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1. An Effective Ensemble Algorithm for Short-Term Load Forecasting NSTL国家科技图书文献中心

En-Wei Zhang |  Luo-Fan Wu... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 164~176 - 共13页

摘要:Short-term load forecasting (STLF) is a |  critical issue for managing electricity distribution |  systems because its accuracy might strongly impact the |  performance and security of the power system. An effective |  load forecasting system, of course, can also be used
关键词: Smart grid |  Deep learning |  Machine learning

2. PUF-Based Authentication and Authorization Protocol for IoT NSTL国家科技图书文献中心

Yu-Tse Shih |  Shih-Ming Huang... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 179~190 - 共12页

摘要:With the rapid development of technology | , smart devices have become indispensable tools for |  people, and IoT devices are ubiquitous, playing an |  important role in our daily lives. When using IoT device |  applications and services, users must go through complex
关键词: Physically unclonable functions |  Authentication |  Authorization |  Key exchange |  Internet of things

3. A Survey on Attack Cases with VBS Malware in Windows NSTL国家科技图书文献中心

GyuHyun Jeon |  Seungho Jeon... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 284~296 - 共13页

摘要:Visual Basic Script (VBS)-based malicious code |  exists in various forms such as document type | , executable file, and LNK file. After disguising it as a |  normal file or exploiting a vulnerability to trick the |  user into executing it, malicious actions are
关键词: Malware |  VBS |  Windows |  Case analysis |  MITRE ATT&CK

4. VoteGAN: Generalized Membership Inference Attack Against Generative Models by Multiple Discriminators NSTL国家科技图书文献中心

Gyeongsup Lim |  Wonjun Oh... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 71~82 - 共12页

摘要:Generative Adversarial Networks (GANs | ) produces samples with the same probability distribution |  as the given training data. However, as they |  frequently train with sensitive data to generate realistic |  samples, many people are concerned about the leakage of
关键词: AI security |  Machine learning |  Computer vision

5. Boosting Black-Box Transferability of Weak Audio Adversarial Attacks with Random Masking NSTL国家科技图书文献中心

Mai Bui |  Thien-Phuc Doan... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 96~108 - 共13页

摘要:The vulnerability of deep learning models to |  adversarial attacks poses a significant challenge in |  artificial intelligence, particularly in deepfake detection | . Adversarial training has emerged as a crucial defense |  mechanism, highlighting the importance of highly
关键词: Adversarial attacks |  Adversarial training |  Random masking |  Boosting transferability |  Low-frequency

6. ARP Spoofing Mitigation for the E2 Interface in Open RAN: An xApp Approach NSTL国家科技图书文献中心

Jihye Kim |  Jaehyoung Park... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 31~43 - 共13页

摘要:In the 5G-Advanced and 6G era, the Open Radio |  Access Network (Open RAN) will support hardware and |  software interoperability between different vendors. The |  O-RAN Alliance, which leads the Open RAN |  initiative, has released standards addressing potential
关键词: Open RAN |  E2 interface |  XApp |  MitM

7. Fuzzing JavaScript Engines with Diversified Mutation Strategies NSTL国家科技图书文献中心

Cheng-Han Shie |  Pin-Huang Fang... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 243~254 - 共12页

摘要:Current fuzzers for JavaScript (JS) engines |  often produce test cases that are syntactically |  correct but semantically incorrect, hindering efficient |  crash discovery. To address this issue, we propose |  three mutation methods: simple mutation, state
关键词: Fuzzing |  Javascript engine |  Abstract syntax tree (AST) |  Just-in-time (JIT) compilation

8. Field Testing and Detection of Camera Interference for Autonomous Driving NSTL国家科技图书文献中心

Ki Beom Park |  Huy Kang Kim -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 191~202 - 共12页

摘要:In recent advancements in connected and |  autonomous vehicles (CAVs), automotive ethernet has emerged |  as a critical technology for in-vehicle networks |  (IVNs), superseding traditional protocols like the CAN |  due to its superior bandwidth and data transmission
关键词: Automotive ethernet and camera interference |  Intrusion detection

9. Plotting OSS-Based Supply Chain Attack Strategies and the Defense Failure NSTL国家科技图书文献中心

Arpita Dinesh Sarang |  Sang-Hoon Choi... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 311~323 - 共13页

摘要:The supply chain attack, which targets open | -source software, is currently the most discussed |  cyberattack. This is due to the recent open-source XZ utils |  and PyPI projects based attacks where the attackers |  employed similar strategies. A backdoor was injected in
关键词: Supply chain attack |  Linux distribution |  Cyber security |  Supply chain attack as a service (SCAaaS) |  Open source software (OSS) security |  Software bill of materials (SBOM)

10. LLM Guardrail Framework: A Novel Approach for Implementing Zero Trust Architecture NSTL国家科技图书文献中心

Bogeum Kim |  Hyejin Sim... -  《Information Security Applications》 -  International Conference on Information Security Applications - 2025, - 138~148 - 共11页

摘要:This paper proposes an LLM guardrail framework |  that incorporates a Zero Trust architecture to |  validate and control the responses of Large Language |  Model (LLM) to unethical queries. The proposed |  framework applies guardrails to harmful inputs to avoid
关键词: Large language model |  Guardrail |  Zero trust
检索条件出处:Information Security Applications
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