Defending against machine learning based inference attacks via adversarial examples: Opportunities and challenges
… the opportunities and challenges of defending against ML-equipped inference … inference
attacks in online social networks as an example to illustrate the opportunities and challenges. …
attacks in online social networks as an example to illustrate the opportunities and challenges. …
Security for Machine Learning-based Software Systems: A Survey of Threats, Practices, and Challenges
… the works for the membership inference attacks against federated machine learning-based …
the state-of-the-practice of system security for the machine learning-based software …
the state-of-the-practice of system security for the machine learning-based software …
Machine learning security attacks and defense approaches for emerging cyber physical applications: A comprehensive survey
… various issues and challenges of ML security mechanisms … They demonstrated the procedure
of machine learning based network … inference attack is discussed at the end of this section. …
of machine learning based network … inference attack is discussed at the end of this section. …
A survey on privacy inference attacks and defenses in cloud-based deep neural network
… We discuss the challenges of privacy attacks on cloud-based … Attack) security, it is not
necessary to discuss privacy issues … Whereas, directly performing a fully-learning-based attack …
necessary to discuss privacy issues … Whereas, directly performing a fully-learning-based attack …
Over-the-air membership inference attacks as privacy threats for deep learning-based wireless signal classifiers
… applications, ML also raises unique challenges in terms of security [2ś4]. In particular, … the
training data in and relects it in the model’s output behavior. Thus, we can infer the training …
training data in and relects it in the model’s output behavior. Thus, we can infer the training …
Machine learning security: Threats, countermeasures, and evaluations
… the security issues of machine learning, focusing on existing … and membership inference
attack can steal the model param… to compromise these deep learning based security applications…
attack can steal the model param… to compromise these deep learning based security applications…
Unraveling Attacks to Machine Learning-Based IoT Systems: A Survey and the Open Libraries Behind Them
… security threats arising from ML’s integration into various facets of IoT, spanning various attack
types including membership inference, … of the attack on five property inference tasks, four …
types including membership inference, … of the attack on five property inference tasks, four …
Toward secure and efficient deep learning inference in dependable IoT systems
… putations in the model training or inference processes, making … a distributed IoT system
conducting computer vision tasks (eg, … for AIoT systems against more advanced attacks like …
conducting computer vision tasks (eg, … for AIoT systems against more advanced attacks like …
Machine learning based solutions for security of Internet of Things (IoT): A survey
… of security of IoT in terms of different types of possible attacks. Moreover, ML-based
potential solutions for IoT security has been presented and future challenges are discussed. …
potential solutions for IoT security has been presented and future challenges are discussed. …
Privacy inference attacks and defenses in cloud-based deep neural network: A survey
… We discuss the challenges of privacy attacks on cloudbased … Attack) security, it is not necessary
to discuss privacy issues in … that any learningbased strategy prevented the attack model …
to discuss privacy issues in … that any learningbased strategy prevented the attack model …