Browsing by Author "Hsu, Chia-Wei"

Now showing 1 - 18 of 18

52.5% Data Rate Improvement by Employing Volterra Filtering and Exponential Companding in a High Loss Budget and High-Capacity OFDM Long-Reach PON
(2016)
Chen, Hsing-Yu
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Wei, Chia-Chien
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Liu, Jun-Jie
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Hsu, Chia-Wei
;
Wu, Hsin-Yu
An exponential companding method cooperating with Volterra filtering is proposed and demonstrated to substantially improve data rate by 52.5% in a 53.3-Gbps 60-km OFDM LR-PON with 30-dB loss budget based on 10-GHz EAM and PIN.
67.6% Improvement in Data Rate Employing Partial Transmit Sequence for PAPR Reduction and Volterra Filtering in an OFDM Long-Reach PON
(2017-01-01)
Chuang, Chun-Yen
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Hsu, Chia-Wei
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Wei, Chia-Chien
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Liu, Jun-Jie
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Nguyen, Hong-Minh
We applied partial transmit sequence and Volterra filtering to achieve 67.6% improvement in capacity in a high-launch-power 60-km OFDM LR-PON. 61-Gbps capacity and 30-dB loss budget were realized to support 64 ONUs with 0.95 Gbps/ONU.
Adaptive Virtual Gestures for GUI Testing on Smartphones
(2017-09-01)
Hsu, Chia-Wei
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Lee, Shan-Hsin
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Shieh, Shiuhpyng Winston
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資訊工程學系
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Department of Computer Science
Traditional in-depth testing isn't optimal for mobile apps because they're updated frequently in response to bugs and security concerns. To complement such testing, a proposed breadth-first approach employs fast, automated GUI testing for adaptive virtual gestures on various mobile devices.
An image based optical lens eccentric error inspection system
(2012)
Chen, Yung-Hsiang
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Hsieh, Yao-Fang
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Hsu, Chia-Wei
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Ou-Yang, Mang
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Lee, Cheng-Chung
In this study, we have presented the prototype of optical lens eccentric error inspection system based on image processing algorithms. The traditional inspection by using the transmission or reflection measurements is limited to the geometry and size of the lens. In this study, an image based inspection system has developed target on fast, accurate and low-cost to meet the need for lens eccentric error inspection.
Can Malware Be Exterminated by Better Understanding Its Roots?
(2014-11-01)
Cho, Michael Cheng Yi
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Hsu, Chia-Wei
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Shieh, Shiuhpyng
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Wang, Chi-Wei
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資訊工程學系
Characterisation of a suspended nanowire channel thin-film transistor with sub-100 nm air gap
(2011-07-01)
Kuo, Chia-Hao
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Hsu, Chia-Wei
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Lin, Horng-Chih
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Huang, Tiao-Yuan
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電子工程學系及電子研究所
A novel suspended nanowire (NW) channel thin-film transistor (TFT) with sub-100 nm air gap has been fabricated and characterised. With a simple and low-cost over-etching-time-controlled reactive ion etching technique and a buffered-oxide etch wet-etching process, a suspended NW of 27 nm and an air gap of 10 nm were achieved. The resultant suspended-NW-channel TFTs showed an ultra-low subthreshold swing (52 mV/dec) and considerable hysteresis window (3.7 V). Finally, the impacts of device dimensions on the characteristics of suspended NW TFTs were also investigated.
Divergence Detector: A Fine-grained Approach to Detecting VM-Awareness Malware
(2013)
Hsu, Chia-Wei
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Shih, Fan-Syun
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Wang, Chi-Wei
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Shieh, Shiuhpyng Winston
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資訊工程學系
Virtualized execution has become an effective mechanism to analyze malware in a dynamic way. To conceal its malicious behaviors, VM-aware malware probes the execution environment for analysis-resistance. These malware programs hide their malicious behaviors if they are launched in a virtual machine (VM). VM awareness becomes a barrier for malware analysis due to the concealment of malicious behaviors. In this paper, we discover that uncertain factors have significant influence on the effectiveness of malware detection. To cope with the problems, a new VM-aware detection scheme, namely Divergence Detector, is proposed to address the swindle of the evolved malware. Unlike conventional schemes, the Divergence Detector reduces the uncertain factors at instruction level, and can detect the divergence of multi-execution traces across heterogeneous virtual machines. The proposed Divergence Detector is implemented across the three commonly used VM platforms, that is, QEMU, Bochs and Xen. It compares the code coverage of the execution traces on various VM platforms to discover the deviation of behavior, thereby precisely detecting the VM-awareness. We will formally predict the effectiveness of Divergence Detector by constructing a mathematic model, which shows the maximum false positive rate is exponentially decreased with respect to the number of multi-executions. Representative samples utilizing seven types of commonly used VM-aware techniques were also employed for evaluation. The evaluation results indicate that the maximum false positive rate complies with our prediction. The uncertain factors play the major role in the VM-awareness detection. To reduce uncertain factors causing false positives, a method is proposed for VM-aware detection. The Divergence Detector can also enable the identification of new types of malware since the benign programs do not need to be aware of execution environment.
