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Oral Session A-4 : Big Data

Threat Analysis for AI-Powered In-App Guide Tools in Decentralized Applications : Vulnerabilities and Mitigation Strategies

첫 페이지 보기
  • 발행기관
    한국차세대컴퓨팅학회 바로가기
  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 통권
    ICNGC 2025 The 11th International Conference on Next Generation Computing 2025 (2025.12)바로가기
  • 페이지
    pp.353-356
  • 저자
    Muhammad Farooq, Muhammad Waseem Iqbal, Muhammad Ibrar, Muhammad Haseeb Khalid, Roshaan Fatima, Reyaz Ahmad
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A478533

원문정보

초록

영어
Decentralized apps are now much more accessible thanks to AI-powered in-app support. Submenu after submenu is not required, nor is it necessary to guess what to click next. Come on, though, these helpful AI features bring with them some new problems. Code injection, data poisoning, and tricks that change what you see or click can all be successful. Prompt injection is a technique that attackers can use to give the AI malicious commands directly. In fact, this study explores the mechanisms behind these attacks. It looks at real-world situations, talks to security professionals, and sorts through the results of real security audits. Most problems show up directly in front of the user interface, whether it's malicious scripts or phony prompts.

목차

Abstract
I. INTRODUCTION (HEADING 1)
A. This Paper's Contributions
II. LITERATURE REVIEW
III. METHODOLOGY
A. Data collection:
B. Threat Identification Framework:
C. Expert Validation:
D. Interface Security Audits:
E. Mitigation Strategy Synthesis:
F. Audit-relevant dApps
IV. SUMMARY OF EXPERT EVALUATIONS
V. IDENTIFIED VULNERABILITIES
A. Audit Observations
B. Effectiveness of Mitigation Strategies
VI. DISCUSSION
A. Severity of threats at the interface level
B. Complexity of risks in decentralized systems
C. The trade-off between usability and security
D. The correlation between expert opinions and auditresults
E. A holistic approach to security
VII. CONCLUSION
REFERENCES

키워드

Decentralized Applications (dApps) AI-Powered In-App Guidance Threat Modeling and Security Prompt Injection and UI Spoofing Attacks

저자

  • Muhammad Farooq [ Department of Computer Science Superior University Lahore, 54000, Pakistan ]
  • Muhammad Waseem Iqbal [ Department of Computer Science Superior University Lahore, 54000, Pakistan ]
  • Muhammad Ibrar [ Department of Computer & Mathematical Sciences New Mexico Highlands University, Las Vegas, USA ]
  • Muhammad Haseeb Khalid [ GW Haden Solar PV IPP Project China Energy CEEC, KSA ]
  • Roshaan Fatima [ School of Computing, Horizon University College, Ajman, UAE ]
  • Reyaz Ahmad [ School of General Education, Horizon University College, Ajman, UAE ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국차세대컴퓨팅학회 [Korean Institute of Next Generation Computing]
  • 설립연도
    2005
  • 분야
    공학>컴퓨터학
  • 소개
    본 학회는 차세대 PC 및 그 관련분야의 학술활동을 통하여 차세대 PC의 학문 및 기술발전을 도모하고 산업발전 및 국제협력 증진을 목적으로 한다.

간행물

  • 간행물명
    한국차세대컴퓨팅학회 학술대회
  • 간기
    반년간
  • 수록기간
    2021~2025
  • 십진분류
    KDC 566 DDC 004

이 권호 내 다른 논문 / 한국차세대컴퓨팅학회 학술대회 ICNGC 2025 The 11th International Conference on Next Generation Computing 2025

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