Zobrazeno 1 - 10
of 415
pro vyhledávání: '"Kanhere, Salil S."'
Location trajectories provide valuable insights for applications from urban planning to pandemic control. However, mobility data can also reveal sensitive information about individuals, such as political opinions, religious beliefs, or sexual orienta
Externí odkaz:
http://arxiv.org/abs/2407.16938
The challenges of healthcare supply chain management systems during the COVID-19 pandemic highlighted the need for an innovative and robust medical supply chain. The healthcare supply chain involves various stakeholders who must share information sec
Externí odkaz:
http://arxiv.org/abs/2407.11207
Honeyfiles are a particularly useful type of honeypot: fake files deployed to detect and infer information from malicious behaviour. This paper considers the challenge of naming honeyfiles so they are camouflaged when placed amongst real files in a f
Externí odkaz:
http://arxiv.org/abs/2405.04758
Digital identity is evolving from centralized systems to a decentralized approach known as Self-Sovereign Identity (SSI). SSI empowers individuals to control their digital identities, eliminating reliance on third-party data custodians and reducing t
Externí odkaz:
http://arxiv.org/abs/2404.06729
Honeyfiles are security assets designed to attract and detect intruders on compromised systems. Honeyfiles are a type of honeypot that mimic real, sensitive documents, creating the illusion of the presence of valuable data. Interaction with a honeyfi
Externí odkaz:
http://arxiv.org/abs/2404.04854
Autor:
Doan, Bao Gia, Nguyen, Dang Quang, Montague, Paul, Abraham, Tamas, De Vel, Olivier, Camtepe, Seyit, Kanhere, Salil S., Abbasnejad, Ehsan, Ranasinghe, Damith C.
The vulnerability of machine learning-based malware detectors to adversarial attacks has prompted the need for robust solutions. Adversarial training is an effective method but is computationally expensive to scale up to large datasets and comes at t
Externí odkaz:
http://arxiv.org/abs/2403.18309
While location trajectories represent a valuable data source for analyses and location-based services, they can reveal sensitive information, such as political and religious preferences. Differentially private publication mechanisms have been propose
Externí odkaz:
http://arxiv.org/abs/2403.07218
Autor:
Akhtar, Mohammad Majid, Bhuiyan, Navid Shadman, Masood, Rahat, Ikram, Muhammad, Kanhere, Salil S.
The detection of automated accounts, also known as "social bots", has been an increasingly important concern for online social networks (OSNs). While several methods have been proposed for detecting social bots, significant research gaps remain. Firs
Externí odkaz:
http://arxiv.org/abs/2402.03740
Autor:
Gill, Sukhpal Singh, Wu, Huaming, Patros, Panos, Ottaviani, Carlo, Arora, Priyansh, Pujol, Victor Casamayor, Haunschild, David, Parlikad, Ajith Kumar, Cetinkaya, Oktay, Lutfiyya, Hanan, Stankovski, Vlado, Li, Ruidong, Ding, Yuemin, Qadir, Junaid, Abraham, Ajith, Ghosh, Soumya K., Song, Houbing Herbert, Sakellariou, Rizos, Rana, Omer, Rodrigues, Joel J. P. C., Kanhere, Salil S., Dustdar, Schahram, Uhlig, Steve, Ramamohanarao, Kotagiri, Buyya, Rajkumar
Publikováno v:
Elsevier Telematics and Informatics Reports, Volume 13, March 2024
Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technologic
Externí odkaz:
http://arxiv.org/abs/2401.02469
In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios. Current deep learning techniques to address multiple-output problems
Externí odkaz:
http://arxiv.org/abs/2312.11735