Dr. S.D Madhu Kumar
Department of Computer Science and Engineering
Dr. S.D Madhu Kumar is an Associate Professor in the Department of Computer Science and Engineering at NIT Calicut. He obtained his PhD in Computer Science from IIT Bombay. His research specialization includes Distributed Computing, Cloud Computing, Big Data & Cloud Database and software Engineering.
Cloud Storage- Advances, Challenges and Opportunities
The primary use of cloud storage today is for storage of unstructured data, which is the fastest growing and most voluminous content, causing many administrative problems. Cloud storage option enables the users and organizations to store their data remotely and enjoy good quality applications on demand without having any burden associated with local hardware resources and software managements. But there are many issues associated with storing data in the cloud. Security of the data, Ensuring the correctness of the data, Fault tolerance, meeting the consistency requirements of the applications in a multi user environment, Performance, reliability and scalability are some of the challenging issues.
There are many techniques existing today, which in turn provide correctness of data in cloud, like Merkle Hash Tree (MHT), Distributed erasure-coded data and flexible distributed storage integrity auditing mechanism. Erasure coded storage scheme offers a promising future for cloud storage. Highlights of erasure coded storage systems are that these offers same level of fault tolerance as of replication at a lower storage footprint.
This tutorial will give a glimpse into the advances, technical challenges and research issues in the cloud storage sector. There will a special focus on erasure coded storage systems and simulation tools that can be used for testing the erasure coded storage systems for cloud.
Mr. Rahul Agrawal
Principal Machine Learning Manager
Deep Learning and Applications to Language Understanding
Rahul Agrawal leads a team of engineers and scientists in Microsoft Bing Ads. His team is
responsible for query intent understanding and matching it to advertiser's intent. His primary
interest is in large scale machine learning algorithms, language understanding and deep
learning architectures. Prior to Microsoft he was with Yahoo labs where he was responsible
for click prediction for Yahoo display advertising.
In this tutorial, we will start with the basics of deep learning and study how it can be applied to various tasks in language understanding. We will look at how Deep Learning compares with respect to conventional bag-of-words representation. We will also look at how deep learning algorithms stack up when solving problems such as NER, segmentation, classification and document clustering. We will also look at various deep learning based architectures and how embedding play a role in intent representation.
Dr. V. Vaidehi
VIT university, Chennai
Dr. V. Vaidehi received her BE (ECE) from College of Engineering, Guindy, ME (Applied Electronics)
and Ph.D. in the area of Parallel Processing from Madras Institute of Technology, Anna University, Chromepet,
Chennai. She was task team member in Micro Satellite (ANUSAT) and Executed several funded project in the area
of Target Tracking, Multi-Sensor Fusion, Semantic Intrusion Detection System and Complex Event Processing. She
has served as the Head of Computer Centre, Head of Electronics department, Head of Computer technology, Head
of Information Technology and Director of AU-KBC Research Centre, MIT, Anna University, Chennai and
Chairman of Faculty of Information and Communication Engineering, Anna University, Chennai. Currently she is
Dean, School of Computer Science and Engineering, VIT University, Chennai. Her research interest includes
Networking, Parallel and Distributed Processing, Adaptive Digital Signal Processing, Image and Video Processing,
Network and System Security.
Automated Pentesting for faster Security Assessment
Automating penetration testing can be used to test the insecurity of an application. It is
conducted to find the security risk which might be present in the system. If a system is not
secured, then any attacker can disrupt or take authorized access to that system. Security risk is
normally an accidental error that occurs while developing and implementing the software.
Penetration testing is essential because it can identify the simulation environment i.e., how an
intruder may attack the system. It helps in finding the weak point of the system where attacker
make use of the weak point to exploit the target.