Xiaowen Zhang

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Xiaowen is a 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

Professor

College of Staten Island
Email Xiaowen Zhang, PhD

Department and Discipline:  Computer Science

Research Title

Parallel Collision Search for Cryptographic Hash Functions

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.

(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]

 

 

(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.  

 

 

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

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