Search Results
Kafka-ML: Connecting the data stream with ML/AI frameworks
Machine Learning (ML) and Artificial Intelligence (AI) depend on data sources to train, improve, and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, this information is turning from static data to continuous data streams. However, most of the ML/AI frameworks used nowadays are not fully prepared for this revolution. In this paper, we propose Kafka-ML, a novel and open-source framework that enables the management of ML/AI pipelines through data streams. Kafka-ML provides an accessible and user-friendly Web user interface where users can easily define ML models, to then train, evaluate, and deploy them for inferences. Kafka-ML itself and the components it deploys are fully managed through containerization technologies, which ensure their portability, easy distribution, and other features such as fault-tolerance and high availability. Finally, a novel approach has been introduced to manage and reuse data streams, which may eliminate the need for data storage or file systems.
Methods increasing inherent resistance of ECC designs against horizontal attacks
Due to the nature of applications such as critical infrastructure and the Internet of Things etc. side channel analysis attacks are becoming a serious threat. Side channel analysis attacks take advantage from the fact that the behaviour of crypto implementations can be observed and provides hints that simplify revealing keys. A new type of SCA is the so called horizontal differential SCA. In this paper we investigate two different approaches to increase the inherent resistance of our hardware accelerator for the kP operation. The first approach aims at reducing the impact of the addressing in our design by realizing a regular schedule of the addressing. In the second approach, we investigated how the formula used to implement the multiplication of GF(2n)-elements influences the results of horizontal DPA attacks against a Montgomery kP-implementation. We implemented 5 designs with different partial multipliers, i.e. based on different multiplication formulae. We used two different technologies, i.e. a 130 and a 250 nm technology, to simulate power traces for our analysis. We show that the implemented multiplication formula influences the success of horizontal attacks significantly. The combination of these two approaches leads to the most resistant design. For the 250 nm technology only 2 key candidates could be revealed with a correctness of about 70% which is a huge improvement given the fact that for the original design 7 key candidates achieved a correctness of more than 90%. For our 130 nm technology no key candidate was revealed with a correctness of more than 60%.