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( Hsing-han Liu ),( Pin-chang Su ),( Meng-hua Hsu ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.11
This research was based on the study conducted by Khodaei et al. (2012), namely, the least-significant-bit (LSB) substitution combined with the pixel-value differencing (PVD) steganography, and presented an improved irreversible image steganography method. Such a method was developed through integrating the improved LSB substitution with the modulus function-based PVD steganography to increase steganographic capacity of the original technique while maintaining the quality of images. It partitions the cover image into non-overlapped blocks, each of which consists of 3 consecutive pixels. The 2nd pixel represents the base, in which secret data are embedded by using the 3-bit LSB substitution. Each of the other 2 pixels is paired with the base respectively for embedding secret data by using an improved modulus PVD method. The experiment results showed that the method can greatly increase steganographic capacity in comparison with other PVD-based techniques (by a maximum amount of 135%), on the premise that the quality of images is maintained. Last but not least, 2 security analyses, the pixel difference histogram (PDH) and the content-selective residual (CSR) steganalysis were performed. The results indicated that the method is capable of preventing the detection of the 2 common techniques.
Genetic Algorithm for Shortest Driving Time in Intelligent Transportation Systems
Chu-Hsing Lin,Jung-Chun Liu,Chia-Han Ho,Jui-Ling Yu,Wei-Shen Lai 보안공학연구지원센터 2009 International Journal of Hybrid Information Techno Vol.2 No.1
The route guidance system, which provides driving advice based on traffic information about an origin and a destination, has become very popular along with the advancement of handheld devices and the global position system. Since the accuracy and efficiency of route guidance depend on the accuracy of the traffic conditions, the route guidance system needs to include more variables in calculation, such as real time traffic flows and allowable vehicle speeds. As variables considered by the route guidance system increase, the cost to compute multiplies. Since handheld devices have limited resources, it is not feasible to use them to compute the exact optimal solutions in real time systems by some well-known algorithm, such as the Dijkstra’s algorithm, which is usually used to find the shortest path with a map of reasonable numbers of vertices. To solve this problem, we propose to use the genetic algorithm to alleviate the rising computational cost. We use the genetic algorithm to find the shortest time in driving with diverse scenarios of real traffic conditions and varying vehicle speeds. The effectiveness of the genetic algorithm is clearly demonstrated when applied on a real map of modern city with very large vertex numbers.
Anomaly Detection Using LibSVM Training Tools
Jung-Chun Liu,Chu-Hsing Lin,Jui-Ling Yu,Wei-Shen Lai,Chia-Han Ho 보안공학연구지원센터 2008 International Journal of Security and Its Applicat Vol.2 No.4
Intrusion detection is the means to identify the intrusive behaviors and provide useful information to intruded systems to respond fast and to avoid or reduce damages. In recent years, learning machine technology is often used as a detection method in anomaly detection. In this research, we use support vector machine as a learning method for anomaly detection, and use LibSVM as the support vector machine tool. By using this tool, we get rid of numerous and complex operations and do not have to use external tools for finding parameters as needed by using other algorithms such as the genetic algorithm. Experimental results show that high average detection rates and low average false positive rates in anomaly detection are achieved by our proposed approach.