DROIT plus : Taint Tracking for Storage Access on Android
(2017-09-01)
Hsu, Chia-Wei
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Chang, Chia-Huei
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Wang, Chi-Wei
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Shieh, Shiuhpyng
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資訊工程學系
The leakage of sensitive data has been a major concern in Android ecosystem. Analysts therefore propose dynamical taint tracking to effectively track the data flow of accessed data. However, the off-the-shelf taint tracking systems lack byte-granularity support for storage tracking. In this paper, we propose DROIT+ which uses the fine-grained storage tracking technique to track data flow among Android storages. DROIT+ is able to reveal the composition of data flows. Storage tracking on Android is difficult since data flows of apps may span heterogeneous media including memory, SD cards, NAND Flash, and network adapters. To capture a whole picture of data flows in storage, we formally define data flow and propose our method from both logical and physical perspectives. The method has also been implemented as an extension to the proposed tracking system, DROIT. Two case studies and two benchmark tools are used for the evaluation in terms of storage tracking ability, network tracking ability, and efficiency, respectively. The result shows that DROIT+ provides a better coverage using byte-granularity taint tracking.
DT-Track: Using DNS-Timing Side Channel for Mobile User Tracking
(2019-01-01)
Lin, Chun-Han
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Lee, Shan-Hsin
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Huang, Hsiu-Chuan
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Wang, Chi-Wei
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Hsu, Chia-Wei
Targeted advertising is a form of online advertising that is directed towards audiences with certain traits. User tracking is useful to provide tailored web content or online advertisement. However, in the case without user online identities, targeted advertising becomes difficult. The challenge gets even higher in a mobile environment as the mobile user roams from one location to another location. In this paper, we propose a third-party web tracking scheme, named DT-Track, which can stealthily track users via the proposed side channel on DNS. The side channel is built on top of the cache existence of DNS records, which are commonly used.
Finder: Automatic ICC Data Reconstruction for Long-Term Runtime Semantics
(2018-01-01)
Hsu, Chia-Wei
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Wei, Sheng-Ru
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Shieh, Shiuhpyng
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資訊工程學系
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Department of Computer Science
In Android, both system services and apps are composed of components, and the inter-component communication (ICC) is therefore vital for representing the system states of the past runtime. Conventional approaches focus on inspecting the program behaviors of apps in the laboratory environment, but not suitable for a long-time period, system-wide activities. Analysts consider that ICC preserves much runtime semantics, so we propose Finder, an automatic ICC data reconstruction system to provide a long-term and comprehensive view of the past runtime. We decouple the program analysis on ICC from runtime monitoring thereby decreasing the runtime overhead. Finder applies transpiling techniques to generate the data resolvers compatible with all off-the-shelf Android version. The generated data resolvers can reconstruct a high-level, system-wide runtime information, and therefore the result is useful for digital forensic, program analysis, and auditing.
IoT Security: Ongoing Challenges and Research Opportunities
(2014-01-01)
Zhang, Zhi-Kai
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Cho, Michael Cheng Yi
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Wang, Chia-Wei
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Hsu, Chia-Wei
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Chen, Chong-Kuan
The Internet of Things (IoT) opens opportunities for wearable devices, home appliances, and software to share and communicate information on the Internet. Given that the shared data contains a large amount of private information, preserving information security on the shared data is an important issue that cannot be neglected. In this paper, we begin with general information security background of IoT and continue on with information security related challenges that IoT will encountered. Finally, we will also point out research directions that could be the future work for the solutions to the security challenges that IoT encounters.
