Zobrazeno 1 - 10
of 208
pro vyhledávání: '"Saxena, Nitesh"'
While advertising has become commonplace in today's online interactions, there is a notable dearth of research investigating the extent to which browser fingerprinting is harnessed for user tracking and targeted advertising. Prior studies only measur
Externí odkaz:
http://arxiv.org/abs/2409.15656
"Honeywords" have emerged as a promising defense mechanism for detecting data breaches and foiling offline dictionary attacks (ODA) by deceiving attackers with false passwords. In this paper, we propose PassFilter, a novel deep learning (DL) based at
Externí odkaz:
http://arxiv.org/abs/2407.16964
In this paper, we present a very first study to investigate trust and ethical implications of on-device artificial intelligence (AI), focusing on ''small'' language models (SLMs) amenable for personal devices like smartphones. While on-device SLMs pr
Externí odkaz:
http://arxiv.org/abs/2406.05364
In this research, we introduce MIND-Crypt, a novel attack framework that uses deep learning (DL) and transfer learning (TL) to challenge the indistinguishability of block ciphers, specifically SPECK32/64 encryption algorithm in CBC mode (Cipher Block
Externí odkaz:
http://arxiv.org/abs/2405.19683
Autor:
Saini, Shalini, Saxena, Nitesh
FemTech, a rising trend in mobile apps, empowers women to digitally manage their health and family planning. However, privacy and security vulnerabilities in period-tracking and fertility-monitoring apps present significant risks, such as unintended
Externí odkaz:
http://arxiv.org/abs/2404.05876
Autor:
Alatawi, Mashari, Saxena, Nitesh
The authentication ceremony plays a crucial role in verifying the identities of users before exchanging messages in end-to-end encryption (E2EE) applications, thus preventing impersonation and man-in-the-middle (MitM) attacks. Once authenticated, the
Externí odkaz:
http://arxiv.org/abs/2310.13894
Autor:
Alatawi, Mashari, Saxena, Nitesh
End-to-End Encryption (E2EE) aims to make all messages impossible to read by anyone except you and your intended recipient(s). Many well-known and widely used Instant-Messaging (IM) applications (such as Signal, WhatsApp, and Apple's iMessage) claim
Externí odkaz:
http://arxiv.org/abs/2307.03426
Publikováno v:
In Proceedings of the 16th ACM Conference on Security and Privacy in Wireless and Mobile Networks, 2023, ACM, New York, NY, USA, 12 pages
The growing adoption of voice-enabled devices (e.g., smart speakers), particularly in smart home environments, has introduced many security vulnerabilities that pose significant threats to users' privacy and safety. When multiple devices are connecte
Externí odkaz:
http://arxiv.org/abs/2302.02042
Autor:
Mahdad, Ahmed Tanvir, Shi, Cong, Ye, Zhengkun, Zhao, Tianming, Wang, Yan, Chen, Yingying, Saxena, Nitesh
Eavesdropping from the user's smartphone is a well-known threat to the user's safety and privacy. Existing studies show that loudspeaker reverberation can inject speech into motion sensor readings, leading to speech eavesdropping. While more devastat
Externí odkaz:
http://arxiv.org/abs/2212.12151