1. 05 May, 2021 11 commits
  2. 27 Feb, 2021 1 commit
    • Mohammad Shojafar's avatar
      Information Processing & Management · 36eafaee
      Mohammad Shojafar authored
      F. Aghili, H. Mala, Ch. Schindelhauer, M. Shojafar, R. Tafazolli, 'Closed-Loop and Open-Loop Authentication Protocols for Blockchain-based IoT Systems
      ', Information Processing & Management, February 2021.
      36eafaee
  3. 09 Feb, 2021 10 commits
  4. 25 Jan, 2021 1 commit
  5. 16 Jan, 2021 13 commits
    • Mohammad Shojafar's avatar
      DOI: https://doi.org/10.1007/s00521-020-04831-9 · cd061c7d
      Mohammad Shojafar authored
      
      README.txt
      
      Help file to run the project written in Python 2.7 and 3.0.
      
      Dr. Rahim Taheri did this implementation. 
      Dr. Rahim Taheri, Dr. Mohammad Shojafar and Dr. Zahra Pooranian helped on idea brainstorming and documentation. 
      Prof. Reza Javidan, Prof. Ali Miri and Prof. M. Conti helped in English correction and leading the team.
      
      If you need any help on the code, feel free to drop a message to
      
      Dr. Mohammad Shojafar <mohammad.shojafar@gmail.com> or <m.shojafar@ieee.org> or
      Dr. Rahim Taheri <taheri.rahim@gmail.com> 
      
      Step of the running project:
      
      Label_Flipping_Paper_with_Feature_Selection(LSD_CSD_KDD).py is for label flipping code with feature selection method on LSD CSD and KDD
      
      Label_Flipping_Paper_without_Feature_Selection(LSD_CSD_KDD).py is for label flipping code without feature selection method on LSD CSD and KDD
      
      The comparisons are embedded in the code.
      
      We used three datasets which can be obtained through the links on the p...
      cd061c7d
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    • Mohammad Shojafar's avatar
      source codes · b762c6dd
      Mohammad Shojafar authored
      b762c6dd
    • Mohammad Shojafar's avatar
      README · bff28469
      Mohammad Shojafar authored
      
      README.txt
      
      Help file to run the project written in Python 2.7 and 3.0.
      
      Dr. Rahim Taheri did this implementation. 
      Dr. Rahim Taheri, Dr. Mohammad Shojafar and Dr. Zahra Pooranian helped on idea brainstorming and documentation. 
      Prof. Reza Javidan, Prof. Ali Miri and Prof. M. Conti helped in English correction and leading the team.
      
      If you need any help on the code, feel free to drop a message to
      
      Dr. Mohammad Shojafar <mohammad.shojafar@gmail.com> or <m.shojafar@ieee.org> or
      Dr. Rahim Taheri <taheri.rahim@gmail.com> 
      
      Step of the running project:
      
      Label_Flipping_Paper_with_Feature_Selection(LSD_CSD_KDD).py is for label flipping code with feature selection method on LSD CSD and KDD
      
      Label_Flipping_Paper_without_Feature_Selection(LSD_CSD_KDD).py is for label flipping code without feature selection method on LSD CSD and KDD
      
      The comparisons are embedded in the code.
      
      We used three datasets which can be obtained through the links on the paper. 
      
      Note: you need to preprocess and clean the dataset before implementation. 
      
      
      I will be glad to cite our paper with the following details in your research papers:
      
      R. Taheri, R. Javidan, M. Shojafar, Z. Pooranian, A. Miri, M. Conti, "On Defending Against Label Flipping Attacks on Malware Detection Systems", Springer, Neural Computing and Applications (NCAA), Vol. 32, pp. 14781–14800, July 2020.
      
      DOI: https://doi.org/10.1007/s00521-020-04831-9
      bff28469
    • Mohammad Shojafar's avatar
      DOI: https://doi.org/10.1016/j.future.2019.11.034 · 38e62566
      Mohammad Shojafar authored
      README.txt
      
      Help file to run the project written in Python 2.7 and 3.0.
      
      Dr. Rahim Taheri did this implementation. 
      Dr. Rahim Taheri, Dr. Mohammad Shojafar and Dr. Meysam Ghahramani helped on idea brainstorming and documentation. 
      Reza Javidan, Zahra Pooranian and Mauro Conti helped in English correction and leading the team.
      
      If you need any help on the code, feel free to drop a message to
      
      Dr. Mohammad Shojafar <mohammad.shojafar@gmail.com> or <m.shojafar@ieee.org> or
      Dr. Rahim Taheri <taheri.rahim@gmail.com> 
      
      Step of the running project:
      
      Label_Flipping_Paper_with_Feature_Selection.py is for label flipping code with feature selection method
      
      Label_Flipping_Paper_without_Feature_Selection.py is for label flipping code without feature selection method
      
      The comparisons are embedded in the code.
      
      We used three datasets which can be obtained through the links on the paper. 
      
      Note: you need to preprocess and clean the dataset before im...
      38e62566
    • Mohammad Shojafar's avatar
      Delete Taheri et al-NCAA2020.zip · 80910e39
      Mohammad Shojafar authored
      80910e39
    • Mohammad Shojafar's avatar
      d0fb38d9
    • Mohammad Shojafar's avatar
      DOI: https://doi.org/10.1109/ICIN.2018.8401618 · aaa9ea8b
      Mohammad Shojafar authored
      
      README.txt
      
      Help file to run the project written in Matlab.
      