Light-Weight CSRF Protection by Labeling User-Created Contents
(2013)
Sung, Yin-Chang
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Cho, Michael Cheng Yi
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Wang, Chi-Wei
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Hsu, Chia-Wei
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Shieh, Shiuhpyng Winston
Cross-site request forgery (CSRF/XSRF) is a serious vulnerability in Web 2.0 environment. With CSRF, an adversary can spoof the payload of an HTTP request and entice the victim's browser to transmit an HTTP request to the web server. Consequently, the server cannot determine legitimacy of the HTTP request. This paper presents a light-weight CSRF prevention method by introducing a quarantine system to inspect suspicious scripts on the server-side. Instead of using script filtering and rewriting approach, this scheme is based on a new labeling mechanism (we called it Content Box) which enables the web server to distinguish the malicious requests from the harmless requests without the need to modify the user created contents (UCCs). Consequently, a malicious request can be blocked when it attempts to access critical web services that was defined by the web administrator. To demonstrate the effectiveness of the proposed scheme, the proposed scheme was implemented and the performance was evaluated.
Proactive Distributed Digital Evidence Preservation with Tamper Resistance, Perfect Secrecy and High Survivability
(2014-11-01)
Lin, Jia-Chun
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Shieh, Shiuhpyng
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Hsu, Chia-Wei
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資訊工程學系
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Department of Computer Science
To reduce the chance of being compromised, digital evidence must be preserved in a secure way when it is generated. The preservation must assure confidentiality, integrity, and survivability of the digital evidence. Some generic storage systems have been proposed. However, they cannot meet the critical requirements for digital evidence preservation. This paper introduces a secure distributed digital evidence preservation system (DEPS) which can preserve digital evidence generated by mission critical servers. With the novel and lightweight (n, n, n-1) secret recovery scheme we proposed, DEPS can efficiently divide each block of a digital evidence file into n shares, compress the first n-1 shares, and then construct a share-message with a sequence number and a fingerprint for each share. Only all the n shares combined together suffice for recovering the block. An adversary can neither obtain any information about the original block from a share-message, nor can he modify digital evidence without being discovered. By using intelligent replication, DEPS can dynamically duplicate and distribute each share-message to a set of distributed repositories to achieve high survivability. The security and performance analyses showed that DEPS is adequate for preserving digital evidence.
Quintuply-Bonded Dichromium(I) Complexes Featuring Metal-Metal Bond Lengths of 1.74 angstrom
(2008)
Hsu, Chia-Wei
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Yu, Jen-Shiang K.
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Yen, Chun-Hsu
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Lee, Gene-Hsiang
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Wang, Yu
Rapid volumetric multiphoton imaging with the combination of an ultrasound lens and a resonant mirror
(2018-01-01)
Hsu, Chia-Wei
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Chiang, Tsung-Yen
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Lai, Feng-Jie
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Chen, Shean-Jen
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光電學院
The combination of a tunable acoustic gradient (TAG) lens and a resonant mirror were integrated into a multiphoton excited (MPE) microscope that is rapidly and precisely controlled by an embedded field programmable gate array (FPGA) to acquire images at high frame rate.
Remarkably short metal-metal bonds: A lantern-type quintuply bonded Dichromium(I) complex
(2008)
Tsai, Yi-Chou
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Hsu, Chia-Wei
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Yu, Jen-Shiang K.
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Lee, Gene-Hsiang
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Wang, Yu
Security Semantics Modeling with Progressive Distillation
(2017-11-01)
Shen, Zong-Xian
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Hsu, Chia-Wei
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Shieh, Shiuhpyng Winston
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資訊工程學系
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Department of Computer Science
The prevalence of Android platform has attracted adversaries to craft malicious payloads for illegal profit. Such malicious artifacts are frequently reused and embedded in benign, paid apps to lure victims that the apps have been cracked for free. To discover these fraudulent apps, administrators of app markets desire an automated scanning process to maintain the health of app ecosystem. However, conventional approaches cannot be efficiently applied due to the lack of a scalable, effective approach to malware characteristics aggregation. On the other hand, the vast number of apps significantly increases the analysis complexity. In this paper, we propose Petridish which generates discriminative models against the repacked malicious apps. These representative models of malicious semantics can be progressively distilled with malign and benign samples. These models can further detect repacked malicious apps. Our experiment shows that, after two retraining rounds, Petridish achieved an average of 28 percent progressive detection improvement from 63 to 91.2 percent for the large families, exceeding 38 test samples in size. With noise reduction, it accomplished 88 percent detection rate and 1.7 percent false alarm rate. The characteristics aggregation approach will become critical in the age of app explosion.
Stepwise Construction of the Cr-Cr Quintuple Bond and Its Destruction upon Axial Coordination
(2012)
Huang, Yu-Lun
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Lu, Duan-Yen
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Yu, Hsien-Cheng
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Yu, Jen-Shiang K.
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Hsu, Chia-Wei