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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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Amazon GuardDuty has launched advanced AI/ML threat detection capabilities, enhancing its ability to protect cloud environments from sophisticated security threats.
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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Published in · 5 min read · 2 days ago Hello guys, in this blog i will share the basics about Time Based Blind SQL Injection and how you can use if and sleep method to find various details about sql version, database length, database name and other details. I also have shared 2 php…
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George Teseleanu ePrint Report In this paper, we present a generalization of Schnorr’s digital signature that allows a user to simultaneously sign multiple messages. Compared to Schnorr’s scheme that concatenates messages and then signs them, the new protocol takes advantage of multiple threads to process messages in parallel. We prove the security of our novel…
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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Mahdi Mahdavi, Navid Abapour, Zahra Ahmadian ePrint Report With the increasing integration of crowd computing, new vulnerabilities emerge in widely used cryptographic systems like the RSA cryptosystem, whose security is based on the factoring problem. It is strongly advised to avoid using the same modulus to produce two pairs of public-private keys, as the cryptosystem…
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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BianLian ransomware actors are likely based in Russia and have multiple Russia-based affiliates, according to new information shared by the FBI and Australian law enforcement.
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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LummaC2 is an Infostealer actively being distributed while being disguised as illegal software such as cracks, and its distribution and creation methods are changing continuously. It has recently been distributed by being inserted into legitimate programs, so caution is needed.
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Boneh et al. (CRYPTO’18) proposed two $t$-out-of-$N$ threshold fully homomorphic encryption ($\sf TFHE$) schemes based on Shamir secret sharing scheme and $\{0,1\}$-linear secret sharing scheme. They demonstrated the simulation security, ensuring no information leakage during partial or final decryption. This breakthrough allows any scheme to be converted into a threshold scheme by using $\sf TFHE$.
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[Submitted on 22 Jan 2024 (v1), last revised 7 Nov 2024 (this version, v2)] View a PDF of the paper titled A Security Risk Assessment Method for Distributed Ledger Technology (DLT) based Applications: Three Industry Case Studies, by Elena Baninemeh and 3 other authors
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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FLock: Robust and Privacy-Preserving Federated Learning based on Practical Blockchain State Channels
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Ruonan Chen, Ye Dong, Yizhong Liu, Tingyu Fan, Dawei Li, Zhenyu Guan, Jianwei Liu, Jianying Zhou ePrint Report \textit{Federated Learning} (FL) is a distributed machine learning paradigm that allows multiple clients to train models collaboratively without sharing local data. Numerous works have explored security and privacy protection in FL, as well as its integration with…
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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Deep Learning Based XIoT Malware Analysis: A Comprehensive Survey, Taxonomy, and Research Challenges
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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
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In this paper, we introduce OT-PCA, a novel approach for conducting Plaintext-Checking (PC) oracle based side-channel attacks, specifically designed for Hamming Quasi-Cyclic (HQC). By calling the publicly accessible HQC decoder, we build offline templates that enable efficient extraction of soft information for hundreds of secret positions with just a single PC oracle call. Our method…