      Dr. Mohammad Mahdi Tajiki did this implementation. 
      Dr. Mohammad Shojafar, Dr. Mohammad Mahdi Tajiki helped on idea brainstorming and documentation. 
      S. Salsano, L. Chiaraviglio, B. Akbari helped in English correction and leading the team.
      
      If you need any help on the code, feel free to drop a message to
      
      Dr. Mohammad Shojafar <mohammad.shojafar@gmail.com> or <m.shojafar@ieee.org> or
      Dr. Mohammad Mahdi Tajiki <mohammad59mt@gmail.com> 
      
      Step of the running project:
      
      How to run the code:
      
      The code is done using CVX solver on MATLAB.
      
      First, you are requested to download and install CVX solver from http://cvxr.com/cvx/doc/solver.html
      
      Then, you can easily access model file for all the scenarios of the published paper in Wiley CPE in the ‘Simulation’ folder.
      
      1. ’CreateTopology.m’ is used to establish the topology of the network, e.g., Abilene topology
      2. ‘CreateVMs.m...
      aaa9ea8b
    • Mohammad Shojafar's avatar
      11ea1027
    • Mohammad Shojafar's avatar
      DOI: https://doi.org/10.1109/ICIN.2018.8401618 · e3f36512
      Mohammad Shojafar authored
      
      README.txt
      
      Help file to run the project written in Matlab.
      
      Dr. Mohammad Mahdi Tajiki did this implementation. 
      Dr. Mohammad Shojafar, Dr. Mohammad Mahdi Tajiki helped on idea brainstorming and documentation. 
      S. Salsano, L. Chiaraviglio, B. Akbari helped in English correction and leading the team.
      
      If you need any help on the code, feel free to drop a message to
      
      Dr. Mohammad Shojafar <mohammad.shojafar@gmail.com> or <m.shojafar@ieee.org> or
      Dr. Mohammad Mahdi Tajiki <mohammad59mt@gmail.com> 
      
      Step of the running project:
      
      How to run the code:
      
      The code is done using CVX solver on MATLAB.
      
      First, you are requested to download and install CVX solver from http://cvxr.com/cvx/doc/solver.html
      
      Then, you can easily access model file for all the scenarios of the published paper in Wiley CPE in the ‘Simulation’ folder.
      
      1. ’CreateTopology.m’ is used to establish the topology of the network, e.g., Abilene topology
      2. ‘CreateVMs.m’ is used to establish VMs riding on each server/node of the designed topology
      3. ‘SolverForONR.m’ and ‘SFC_ONR.m’ are the solver code (CVX) for ONR algorithm for without SFC and with SFC, respectively.  
      4. ‘HNR-RR.m’ is used to address the relaxation of HNR algorithm. 
      5. The rest m files are used to plot the results and make analytics of the results.
      
      I will be glad to cite our paper with the following details in your research papers:
      Wiley CPE:
      
      M.M. Tajiki, M. Shojafar, S. Salsano, M. Shojafar, L. Chiaraviglio, B. Akbari, "Energy-efficient Path Allocation Heuristic for Service Function Chaining", The 21st IEEE Conference on Innovations in Clouds, Internet and Networks, (ICIN 2018), Paris, France, pp. 1-8, 2018. DOI: https://doi.org/10.1109/ICIN.2018.8401618
      
      
      The papers are supported and fully funded by H2020 EU project named:
      
      SUPERFLUIDITY
      
      Project Link: http://superfluidity.eu/
      
      (grant agreement No. 671566)
      e3f36512
    • Mohammad Shojafar's avatar
      7a923d43
    • Mohammad Shojafar's avatar
      Add files via upload · 7a53d35a
      Mohammad Shojafar authored
      7a53d35a
    • Mohammad Shojafar's avatar
      Automatic Clustering of Attacks in IDS · 7918a137
      Mohammad Shojafar authored
      README.txt
      
      Help file to run the project written in Matlab.
      
      Dr. Rahim Taheri and Dr. Mohammad Shojafar did this implementation. 
      Dr. Mohammad Shojafar, Dr. Rahim Taheri, Dr. Zahra Pooranian helped on idea brainstorming and documentation. 
      Dr. Reza Javidan, Prof. Ali Miri, Prof. Yaser Jararweh helped in English correction and leading the team.
      
      Contact: Dr. Mohammad Shojafar / Dr. Rahim Taheri
      Email: m.shojafar@surrey.ac.uk; m.shojafar@ieee.org/ r.taheri@sutech.ac.ir; tahery.rahim@gmail.com 
      
      Step of the running project:
      
      1.	Open this project in your Matlab. the NLS-KDD 10% dataset is preprocessed and saved in ‘KDD.mat’
      2.	You can run ‘abc.m’ to run abc algorithm.
      3.	You can run ‘abc2.m’ to run abc2 algorithm.
      4.	You can run ‘de.m’ to run deferential evaluation algorithm.
      5.	You can run ‘pso.m’ to particle swarm optimization algorithm.
      6.	You can run ‘hs.m’ to run hs algorithm.
      7.	Since we use two indexes for the analyzing o...
      7918a137
  6. 14 Dec, 2020 4 commits