http://repository.sungshin.ac.kr/handle/2025.oak/173 2026-03-25T12:25:52Z http://repository.sungshin.ac.kr/handle/2025.oak/8875 Title: MDC+: A Cooperative Approach to Memory-Efficient Fork-Based Checkpointing for In-Memory Database Systems Author(s): 박지웅; 민철기; 염헌영; 정형수 Abstract: Consistent checkpointing is a critical for in-memory databases (IMDBs) but its resource-intensive nature poses challenges for small- and medium-sized deployments in cloud environments, where memory utilization directly affects operational costs. Although traditional fork-based checkpointing offers merits in terms of performance and implementation simplicity, it incurs a considerable rise in memory footprint during checkpointing, particularly under update-intensive workloads. Memory provisioning emerges as a practical remedy to handle peak demands without compromising performance, albeit with potential concerns related to memory over-provisioning. In this article, we propose MDC+, a memory-efficient fork-based checkpointing scheme designed to maintain a reasonable memory footprint during checkpointing by leveraging collaboration among an IMDB, a user-level memory allocator, and the operating system. We explore two key techniques within the checkpointing scheme: (1) memory dump-based checkpointing, which enables early memory release, and (2) hint-based segregated memory allocation, which isolates immutable and updatable data to minimize page duplication. Our evaluation demonstrates that MDC+ significantly lowers peak memory footprint during checkpointing without affecting throughput or checkpointing time. 2025-06-29T15:00:00Z http://repository.sungshin.ac.kr/handle/2025.oak/8874 Title: Dual-Core Hierarchical Fuzzing Framework for Efficient and Secure Firmware Over-the-Air Author(s): 이일구; 김나현; 이진민 Abstract: As the use of Internet of Things (IoT) devices becomes extensive, ensuring their security has become a critical issue for both individuals and organizations, particularly as these devices collect, transmit, and analyze diverse data. The firmware of IoT devices plays a key role in ensuring system security; any vulnerabilities in the firmware can expose the system to threats such as hacking or malware infections. Consequently, fuzzing is used to analyze firmware vulnerabilities during the update process. However, conventional single-core and random fuzzing-based firmware vulnerability analysis techniques suffer from low efficiency, limited security, and high memory usage. Each time the firmware is updated, the entire file—including previously analyzed code—must be reanalyzed. Moreover, given that the firmware is not layered, unaffected code segments are redundantly reanalyzed. To address these limitations, this study proposes a dual-core-based hierarchical partial fuzzing technique for wireless networks using dual cores. Experimental results show that the proposed technique detects 11 more unique crashes within 300 s and finds 2435 more total crashes than that of the conventional scheme. It also reduces memory usage by 35 KiB. The proposed technique improves the speed, effectiveness, and reliability of firmware up 2025-07-17T15:00:00Z http://repository.sungshin.ac.kr/handle/2025.oak/8873 Title: Privacy-Preserving Data Sharing via PCA-Based Dimensionality Reduction in Non-IID Environments Author(s): 이일구; 이연지; 신나연 Abstract: The proliferation of mobile devices has generated exponential data growth, driving efforts to extract value. However, mobile data often presents non-independent and identically distributed (non-IID) challenges owing to varying device, environmental, and user factors. While data sharing can mitigate non-IID issues, direct raw data transmission poses significant security risks like privacy breaches and man-in-the-middle attacks. This paper proposes a secure data-sharing mechanism using principal component analysis (PCA). Each node independently builds a local PCA model to reduce data dimensionality before sharing. Receiving nodes then recover data using a similarly constructed local PCA model. Sharing only dimensionally reduced data instead of raw data enhances transmission privacy. The method’s effectiveness was evaluated from both legitimate user and attacker perspectives. Experimental results demonstrated stable accuracy for legitimate users post-sharing, while attacker accuracy significantly dropped. The optimal number of principal components was also experimentally determined. Under optimal configuration, the proposed method achieves up to 42 times greater memory efficiency and superior privacy metrics compared with conventional approaches, demonstrating its advantages. 2025-07-03T15:00:00Z http://repository.sungshin.ac.kr/handle/2025.oak/8865 Title: 최근 30년간 국내 프랜차이즈 분쟁사례의 변화에 관한 연구: 분쟁조정 의결서 대상 토픽모델링을 중심으로 Author(s): 김준영; 김향미; 김재욱; 정소희 Abstract: 본 연구는 국내 프랜차이즈 산업에서 발생한 분쟁의 구조적 양상과 진화 과정을 탐색적으로 분석하고자 한다. 기존 연구들이 주로 특정 시점의 사례나 법적 쟁점에 국한되었던 것과 달리, 본 연구는 1996년부터 2024년까지 약 30년에 걸친 공정거래위원회의 가맹사업 분쟁 조정 및 심의 자료 757건을 수집하여, 시계열적·총체적으로 분쟁의 양상 변화를 조망하였다. 특히, 단순 빈도 분석이나 사례 열거에 그치지 않고, LDA(Latent Dirichlet Allocation) 기반 토픽 모델링과 연관어 네트워크 분석이라는 정량적 탐색 기법을 접목함으로써, 가맹사업 분쟁의 주요 주제와 이슈 군집이 시기별로 어떻게 형성되고 변화해 왔는지를 실증적으로 규명하였다. 분석 결과, 산업 초기에는 정보공개서 미제공, 허위·과장 정보 등 계약 체결 단계에서의 정보 비대칭 문제가 핵심 갈등 요인으로 작용했으나, 산업이 성숙함에 따라 로열티, 필수 물품 강제, 영업 지역 침해 등 운영·수익 배분 단계의 구조적 갈등으로 쟁점이 확산되었음이 확인되었다. 최근에는 점주 단체의 결성, 집단 소송, 계약 해지 등을 둘러싼 갈등의 집단화 및 제도화 경향이 뚜렷해졌으며, 분쟁이 보다 복합적이고 구조적인 양상으로 진화하고 있음을 보여주었다. 이러한 결과는 프랜차이즈 갈등이 거래 효율성의 문제를 넘어, 통제와 자율성의 긴장, 권력과 자원의 불균형 등 보다 구조적 요인과 관련되어 있음을 시사한다. 본 연구는 국내 프랜차이즈 분쟁에 대한 정책적 개입의 방향성을 도출함과 동시에, 정성·정량 자료를 통합하는 탐색적 방법론의 유용성을 실증적으로 제시했다는 점에서 학술적 기여가 있다. 특히, 갈등의 구조적 원인을 파악하고 장기적 관점에서의 규제 및 조정 장치를 설계할 수 있는 근거를 제공하며, 가맹본부와 가맹점 간 균형 잡힌 파트너십 구축, 사전적 분쟁 예방 시스템 설계, 정보공개서의 실효성 제고 등의 정책적 시사점을 함께 제시한다. 2025-07-30T15:00:00Z