• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2278-2280
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• 1998

This paper discusses a technique that can detect cascading disturbances for automated monitoring and diagnosis systems in power plants. A multi-layered directed AND/OR graph called a disturbance interrelation analysis graph (DIAG) is utilized to represent the relationships among cascading disturbances and trace them. Disturbances that cannot be observed directly from sensors can be traced using techniques similar to interpolations and extrapolations on the DIAG.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.169-172
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• 2015

Dalvik is a virtual machine (VM) that is designed to run Java-based Android applications. A trace-based just-in-time (JIT) compilation technique is currently employed to improve performance of the Dalvik VM. However, due to runtime compilation overhead, the trace-based JIT compiler provides only a few simple optimizations. Moreover, because each trace contains only a few instructions, the trace-based JIT compiler inherently exploits fewer optimization and parallelization opportunities than a method-based JIT compiler that compiles method-by-method. So we propose a new method-based JIT compiler, named DEX2C, in order to improve performance by finding more opportunities for both optimization and parallelization in Android applications. We employ C code as an intermediate product in order to find more optimization opportunities by using the GNU C Compiler (GCC), and we will detect parallelism by using the Intel C/C++ parallel compiler and the AESOP compiler in our future work. In this paper, we introduce our DEX2C compiler, which dynamically translates Dalvik bytecodes (DEX) into C code with method granularity. We also describe a new method-based JIT interface in the Dalvik VM for the DEX2C compiler. Our experiment results show that our compiler and its interface achieve significant performance improvement by up to 15.2 times and 3.7 times on average, in Element Benchmark, and up to 2.8 times for FFT in Smartbench.

• Journal of Korea Multimedia Society
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• v.18 no.6
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• pp.710-722
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• 2015

Counterfeit products have been a major concern in global market. With the emergence of RFID systems, to detect counterfeit products in supply chain is relatively easy. Many anti-counterfeiting techniques for products attached by RFID tag are proposed. Most of the previous anti-counterfeiting techniques are not considering the distribution of the counterfeit from a customer to a customer. Using the ownership transfer protocols we can prevent the counterfeit from being distributed on the supply chain as well as between the customers and the customers. The ownership transfer protocols must be modified for anti-counterfeiting because of the usage of the protocol. In this paper, we modify the ownership transfer protocol proposed by G. Kapoor and S. Piramuthu[1] to be able to detect the counterfeit and track and trace the products in the supply chain. Our proposed protocol consists of three phases: the products delivery phase, the products takeover phase, and the products sale phase. We show that our protocol is anti-counterfeiting as well as secure against the security attacks.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1667-1669
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• 2001

The clack of Insulator, which results from internal or external surges such as electrical, mechanical, and thermal stress, might cause ground fault and a power failure without proper repairs. In order to minimize losses caused by a short-term or long-term power failure, it is necessary to detect the deteriorated insulator as early as possible. To do so, we will develop a new device, which can detect and trace an deteriorated insulator by monitoring its physical change the variation of frequency spectrum. This device will do so by finding a Periodic wave sharp (120 Hz), a peculiar wave generated by defused electricity.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.205-211
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• 2024

The increasing number of botnet attacks incorporating new evasion techniques making it infeasible to completely secure complex computer network system. The botnet infections are likely to be happen, the timely detection and response to these infections helps to stop attackers before any damage is done. The current practice in traditional IP networks require manual intervention to response to any detected malicious infection. This manual response process is more probable to delay and increase the risk of damage. To automate this manual process, this paper proposes to automatically select relevant countermeasures for detected botnet infection. The propose approach uses the concept of flow trace to detect botnet behavior patterns from current and historical network activity. The approach uses the multiclass machine learning based approach to detect and classify the botnet activity into IRC, HTTP, and P2P botnet. This classification helps to calculate the risk score of the detected botnet infection. The relevant countermeasures selected from available pool based on risk score of detected infection.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.4
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• pp.3-11
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• 2003

