Akhilesh Siddhanti
About Me: Akhilesh Siddhanti

Solving problems fascinates me. I believe that each problem can be modelled mathematically using symbols and equations, and the key to solving a problem lies in understanding the problem itself. I am a student conscientiously placed in the confluence of areas of Computer Science and Mathematics, and I embark upon new challenges as them come to me.

I am currently pursuing Master of Science in Computer Science at College of Computing, Georgia Institute of Technology with a specialization in Machine Learning. Previously, I was a Bachelor's in Computer Science and Master's in Mathematics student at BITS Pilani Goa Campus.

My current research interests lie in the confluence of the areas of Network Security and Machine Learning and am currently enrolled into both courses at Georgia Tech. Apart from this, I am pursuing courses of Computer Vision and Data & Visual Analytics. I have worked in the areas of Cryptography and Cryptanalysis at Indian Statistical Institute, Kolkata and Nanyang Technological University, Singapore.

My complete resume can be found attached here.


News


Education

B.E. (Hons) in Computer Science
M.Sc. (Hons) in Mathematics
Birla Institute of Technology and Science, Pilani
K.K Birla Goa Campus, Goa, India - 403726
M.S. in Computer Science,
Specialization in Machine Learning and Computing Systems
Georgia Institute of Technology, Atlanta, GA
USA- 30318
Research



During my undergraduate days, I have worked in the field of Cryptography, specifically in the area of stream ciphers. I have interned at Indian Statistical Institute (ISI), Kolkata and Nanyang Technological University (NTU), Singapore during the summers followed by a 1-year thesis at ISI Kolkata, on various fault, side-channel and Time-Memory-Data Tradeoff (TMDTO) Attacks on stream and block ciphers. Relevant works have been published in leading conferences and journals.

Publications:

Cryptanalysis using Machine Learning

  1. Finding Fault Locations With Machine Learning: Case Study With CLX-128. (Under Review)
    Used Deep Neural Networks to identify fault locations in a stream cipher.

Cryptography & Cryptanalysis

  1. A TMDTO Attack Against Lizard, IEEE Transactions on Computers (Journal)
    Cryptanalysis of stream cipher Lizard with a time complexity faster than brute-force search.

  2. A Differential Fault Attack on Plantlet, IEEE Transactions on Computers (Journal)
    Demonstrated a Differential Fault Attack on Plantlet with minimum fault requirements.

  3. Certain Observations on ACORN v3 and Grain v1 - Implications Towards TMDTO Attacks, Journal of Hardware and Systems Security (Journal)
    An extended work of conditional TMDTO attack on ACORN v3 and Grain v1.

  4. Differential Fault Attack on SIMON with Very Few Faults and minimal assumptions, INDOCRYPT 2018 (Conference)
    Showed how block ciphers can also be vulnerable to fault attacks, like stream ciphers.

  5. Differential Fault Attack on Grain v1, ACORN v3 and Lizard, SPACE 2017 (Conference)
    Mounted fault attacks on popular stream ciphers using numerous optimizations.

  6. Certain Observations on ACORN v3 and the Implications to TMDTO Attacks, SPACE 2017 (Conference).
    Cryptanalysis of ACORN v3 using SAT solving techniques.

  7. Differential fault attack on hardware stream ciphers -- A technical survey, RICAM Special Semester (Conference).
    A survey of various fault attack techniques employed to cryptanalyze stream ciphers.
Projects

  1. Pinning Accents: Accent Classification using Machine Learning
    Classifying different dialects of English language using K-means, CNN and Bidirectional-LSTMs.

  2. Nailed it: Selecting the most relevant thumbnail for a video
    Based on features developed on aesthetics and relevance, clustering and random forests is implemented.

  3. FindMyAir: An Intelligent Trip Planning Algorithm
    Searching for an optimal Airbnb accomodation and travel plan for a given set of parameters.

  4. Facenet with Privacy Preserving Biometric Authentication
    Facial recognition using Google's Facenet, keeping in mind, the server gains no information about the client.

  5. ANN-aided fault location identification for stream ciphers
    Implemented Artificial Neural Networks to find fault locations in a stream cipher (waiting for publication).

  6. Surfboard - Surf the web, only using your keyboard!
    Developed a web extension in Javascript to help differently-abled browse the web only using a keyboard.
My hobby: Travelling!

My Resume


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