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Fortinet's Security Fabric-based platform is ideal for supporting MSSPs in all the segments of MSS, from the largest and most traditional security asset management and monitoring (SAMM) segment to the growth segments of threat intelligence, incident remediation (TIIR) and risk and compliance management (RCM). More importantly, Fortinet is well prepared to support the following three key trends: "Fortinet's Security Fabric, introduced in 2016, promotes a newer way of addressing security threats and is suitable for enterprises across the size spectrum," said Frost & Sullivan Research Analyst, Yiru Zhong. "Fortinet believes that small- and medium-sized enterprises can implement this solution more quickly to achieve 100% network coverage, while larger customers can scale up based on business priorities or their network and security stacks." The Fortinet Security Fabric overcomes the current challenges in the market by: Significantly, Fortinet makes sure that its MSSPs are profitable to its partners by presenting expert consultative and service creation support, including monthly billing and return-on-investment models. Fortinet has also set up a Veterans employment and their Network Security Academy program to help MSSPs recruit and train cybersecurity talent and the company offers free training to MSSPs to support newer organizations entering the service provider market. Fortinet encourages continuous learning with scholarships and indirect incentives for certification and education. Fortinet remained a market leader for the third consecutive year with the deployment of FortiGate enterprise firewall appliances. Overall, Fortinet supported more than 2.8 million devices globally in 2016, compared to a little more than 1 million in 2012. Its enterprise market share is vital to determine the margins of MSSPs because the more platforms MSSPs support, the more multi-skilled the MSSPs' engineers have to be or MSSPs must retain highly specialized security engineers in-house. In a sector already beset by skills shortage, the cost of talent is one of the largest components that must be managed. "Fortinet's revenue in 2016 touched $1.28 billion, almost a 200% leap from $433.6 million in 2011. From 2011 to 2016, its compound annual growth rate reached 24.2%, which exceeded the combined MSS market average of 16.9% for North America, Europe, and the Middle East and Africa (EMEA)," noted Zhong. "Fortinet's mix of devices in the field and its reach among MSSPs globally has provided it with the foundation for sustainable revenue streams in coming years." Each year, Frost & Sullivan presents this award to the company that has demonstrated excellence in terms of growth strategy and implementation. The award recognizes a high degree of innovation with products and technologies and the resulting leadership in terms of customer value and market penetration. Frost & Sullivan Best Practices awards recognize companies in a variety of regional and global markets for demonstrating outstanding achievement and superior performance in areas such as leadership, technological innovation, customer service, and strategic product development. Industry analysts compare market participants and measure performance through in-depth interviews, analysis, and extensive secondary research to identify best practices in the industry. "The challenges of today's increasingly hostile and complex threat landscape are driving many organizations to seek out security service providers that have the expertise and advanced security capabilities to secure their unique enterprise environments," said Stephan Tallent, senior director, managed security service providers at Fortinet. "Being honored as Frost & Sullivan's top MSSP platform provider reinforces our ongoing investments and continued dedication to the success of our MSSP partners and the security of their customers." Fortinet (NASDAQ: FTNT) secures the largest enterprise, service provider, and government organizations around the world. Fortinet empowers its customers with intelligent, seamless protection across the expanding attack surface and the power to take on ever-increasing performance requirements of the borderless network - today and into the future. Only the Fortinet Security Fabric architecture can deliver security without compromise to address the most critical security challenges, whether in networked, application, cloud, or mobile environments. Fortinet ranks #1 in the most security appliances shipped worldwide and more than 300,000 customers trust Fortinet to protect their businesses. Learn more at https://www.fortinet.com, the Fortinet Blog, or FortiGuard Labs. Frost & Sullivan, the Growth Partnership Company, works in collaboration with clients to leverage visionary innovation that addresses the global challenges and related growth opportunities that will make or break today's market participants. For more than 50 years, we have been developing growth strategies for the global 1000, emerging businesses, the public sector and the investment community. Contact us: Start the discussion.