It is very important to detect and remove original sources of various attacks through networks. One of the effective method to detect the sources is traceback systems. In this paper, we design and implement an agent-based traceback system that does not require the reaction of routers and administrators and does not need numerous log data. In the design, we introduce a traceback server and traceback agents in each network Using sniffing and spoofing, the server transmits a packet with a specific message. The agents detect the packet and provide the information for the server to trace back the original source.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.7
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• pp.267-275
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• 2007

Message races should be detected for debugging message-passing parallel programs because they can cause non-deterministic executions. Specially, it is important to detect the first race in each process because the first race can cause the occurrence of the other races in the same process. The previous techniques for detecting the first races require more than two monitored runs of a program or analyze a trace file which size is proportional to the number of messages. In this paper we introduce an on-the-fly technique to detect the first race in each process without generating any trace file. In the experiment we test the accuracy of our technique with some benchmark programs and it shows that our technique detects the first race in each process in all benchmark programs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.2
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• pp.263-277
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• 2021

Taint analysis techniques are popularly used to detect web vulnerabilities originating from unverified user input data, such as Cross-Site Scripting (XSS) and SQL Injection, in web applications written in JavaScript. To detect such vulnerabilities, it would be necessary to trace variables affected by user-submitted inputs. However, because of the dynamic nature of JavaScript, it has been a challenging issue to identify those variables without running the web application code. Therefore, most existing taint analysis tools have been developed based on dynamic taint analysis, which requires the overhead of running the target application. In this paper, we propose a novel static taint analysis technique using symbol information obtained from the TypeScript (a superset of JavaScript) compiler to accurately track data flow and detect security vulnerabilities in TypeScript code. Our proposed technique allows developers to annotate variables that can contain unverified user input data, and uses the annotation information to trace variables and data affected by user input data. Since our proposed technique can seamlessly be incorporated into the TypeScript compiler, developers can find vulnerabilities during the development process, unlike existing analysis tools performed as a separate tool. To show the feasibility of the proposed method, we implemented a prototype and evaluated its performance with 8 web applications with known security vulnerabilities. We found that our prototype implementation could detect all known security vulnerabilities correctly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3694-3701
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• 2009

This paper suggests that location tracking system by RFID. It uses the location tracking and the authentication to entrance after inserts passive RFID tag into user Identification card. The readers periodically broadcast their signal, and then the readers understand where users are by analyzing them. In one of tracking systems, it is possible to detect the area where user had stayed for the longest time during moving according to signal power, to know user moved path and user next moving path. Also, it can be used in entrance authentication system in security area by using tag ID value which stored to backend server.

• Analytical Science and Technology
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• v.32 no.6
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• pp.233-242
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• 2019

Substance identification is the first step of the REACH registration. It is essential in terms of Classification, Labelling and Packaging (CLP) regulation and because even trace amounts of impurities or additives can affect the classification. In this study, a scheme for the screening, quantification, and interpretation of trace amounts of hazardous inorganic substances is proposed to detect the presence of more than 0.1% hazardous inorganic substances that have been affecting the hazard classification. An exemplary list of hazardous inorganic substances was created from the substances of very high concern (SVHCs) in REACH. Among 201 SVHCs, there were 67 inorganic SVHCs containing at least one or ~2-3 heavy metals, such as As, Cd, Co, Cr, Pb, Sb, and Sn, in their molecular formula. The inorganic SVHCs are listed in excel format with a search function for these heavy metals so that the hazardous inorganic substances, including each heavy metal and the calculated ratio of its atomic weight to molecular weight of the hazardous inorganic substance containing it, can be searched. The case study was conducted to confirm the validity of the established scheme with zinc oxide (ZnO). In a substance that is made of ZnO, Pb was screened by XRF analysis and measured to be 0.04% (w/w) by ICP-OES analysis. After referring to the list, the presence of Pb was interpreted just as an impurity, but not as an impurity relevant for the classification. Future studies are needed to expand on this exemplary list of hazardous inorganic substances using proper regulatory data sources.