 활용하는 방식은 gadget 의 크기를 계산하는 추가적인 코드의 수행을 제거해 주므로, 더욱 효율적으로 CRA 를 탐지할 수 있도록 도와준다. 실험 결과, 이러한 meta-data 는 본래의 바이너리 코드 대비 9% 만의 크기 증가를 일으키는 것으로 나타났다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.06a
• /
• pp.185-187
• /
• 2018

This paper presents an aircraft detection on panchromatic image using densely connected convolutional network. This algorithm connects all preceding feature-maps to all subsequent layers. It is encouraged to reuse feature-maps and enhance feature-maps representation. This algorithm is driven to learn aircraft feature to detect aircraft objects on panchromatic imagery. Based on the experimental result, it can yield accuracy of 92%.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.443-446
• /
• 2014

Code reuse attack (CRA)는 기존의 코드 내에서 필요한 코드 조각들 (gadgets)을 모아 indirect branch 명령어들로 잇는 방식으로 공격자가 원하는 악성 프로그램을 구성할 수 있는 강력한 공격 방법이다. 공격자는 자신의 코드를 대상 시스템에 심는 대신 기존의 코드를 이용하기 때문에, 대부분의 범용 운영체제 (OS)가 강제하는 W^X protection 을 무력화할 수 있다. 이러한 CRA 에 대응하기 위하여 다수의 연구들에서 branch 의 trace 를 분석하여 CRA 고유의 특성을 찾아내는 Signature 기반 탐지 기술을 제안하였다. 본 논문에서는 ARM 프로세서 상에서의 CRA 를 대응하기 위한 Signature 기반 탐지 기술을 효율적으로 도울 수 있는 binary 분석 및 meta-data 생성 기술을 제안한다. 특히, 본 논문은 우리의 이전 논문에서 고려 되지 못했던 ARM 의 두 가지 명령어 세트의 특성을 고려하여, 공격자가 어느 명령어 세트를 이용하여 CRA 를 시도하더라도 막아낼 수 있도록 meta-data 를 두 가지 mode 에 대해서 생성하였다. 실험 결과, meta-data 는 본래 바이너리 코드 대비 20.8% 정도의 크기 증가를 일으키는 것으로 나타났다.

• Journal of Information Technology Services
• /
• v.7 no.3
• /
• pp.271-286
• /
• 2008

The core of the semantic web is ontology, which supports interoperability among semantic web applications and enables developer to reuse and share domain knowledge. It used a variety of fields such as Information Retrieval, E-commerce, Software Engineering, Artificial Intelligence and Bio-informatics. However, the reality is that various errors might be included in conceptual hierarchy when developing ontologies. Therefore, methodologies and supporting tools are essential to help the developer construct suitable ontologies for the given purposes and to detect and analyze errors in order to verify the inconsistency in the ontologies. In this paper we propose a new approach for ontology error detection based on the Concept Lattices of Formal Concept Analysis. By using the tool that we developed in this research, we can extract core elements from the source code of Ontology and then detect some structural errors based on the concept lattices. The results of this research can be helpful for ontology engineers to support error detection and construction of "well-defined" and "good" ontologies.