Fortinet ensures that its MSSPs obtain optimum value from its platforms by offering expert consultative and service creation support SANTA CLARA, Calif., May 8, 2017 /PRNewswire/ -- Based on its recent analysis of the managed security services platform (MSSP) market, Frost & Sullivan recognizes Fortinet with the 2017 Global Frost & Sullivan Company of the Year Award. Fortinet made a strong bid to be a top player in the MSSP market, posting impressive financial results, rolling out technology innovations that supported end-customers' IT and security needs, and ensuring high customer retention. Its accelerated growth in the market coincided with MSSPs' new drive to establish a foothold in the emerging MSS segments of risk compliance and threat intelligence. Fortinet's Security Fabric-based platform is ideal for supporting MSSPs in all the segments of MSS, from the largest and most traditional security asset management and monitoring (SAMM) segment to the growth segments of threat intelligence, incident remediation (TIIR) and risk and compliance management (RCM). More importantly, Fortinet is well prepared to support the following three key trends: "Fortinet's Security Fabric, introduced in 2016, promotes a newer way of addressing security threats and is suitable for enterprises across the size spectrum," said Frost & Sullivan Research Analyst, Yiru Zhong. "Fortinet believes that small- and medium-sized enterprises can implement this solution more quickly to achieve 100% network coverage, while larger customers can scale up based on business priorities or their network and security stacks." The Fortinet Security Fabric overcomes the current challenges in the market by: Significantly, Fortinet makes sure that its MSSPs are profitable to its partners by presenting expert consultative and service creation support, including monthly billing and return-on-investment models. Fortinet has also set up a Veterans employment and their Network Security Academy program to help MSSPs recruit and train cybersecurity talent and the company offers free training to MSSPs to support newer organizations entering the service provider market. Fortinet encourages continuous learning with scholarships and indirect incentives for certification and education. Fortinet remained a market leader for the third consecutive year with the deployment of FortiGate enterprise firewall appliances. Overall, Fortinet supported more than 2.8 million devices globally in 2016, compared to a little more than 1 million in 2012. Its enterprise market share is vital to determine the margins of MSSPs because the more platforms MSSPs support, the more multi-skilled the MSSPs' engineers have to be or MSSPs must retain highly specialized security engineers in-house. In a sector already beset by skills shortage, the cost of talent is one of the largest components that must be managed. "Fortinet's revenue in 2016 touched $1.28 billion, almost a 200% leap from $433.6 million in 2011. From 2011 to 2016, its compound annual growth rate reached 24.2%, which exceeded the combined MSS market average of 16.9% for North America, Europe, and the Middle East and Africa (EMEA)," noted Zhong. "Fortinet's mix of devices in the field and its reach among MSSPs globally has provided it with the foundation for sustainable revenue streams in coming years." Each year, Frost & Sullivan presents this award to the company that has demonstrated excellence in terms of growth strategy and implementation. The award recognizes a high degree of innovation with products and technologies and the resulting leadership in terms of customer value and market penetration. Frost & Sullivan Best Practices awards recognize companies in a variety of regional and global markets for demonstrating outstanding achievement and superior performance in areas such as leadership, technological innovation, customer service, and strategic product development. Industry analysts compare market participants and measure performance through in-depth interviews, analysis, and extensive secondary research to identify best practices in the industry. "The challenges of today's increasingly hostile and complex threat landscape are driving many organizations to seek out security service providers that have the expertise and advanced security capabilities to secure their unique enterprise environments," said Stephan Tallent, senior director, managed security service providers at Fortinet. "Being honored as Frost & Sullivan's top MSSP platform provider reinforces our ongoing investments and continued dedication to the success of our MSSP partners and the security of their customers." Fortinet (NASDAQ: FTNT) secures the largest enterprise, service provider, and government organizations around the world. Fortinet empowers its customers with intelligent, seamless protection across the expanding attack surface and the power to take on ever-increasing performance requirements of the borderless network - today and into the future. Only the Fortinet Security Fabric architecture can deliver security without compromise to address the most critical security challenges, whether in networked, application, cloud, or mobile environments. Fortinet ranks #1 in the most security appliances shipped worldwide and more than 300,000 customers trust Fortinet to protect their businesses. Learn more at https://www.fortinet.com, the Fortinet Blog, or FortiGuard Labs. Frost & Sullivan, the Growth Partnership Company, works in collaboration with clients to leverage visionary innovation that addresses the global challenges and related growth opportunities that will make or break today's market participants. For more than 50 years, we have been developing growth strategies for the global 1000, emerging businesses, the public sector and the investment community. Contact us: Start the discussion.


Olteanu M.,SAMM | Villa-Vialaneix N.,SAMM | Villa-Vialaneix N.,French National Institute for Agricultural Research
Neurocomputing | Year: 2015

