Page 200 - Kaleidoscope Academic Conference Proceedings 2021
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2021 ITU Kaleidoscope Academic Conference




           the current situation of the network and its expected future to   system completely. Intelligent algorithms have also shown
           make the best decision for the best outcome. Computational   to be beneficial for implementing this technique. With the
           methods  need  to  have  complete  data  on  the  system’s   purpose of providing security in the network, deep neural
           variables;  instead,  intelligent  methods  have  the  ability  to   network  and  principal  component  analysis  algorithms  are
           consider all variables and find the equilibrium point where   utilized and the goal is to learn the behavior of users and
           a KPI is met while having the maximum revenue possible [41].   devices in order to detect malicious behavior and intrusion
           Deep Reinforcement Learning (DRL) is a perfect candidate for   in the network [16].
           this problem, considering all variables in the network and
           learning  its  behavior  to  determine  the  best  decision  for   5.  CHALLENGES AND OPEN ISSUES
           reaching  the  desired  outcome.  Deep  reinforcement
           techniques operate as follows:                     Due to the daily advances of technology and industry, there
                                                              are still a number of challenges and research topics that need
           •  When a new request arrives, the system takes an action to   to be addressed to ensure the proper functioning of the sliced
             maximize the long-term award. This action can be either   5G  networks.  Communication  networks  are  undergoing  a
             accepting or rejecting the request.              major  evolutionary  transformation  to  meet  the  needs  of  a
           •  After taking the action, the algorithm evaluates the action   large number of users and connected devices, and to enable
             and the award by interacting with the system and then the   the  operation of  newly  introduced  services  in  an  adaptive
             information  from  the  evaluation  is  used  to  retrain  the   manner.  Establishing  isolation  between  network  slices  is
             network.                                         very  important  and  it  is  possible  to  achieve  complete
           •  When  noticing  a  change  in  system  behavior,  the   isolation  with  today's  technologies.  But  with  complete
             algorithm  should  be  retrained  to  adapt  to  the  new   isolation,  network  efficiency  decreases  significantly,  not
             behavior [17].                                   being able to share the limited resources of ours. Therefore,
                                                              one  of  the  challenges  in  this  area  is  exploiting  intelligent
           4.3.2   Fault management                           techniques for finding the attainable degree of isolation for
           Fault  management  is  another  paramount  function  in  slice   each slice based on its use cases. As mentioned, the isolation
           automation. Fault management tasks are as mentioned below:   of  the  slices  is  of  great  importance.  Not  only  because  of
                                                              resource  sharing,  but  also  for  the  security  of  slices.  In  a
           •  Analyzing the system activities and classifying into two   poorly  isolated  slices  network,  damage  and  attack  in  one
             groups of normal and flawed                      slice will harm other slices too, causing a huge disaster in the
           •  Recognizing usual and unusual user behavior and traffic   network’s operation. Therefore, the challenge here is to find
           •  Detecting the precise location of error         a  solution  considering  the  necessity  of  slice  isolation
           •  Trying to fix the flaws                         alongside  the  need  of  resource  sharing.  These  issues  and
                                                              challenges need to be addressed in order to provide a good
           Principal  component  analysis,  independent  component
           analysis,  logistic  regression  and  Bayesian  networks  are   efficient model for 5G networks and beyond.
           algorithms that are used for fault management in networks.
           All  these  techniques  try  to  detect  faults  in  the  network’s   6.  CONCLUSION
           operation  and  predict  unusual  behavior  in  the  future.
           Furthermore,  unsupervised  learning  techniques  are  useful   In this paper, we presented the 5G network slicing concept
           for intrusion detection and spoofing attacks [16].   and its standards, use cases and architecture. Moreover, we
                                                              discussed  the  critical  role  of  AI  and  machine  learning
           4.3.3   Security                                   techniques for automation of network slicing functions and
                                                              mentioned some of the intelligent algorithm used for each
           Security is a major issue in 5G network slicing. For having a   function.  With  the  help  of  AI-based  solutions,  we  can
           secure  network,  there  are  3  subfunctions  that  need  to  be   address complex  problems  emerging  in  different  slicing
           carried out and the system can achieve an approving level of   functions such as designing, resource management and fault
           security  with  the  help  of  artificial  intelligence  in  these   management.  Considering  the  high  potential  of  artificial
           subfunctions. These main security system subfunctions are:   intelligent techniques, we can conclude that the challenges
           •  Analyzing the traffic, service requests and status of slice   mentioned above, maintaining a balance between isolation
           •   Spotting security vulnerabilities and detecting attacks in   degree of slices and resource sharing, can be addressed by
             the slice                                        exploiting ML and DL techniques. Moreover, since beyond
           •  Taking the proper action against threats and attacks   5G networks have higher data rates and a vast number of
                                                              new emerged  use  cases,  these  challenges  become  more
           Artificial intelligence has a worthwhile impact in analyzing  severe.  Therefore,  the  learning  algorithms-based  solutions
           the network traffic as well as detecting attacks and making  will get deeper and more complex.
           the  right  move  against  the  attacks  and  to  handle  the
           vulnerabilities  in  the  system.  However,  the  main  role  of        REFERENCES
           artificial intelligence in security is in analyzing the traffic,
           service requests and status of each slice. One of the effective  [1]  B.  NGMN  Alliance,  R.  El  Hattachi,  and  J.  Erfanian,
           actions against attacks is quarantining the contaminated slice.   “NGMN 5G White paper", 2015. “5G PPP Architecture
           In this way, we get to restrict the attack and its following   Working Group View on 5G Architecture View on 5G
           damage  to  other  slices  without  having  to  shut  down  the




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