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Application Monitoring System Design and Implementation using System Call Pattern
http://doi.org/10.5626/JOK.2022.49.10.795
A user application consists of a set of functions. An application gives a set of functions to do what the user needs. Applications that provide services such as web servers are very large and complex, making them a target for attackers. As a result of attacks by malicious hackers, application variables and program flow are distorted, leading to the hijacking of system administrator privileges or abnormal operations. In this paper, we designed and implemented a system that collects an application"s system call and detects anomalies in applications through the collected patterns. As a result of measuring the overhead through the actually implemented system, it was found that when about 1 million system calls were monitored, it had an overhead of about 0.8 seconds. This is about 1/28 of the overhead time of existing tools such as strace.
Methods for Analyzing Preference Tendencies and Activity Patterns with Audio Contexts
Hyun Jung La, Moon Kwon Kim, Han Ter Jung, Soo Dong Kim
http://doi.org/10.5626/JOK.2018.45.4.348
Recently, there has been a trend for collecting various rich personal contexts, such as social network services (SNS), user created contents (UCC), and digital diaries. Because of this trend, much more attention to semantic analysis with personal contexts is being paid. The semantic analysis allows users to analyze and understand diverse aspects of their lives such as their lifestyle and quality of life which are not easily recognized by them. Hence, in this paper, we propose a process to infer semantics from personal contexts, more specifically, audio contexts. This paper is focused on proposing detailed algorithms for analyzing user’s preference tendencies and activity patterns. To evaluate the proposed methods, we apply them to developing a system, called Smart Diary System, which is used to analyze a user’s preference tendency and activity pattern from audio diaries, and we present experiment results with the system. We expect to use the proposed process and algorithms in various application domains such as personal secretary service, recommendation services, and advertising services.
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