Due to outstanding developments in sensor technologies, wide spread usage of smart phones and Internet, we now have the opportunity and capability to gather huge amounts of data in different real life commercial applications (which was not possible in the past). Efficient and effective processing of this big data can significantly improve the performance of many commercial applications. However, this big data has dimensions and volumes unseen before, comes in different modalities and its quality, quantity and statistics rapidly change in time and among elements.
To accommodate these problems, the big data should be processed by advance machine learning algorithms and tools in a streaming manner, i.e., instantly, without any storage requirement, can constantly adapt to the changing statistics or quality of the data, hence can be robust and prone to variations and uncertainties.
We offer full-cycle Data Analytics starting from data gathering and cleansing to profound modeling and suggestions on implementation.
Network Based Intrusion Detection System/Intrusion Prevention System
The amount of cyber attacks has been steadily growing up during the last decade. Network Intrusion Detection and Prevention System (IDS/IPS) can provide a highly effective layer of security designed to protect critical assets from cyber threats.
Databoss provides a completely automated intrusion detection prevention system (IDPS) with real time log analysis for technical and strategic recommendations in order to enhance quality of service. We essentially review your network traffic and data, and can identify probes, attacks, exploits and other vulnerabilities. We warn you of suspicious activities and prevent them. And also, we automatically reconfigure the network to reduce the effects of a suspicious intrusion.
Our IDS/IPS Management Solutions provide organizations with full maintenance, updates, rule changes, tuning and 24/7 log monitoring. Clients are able to leverage their current technology investment, using leading security vendors. Our solutions must be properly provisioned, updated and patched to protect against threats. Policies, signatures and rules need to be updated and maintained to ensure accessibility, provide security and to comply with regulations.
Due to recent advances in device technologies, we now have the ability to collect, store and realtime process considerable amount of data from various sources including cell phone usage statistics to Internet logs. This technical advance is especially noticeable in cell phone technologies. Today, 1/5th of the world’s population use cell phones, out of which 1/3rd are smart phones.
In this product, we build a completely automated smart personal assistance system with real time activity planning and optimization capabilities in order to enhance quality of life. Comprehensive automated smart personal assistance (HAIKO) predicts "the user intend" and act on this intend directly in a time, activity and location aware manner. This predictive capability is essential for a successful automated system with continuous learning capabilities and is achieved by leveraging ideas from machine learning and computational theory.
In the past 10 years, the number of cell phone users has drastically increased. Thus, delivering the most relevant and up-to-date promotions, information, and advertisements to these users became a significant problem for telecommunication companies since we have a massive amount of relevant data on each user.
In order to obtain a bigger market share, e.g., by providing better advertisement systems, this data should be carefully processed since both user intentions and the characteristics of the data vary from one user to another. Furthermore, the user intentions itself usually change over time, which causes the data to be highly nonstationary. Hence, low complexity sequential machine learning products are needed to intelligently analyze the data, identify the user intentions and trends, predict the most suitable type of advertisement at the most convenient time for each user, and infer the reactions of the users to these advertisements.
We provide a completely automated smart advertising product that choses the most appropriate advertisement for the consumer in the given location, time and event.
We develop new technologies for cyber security, anomaly detection, big data and data intelligence. Our algorithms are currently used in several different Microsoft and IBM products such as the MSN and the ViaVoice
H. Ozkan, F. Ozkan and S. S. Kozat, "Online Anomaly Detection under Markov Statistics with Controllable Type-I Error," IEEE Transactions on Signal Processing.Accepted
H. Ozkan, O. Pelvan and S. S. Kozat, "Data Imputation through the Identification of Local Anomalies," IEEE Transactions on Neural Networks and Learning Systems.Accepted
H. Ozkan, M. A. Donmez, S. Tunc and S. S. Kozat, "A Deterministic Analysis of an Online Convex Mixture of Experts Algorithm," IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 7, pp. 1575-1581.July
N. D. Vanli and S. S. Kozat, "A Unified Approach to Universal Prediction: Generalized Upper and Lower Bounds," IEEE Transactions on Neural Networks and Learning Systems, pp. 646-651.March
M. O. Sayin, Y. Yilmaz, A. Demir and S. S. Kozat, ``The Krylov-proportionate Normalized Least Mean Fourth Approach: Formulation and Performance Analysis,'' Signal Processing, vol. 109, pp. 1-13.April
N. D. Vanli, M. A. Donmez and S. S. Kozat, ``Robust Least Squares Methods Under Bounded Data Uncertainties,'' Digital Signal Processing, vol. 36, pp. 82-92.January
DATABOSS is a high-tech research company that provides state-of-the-art data analytics services for cyber security, threat intelligence, data regression/classification, stream data processing. The main mission of DataBoss is to provide world class data analytics services based on over 20 years of expertise in renowned high-tech companies, Microsoft and IBM, in the USA.
© 2016 Databoss Bilisim