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ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models [PDF]
Network and Distributed System Security Symposium, 2018 Machine learning (ML) has become a core component of many real-world applications and training data is a key factor that drives current progress. This huge success has led Internet companies to deploy machine learning as a service (MLaaS).
A. Salem +4 more
semanticscholar +1 more source
Future of Artificial Intelligence (AI) - Machine Learning (ML) Trends in Pathology and Medicine.
Modern PathologyArtificial Intelligence (AI) and Machine Learning (ML) are transforming the field of medicine. Healthcare organizations are now starting to establish management strategies for integrating such platforms (AI-ML toolsets) which leverage the computational ...
Matthew G. Hanna +6 more
semanticscholar +1 more source
Seagrass classification using unsupervised curriculum learning (UCL)
Ecological InformaticsSeagrass ecosystems are pivotal in marine environments, serving as crucial habitats for diverse marine species and contributing significantly to carbon sequestration.
Nosheen Abid +7 more
doaj +1 more source
Perturbing Inputs to Prevent Model Stealing
, 2020 We show how perturbing inputs to machine learning services (ML-service) deployed in the cloud can protect against model stealing attacks. In our formulation, there is an ML-service that receives inputs from users and returns the output of the model ...
Grana, Justin
core +1 more source
HeliyonGuar korma and churi protein isolates were assessed for their physicochemical, nutritional, functional, structural, and digestibility properties for their application in the food industry.
Bhavya Kotnala +2 more
doaj +1 more source
The Challenges in SDN/ML Based Network Security : A Survey
, 2018 Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge.
Nguyen, Tam N.
core +1 more source
Hydro-power generation forecast in South Africa based on Machine Learning (ML) models
Scientific African, 2023 With the advancement of technology and the ever-growing need for electronics, electricity has become an indispensable aspect of modern life. Developing or underdeveloped nations must overcome a number of obstacles to balance the supply and demand for ...
Selaki Ivy Ramarope +2 more
doaj +1 more source
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
, 2019 Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable ...
Chen, Kwang-Cheng +5 more
core +1 more source
Identification of semen traces at a crime scene through Raman spectroscopy and machine learning
Scientific ReportsBiological fluid stains can be instrumental in solving crimes. Identification of semen can help reconstruct events in sexual assault cases and identify suspects via DNA profiling.
Alexey V. Borisov +5 more
doaj +1 more source
Diffusion models for 3D generation: A survey
Computational Visual MediaDenoising diffusion models have demonstrated tremendous success in modeling data distributions and synthesizing high-quality samples. In the 2D image domain, they have become the state-of-the-art and are capable of generating photo-realistic images with ...
Chen Wang +4 more
doaj +1 more source