Security and privacy challenges of large language models: A survey

BC Das, MH Amini, Y Wu - ACM Computing Surveys, 2025 - dl.acm.org
Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …

Sensor and sensor fusion technology in autonomous vehicles: A review

DJ Yeong, G Velasco-Hernandez, J Barry, J Walsh - Sensors, 2021 - mdpi.com
With the significant advancement of sensor and communication technology and the reliable
application of obstacle detection techniques and algorithms, automated driving is becoming …

A survey of machine unlearning

TT Nguyen, TT Huynh, Z Ren, PL Nguyen… - ar** future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges
K Ahmad, M Maabreh, M Ghaly, K Khan, J Qadir… - Computer Science …, 2022 - Elsevier
As the globally increasing population drives rapid urbanization in various parts of the world,
there is a great need to deliberate on the future of the cities worth living. In particular, as …

[HTML][HTML] Network traffic classification: Techniques, datasets, and challenges

A Azab, M Khasawneh, S Alrabaee, KKR Choo… - Digital Communications …, 2024 - Elsevier
In network traffic classification, it is important to understand the correlation between network
traffic and its causal application, protocol, or service group, for example, in facilitating lawful …

Cyber-physical energy systems security: Threat modeling, risk assessment, resources, metrics, and case studies

I Zografopoulos, J Ospina, X Liu, C Konstantinou - IEEE Access, 2021 - ieeexplore.ieee.org
Cyber-physical systems (CPS) are interconnected architectures that employ analog and
digital components as well as communication and computational resources for their …

[КНИГА][B] Deep learning on graphs

Y Ma, J Tang - 2021 - books.google.com
Deep learning on graphs has become one of the hottest topics in machine learning. The
book consists of four parts to best accommodate our readers with diverse backgrounds and …

A survey of adversarial defenses and robustness in nlp

S Goyal, S Doddapaneni, MM Khapra… - ACM Computing …, 2023 - dl.acm.org
In the past few years, it has become increasingly evident that deep neural networks are not
resilient enough to withstand adversarial perturbations in input data, leaving them …

Adversarial attacks and defenses in machine learning-empowered communication systems and networks: A contemporary survey

Y Wang, T Sun, S Li, X Yuan, W Ni… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Adversarial attacks and defenses in machine learning and deep neural network (DNN) have
been gaining significant attention due to the rapidly growing applications of deep learning in …