The Fifth Elephant 2018

The seventh edition of India's best data conference

Big Data Forensic Analytics

Submitted by Deepak Mane (@deepak5278) on Sunday, 4 March 2018

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Technical level

Beginner

Section

Full talk

Status

Submitted

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Total votes:  +1

Abstract

Big Data forensics is a new type of forensics, just as Big Data is a new way of solving the challenges presented by large, complex data. Thanks to the growth in data and the increased value of storing more data and analyzing it faster—Big Data solutions have become more common and more prominently positioned within organizations. As such, the value of Big Data systems has grown, often storing data used to drive organizational strategy, identify sales, and many different modes of electronic communication. The forensic value of such data is obvious: if the data is useful to an organization, then the data is valuable to an investigation of that organization. The information in a Big Data system is not only inherently valuable, but the data is most likely organized and analyzed in such a way to identify how the organization treated the data.
Big Data forensics is the forensic collection and analysis of Big Data systems. Traditional computer forensics typically focuses on more common sources of data, such as mobile devices and laptops. Big Data forensics is not a replacement for traditional forensics. Instead, Big Data forensics augments the existing forensics body of knowledge to handle the massive, distributed systems that require different forensic tools and techniques

Outline

In Big Data Forensic workshop/Presentation , I will cover following topics

• Goals of a forensic investigation • Forensic investigation methodology • Big Data – defined and described • Key differences between traditional forensics and Big Data forensics • Understanding hadoop and its internal Architecture • Data source identification • Structured and unstructured data • Data collection types • HDFs Data Collection techniques using Linux commands • HIVE/Mapreduce envidence techniques using linux command • Analysis of evidence using Linux • Preparation of reports • Solution to fix issues.

Requirements

Laptops , Forensic analytics software

Speaker bio

Designation – Enterprise big Data Solution Architect
16+ Years Experience in Industry (12 Years in TCS , 4 Years in Tata Institute Fundamental Research)
Currently pursing PhD in Big Data Forensic analytics at VTU – Belgaum university
6+ Onsite working experience (USA, UK , Europe and Asia)
18+ Research/Technical white papers published
Working as TPC and Reviewer for national and International Conferences
Conducted 100+ Seminar/Workshop in Engineering Colleges
Research domain – Big Data Analytics , Forensic analysis , Augmented Reality , Cloud Computing

Slides

https://www.slideshare.net/secret/wKLpUvElWws0jv

Comments

  • 1
    Zainab Bawa (@zainabbawa) Reviewer 7 months ago

    Deepak, you have to share slides and preview video for us to evaluate this talk.

  • 1
    Deepak Mane (@deepak5278) Proposer 7 months ago

    Please provide me link so i can upload ppt and videos

  • 1
    Venkata Pingali (@venkatapingali) 7 months ago

    Say hello to Harrick and team from my side!

    I think this is a significant and growing area of work but it needs to be clearly articulated and methods identified.

    A few thoughts after looking at the slides:

    1. The talk has to be simplified and decluttered. Several of the slides are almost unreadable. Would recommend keeping the background plain, font consistent, and limiting to 30pt font.
    2. The talk has to go beyond overview of data forensics to specific challenges, methods, and approaches. You can assume a reasonably informed audience.
    3. The talk could pick up a specific case (e.g., telecom fraud you mention) and develop that story to identify specific challenges and methods.
    4. You should explicity identify what the takeaway for the audience is.

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