Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Parallel optimization sampling clustering K-means algorithm for big data processing
ZHOU Runwu, LI Zhiyong, CHEN Shaomiao, CHEN Jing, LI Renfa
Journal of Computer Applications    2016, 36 (2): 311-315.   DOI: 10.11772/j.issn.1001-9081.2016.02.0311
Abstract656)      PDF (883KB)(1541)       Save
Focusing on the low accuracy and slow convergence of K-means clustering algorithm, an improved K-means algorithm based on optimization sample clustering named OSCK (Optimization Sampling Clustering K-means Algorithm) was proposed. Firstly, multiple samples were obtained from mass data by probability sampling. Secondly, based on Euclidean distance similarity principle of optimal clustering center, the results of sample clustering were modeled and evaluated, and the sub-optimal solution of sample clustering results was removed. Finally, the final k clustering centers were got by weighted integration evaluation of clustering results, and the final k clustering centers were used as cluster centers of big data set. Theoretical analysis and experimental results show that the proposed method for mass data analysis with respect to the comparison algorithm has better clustering accuracy, and has strong robustness and scalability.
Reference | Related Articles | Metrics
FPGA-based implementation for fault detection of SMS4
XIN Xiaoxia, WANG Yi, LI Renfa
Journal of Computer Applications    2015, 35 (2): 420-423.   DOI: 10.11772/j.issn.1001-9081.2015.02.0420
Abstract543)      PDF (595KB)(379)       Save

Faults will frequently occur during the computational process of the hardware based SMS4 algorithm. The attacker can easily break the algorithm by using the fault information and performing the fault attack. In order to solve this issue, a new fault detection method for SMS4 was proposed. Firstly, locations of the fault occurrence and the impact of the faults were analyzed. Then, three detection position points on the critical path were targeted, and by monitoring these three points in real-time to locate the faults. Once a fault was successfully detected, the system would immediately re-execute the algorithm to avoid the attacker obtaining the fault information. Furthermore, the proposed SMS4 with fault detection and the original SMS4 without fault detection were implemented on two Field Programmable Gate Array (FPGA) platforms respectively, including Virtex-7 of Xilinx and Cyclone Ⅱ of Altera. Compared with the original SMS4, hardware resource of the proposed SMS4 with fault detection was increased by 30% with similar throughput on Virtex-7. Hardware resource of the proposed SMS4 with fault detection was increased by 0.1% and the throughput was around 93% on EP2C35F76C6. The experimental results show that the proposed algorithm can effectively detect faults using affordable hardware resource to avoid fault attack without affecting throughput.

Reference | Related Articles | Metrics
Differential power analysis attack based on algebraic expression for power model
CAI Zemin WANG Yi LI Renfa
Journal of Computer Applications    2014, 34 (2): 448-451.  
Abstract504)      PDF (735KB)(468)       Save
Differential Power Analysis (DPA) attack is the most efficient attack to encryption device. Some existing DPA methods have high demands for differential information and their stabilities are not strong. In this paper based on the analysis of DPA, the authors reconstructed the model of DPA, which reduced the complexity of attack. A new DPA attack combining new power model based on algebraic expression was proposed, and the experimental results show that the proposed DPA attack has the advantages of increasing the correctness of attacking without increasing the time complexity and reducing the number of the needed differential information from thousands to hundreds compared with the existing method.
Related Articles | Metrics