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Security and privacy challenges of large language models: A survey
Large language models (LLMs) have demonstrated extraordinary capabilities and
contributed to multiple fields, such as generating and summarizing text, language …
contributed to multiple fields, such as generating and summarizing text, language …
Sensor and sensor fusion technology in autonomous vehicles: A review
With the significant advancement of sensor and communication technology and the reliable
application of obstacle detection techniques and algorithms, automated driving is becoming …
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
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 …
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
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 …
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
Cyber-physical systems (CPS) are interconnected architectures that employ analog and
digital components as well as communication and computational resources for their …
digital components as well as communication and computational resources for their …
[КНИГА][B] Deep learning on graphs
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 …
book consists of four parts to best accommodate our readers with diverse backgrounds and …
A survey of adversarial defenses and robustness in nlp
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 …
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
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 …
been gaining significant attention due to the rapidly growing applications of deep learning in …