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Analysis of Vulnerabilities in Autonomous Driving Environments through Physical Adversarial Attacks Incorporating Natural Elements
Kyuchan Cho, Woosang Im, Sooyong Jeong, Hyunil Kim, Changho Seo
http://doi.org/10.5626/JOK.2024.51.10.935
Advancements in artificial intelligence technology have significantly impacted the field of computer vision. Concurrently, numerous vulnerabilities related to adversarial attacks, which are techniques designed to force models into misclassification, have been discovered. In particular, adversarial attacks such as physical adversarial attacks in the real world, pose a serious threat to autonomous vehicle systems. These attacks include artificially created attacks such as adversarial patches and attacks that exploit natural elements to cause misclassification. A common scenario in autonomous driving environments involves obstruction of traffic signs by natural elements such as fallen leaves or snow. These elements do not remain stationary. They can cause misclassification even in fleeting moments, highlighting a critical vulnerability. Therefore, this study investigated adversarial patch attacks based on natural elements, proposing fallen leaves as a natural adversarial element. Specifically, it reviewed current trends in adversarial attack research, presented an experimental environment based on natural elements, and analyzed experimental results to assess vulnerabilities posed by fallen leaves in physical environments to autonomous vehicles.
Encrypted Data Deduplication Using Key Issuing Server
Hyun-il Kim, Cheolhee Park, Dowon Hong, Changho Seo
Data deduplication is an important technique for cloud storage savings. These techniques are especially important for encrypted data because data deduplication over plaintext is basically vulnerable for data confidentiality. We examined encrypted data deduplication with the aid of a key issuing server and compared Convergent Encryption with a technique created by M.Bellare et al. In addition, we implemented this technique over not only Dropbox but also an open cloud storage service, Openstack Swift. We measured the performance for this technique over Dropbox and Openstack Swift. According to our results, we verified that the encrypted data deduplication technique with the aid of a key issuing server is a feasible and versatile method.
An Implementation of an SHA-3 Hash Function Validation Program and Hash Algorithm on 16bit-UICC
Hee-Woong Lee, Dowon Hong, Hyun-il Kim, ChangHo Seo, Kishik Park
A hash function is an essential cryptographic algorithm primitive that is used to provide integrity to many applications such as message authentication codes and digital signatures. In this paper, we introduce a concept and test method for a Cryptographic Algorithm Validation Program (CAVP). Also, we design an SHA-3 CAVP program and implement an SHA-3 algorithm in 16bit-UICC. Finally, we compare the efficiency of SHA-3 with SHA-2 and evaluate the exellence of the SHA-3 algorithm.
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