2,999,049 research outputs found
SIDE proceedings : "Resilient SIDE" : Monday 22 - Wednesday 24 June 2009, Lincoln University, Canterbury
No full textA partnership involving DairyNZ, Lincoln University and South Island Dairy farmers
South Island Dairy Event proceedings Opportunity SIDE SIDE proceedings 22 - 24 June 2010
No full textA partnership involving Dairy NZ, Lincoln University and South Island Dairy farmers
On the Evaluation of Deep Learning-Based Side-Channel Analysis
No full textDeep learning-based side-channel analysis is rapidly positioning itself as a de-facto standard for the most powerful profiling side-channel analysis.The results from the last few years show that deep learning techniques can efficiently break targets that are even protected with countermeasures. While there are constant improvements in making the deep learning-based attacks more powerful, little is done on evaluating the attacks’ performance. Indeed, how the evaluation process is done today is not different from what was done more than a decade ago from the perspective of evaluation metrics. This paper considers how to evaluate deep learning-based side-channel analysis and whether the commonly used approaches give the best results. To that end, we consider different summary statistics and the influence of algorithmic randomness on the stability of profiling models. Our results show that besides commonly used metrics like guessing entropy, one should also show the standard deviation results to assess the attack performance properly. Even more importantly, using the arithmetic mean for guessing entropy does not yield the best results, and instead, a median value should be used.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
The 1947 South Side Catholic High School Class
No full textThe 1947 South Side Catholic High School Class. The class is portrayed on the poster/photograph as portrait photographs. A name is under each photograph. The class officers and the school officials are listed in the center. Joseph Lyles graduated from South Side in this year. During his time there he was a star on the Basketball and Baseball teams. In 1996, he was inducted into their sports Hall of Fame.For more information on Joseph F. Lyles see https://springfield.as.atlas-sys.com/agents/people/12
South Island Dairy Event proceedings Smart SIDE
No full textA partnership involving Dexcel, Lincoln University, and South Island Dairy farmers
Focus is Key to Success: A Focal Loss Function for Deep Learning-Based Side-Channel Analysis
No full textThe deep learning-based side-channel analysis represents one of the most powerful side-channel attack approaches. Thanks to its capability in dealing with raw features and countermeasures, it becomes the de facto standard approach for the SCA community. The recent works significantly improved the deep learning-based attacks from various perspectives, like hyperparameter tuning, design guidelines, or custom neural network architecture elements. Still, insufficient attention has been given to the core of the learning process - the loss function. This paper analyzes the limitations of the existing loss functions and then proposes a novel side-channel analysis-optimized loss function: Focal Loss Ratio (FLR), to cope with the identified drawbacks observed in other loss functions. To validate our design, we 1) conduct a thorough experimental study considering various scenarios (datasets, leakage models, neural network architectures) and 2) compare with other loss functions used in the deep learning-based side-channel analysis (both “traditional” ones and those designed for side-channel analysis). Our results show that FLR loss outperforms other loss functions in various conditions while not having computational overhead like some recent loss function proposals.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
Elsie Side Interview
No full textInterview with Elsie Side, as part of the Hearing Hazelton History project, managed by the Hazelton Area Historical Association.Attribution incomplet
Drug trafficking, money laundering and the business cycle: Does secular stagnation include crime?
No full textThe aim of the paper is to analyze theoretically and empirically the impact the macroeconomic cycle has on the accumulation of capital by organized crime, using estimates for the global drug market. So far, the economic literature has neglected the relationships existing between illegal markets, money laundering and the business cycle. We propose a dynamic model where the business cycle influences the criminal economy via two different channels. On the one side, illegal markets grow at variable rates, depending on the health of the legal economy. Second, a pass-through effect can exist, since the business cycle affects the legal markets which criminal operators use to launder their revenues. Furthermore, we analyze the consequences of a ‘saturation effect’ limiting maximum accumulation of illegal capital. We find that overall illegal capital is affected by the business cycle through a capital multiplier; in addition to this, the dynamics of interest rates in financial markets can influence such multiplier
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