In some applications and in order to address real-world situations better, data may be more complex than simple numerical vectors. In some examples, data can be known only through their pairwise dissimilarities or through multiple dissimilarities, each of them describing a particular feature of the data set. Several variants of the Self-Organizing Map (SOM) algorithm were introduced to generalize the original algorithm to the framework of dissimilarity data. Whereas median SOM is based on a rough representation of the prototypes, relational SOM allows representing these prototypes by a virtual linear combination of all elements in the data set, referring to a pseudo-Euclidean framework. In the present article, an on-line version of relational SOM is introduced and studied. Similar to the situation in the Euclidean framework, this on-line algorithm provides a better organization and is much less sensible to prototype initialization than standard (batch) relational SOM. In a more general case, this stochastic version allows us to integrate an additional stochastic gradient descent step in the algorithm which can tune the respective weights of several dissimilarities in an optimal way: the resulting multiple relational SOM thus has the ability to integrate several sources of data of different types, or to make a consensus between several dissimilarities describing the same data. The algorithms introduced in this paper are tested on several data sets, including categorical data and graphs. On-line relational SOM is currently available in the R package SOMbrero that can be downloaded at http://sombrero.r-forge.r-project.org/ or directly tested on its Web User Interface at http://shiny.nathalievilla.org/sombrero. © 2014 Elsevier B.V.


Massoni S.,Paris-Sorbonne University | Olteanu M.,SAMM | Villa-Vialaneix N.,SAMM | Villa-Vialaneix N.,French National Institute for Agricultural Research
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Originally developed in bioinformatics, sequence analysis is being increasingly used in social sciences for the study of life-course processes. The methodology generally employed consists in computing dissimilarities between the trajectories and, if typologies are sought, in clustering the trajectories according to their similarities or dissemblances. The choice of an appropriate dissimilarity measure is a major issue when dealing with sequence analysis for life sequences. Several dissimilarities are available in the literature, but neither of them succeeds to become indisputable. In this paper, instead of deciding upon one dissimilarity measure, we propose to use an optimal convex combination of different dissimilarities. The optimality is automatically determined by the clustering procedure and is defined with respect to the within-class variance. © 2013 Springer-Verlag Berlin Heidelberg.


Karolak S.,University Paris - Sud | Nefau T.,University Paris - Sud | Bailly E.,University Paris - Sud | Solgadi A.,SAMM | Levi Y.,University Paris - Sud
Forensic Science International | Year: 2010

Illicit drugs consumption is actually an important public health concern that needs to be well defined to be managed. A new method, expressed as sewage epidemiology has been proposed by Daughton and developed by Zuccato. This method involves estimating the consumption from the measurement of drug residues in sewage. Several studies have been carried out, leading to an assessment of drugs consumption in some European countries. This work, carried out in Paris area (France) brings new data to this assessment and allows a comparison of cocaine and MDMA consumptions with European estimations.Four wastewater treatment plants (WWTPs) have been retained for the study, taking into account biological treatment, volume capacity, geographic location and social environment. Cocaine and its major metabolite benzoylecgonine (BZE), amphetamine, 3,4-methylenedioxymethamphetamine (MDMA) and buprenorphine were measured in raw water and WWTP effluent using HPLC-MS/MS after SPE extraction. Amphetamine was rarely detected. Cocaine and BZE were quantified at levels from 5 to 282ngL-1 and 15 to 849ngL-1, respectively. MDMA and buprenorphine concentrations remained under 20ngL-1. Cocaine consumption was estimated from cocaine or BZE concentrations measured in raw water and the results showed significant difference in drug taking during week or weekend. The estimated doses observed in this study are lower than those reported for others countries, especially Spain and Italy. MDMA consumption was estimated at lower levels than cocaine. © 2010 Elsevier Ireland Ltd.


Rynkiewicz J.,SAMM
Neurocomputing | Year: 2012

Multilayer perceptrons (MLP) with one hidden layer have been used for a long time to deal with non-linear regression. However, in some task, MLP's are too powerful models and a small mean square error (MSE) may be more due to overfitting than to actual modeling. If the noise of the regression model is Gaussian, the overfitting of the model is totally determined by the behavior of the likelihood ratio test statistic (LRTS), however in numerous cases the assumption of normality of the noise is arbitrary if not false. In this paper, we present an universal bound for the overfitting of such model under weak assumptions, this bound is valid without Gaussian or identifiability assumptions. The main application of this bound is to give a hint about determining the true architecture of the MLP model when the number of data goes to infinite. As an illustration, we use this theoretical result to propose and compare effective criteria to find the true architecture of an MLP. © 2012 Elsevier B.V.


Olteanu M.,SAMM | Rynkiewicz J.,SAMM
Neurocomputing | Year: 2011

The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the number of experts in the model. Our purpose is to extend the existing results for simple mixture models (Liu and Shao, 2003 [8]) and mixtures of multilayer perceptrons (Olteanu and Rynkiewicz, 2008 [9]). In this paper we first study a simple example which embodies all the difficulties arising in such models. We find that in the most general case the LRTS diverges but, with additional assumptions, the behavior of such models can be totally explicated. © 2011 Elsevier B.V.

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