Xiaowen is an Associate Professor at College of Staten Island and a PhD faculty member at Graduate Center, CUNY. He received a PhD in Computer Science from City University of New York and a PhD in Electrical Engineering from Beijing Jiaotong University. His research interests include information security,  cryptography, wireless communications, biometrics, and RFID security & privacy.

Contact Information

Xiaowen Zhang, PhD
Associate Professor
College of Staten Island
Phone : 718.982.3262
Contact Via Email


Department and Discipline:  Computer Science

Research Title

Parallel Collision Search for Cryptographic Hash Functions

Research Description

A cryptographic hash function (short for hash function) takes a much longer input message of arbitrary length and outputs a very shorter-fixed-length bit-string, called hash.  Since a large domain is mapped to a smaller range, collisions (pairs of inputs are mapped to the same output) are inevitable.  However, as required for a hash function, it should be computationally infeasible to find any two distinct inputs that hash to the same value, i.e. collision resistant.  Hash functions are commonly used for data integrity in conjunction with digital signature.  Parallel collision search for hash function is to find hash collisions in an efficient and effective way.

Publications pertaining to the HPC over the past five years

(1). Melisa Cantu*, Joon Kim*, and Xiaowen Zhang. Finding Hash Collisions using MPI on HPC Clusters. Proceedings of 2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT 2017), Farmingdale, NY, May 5-6, 2017. [6 pages]  

 

 

(2). Vincent Chiriaco*, Aubrey Franzen*, Rebecca Thayil*, and Xiaowen Zhang. Finding Partial Hash Collisions by Brute Force Parallel Programming. Proceedings of 2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT 2017), Farmingdale, NY, May 5-6, 2017. [6 pages]

 

 

(3). Vincent Chiriaco*, Aubrey Franzen*, Rebecca Thayil*, and Xiaowen Zhang. Finding Partial Hash Collisions by Brute Force Parallel Programming. Proceedings of the 37th IEEE Sarnoff Symposium, New Jersey, September 2016. [2 pages]

 

 

Current Funding

(1). NSF: Research Experiences for Undergraduates in Computational Methods in High Performance Computing with Applications to Computer Science (Period: 10/01/2014 ~ 09/30/2017), $356,134, Co-PI.

 

 

(2). PSC-CUNY Research Award Cycle-48: A Bloom filter based scheme for removing obsolete file blocks (Period: 07/01/2017~06/30/2018), $5,896, PI.  

 

 

Collaborators on the HPCC based Research Project

Melisa Cantu, Joon Kim, Vincent Chiriaco, Aubrey Franzen, and Rebecca Thayil. They were the REU Undergraduate Students.

Contribution of the HPC in my research

Parallel programming MPI training, the use of HPC clusters to search for hash function collisions.