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DTSTAMP:20250328T142541Z
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DTSTART;TZID=US/Eastern:20250326T120000
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DESCRIPTION:[]\n\nInternet traffic modeling and analysis is critical for ne
 twork design and for cybersecurity. Internet traffic differs from Telephon
 e traffic insofar as it characterized by long range dependent scale-free t
 emporal dynamics. In this talk\, we will describe multiscale analysis as a
  state-of-the-art tool to assess and quantify scale-free dynamics. We will
  also that show that wavelet analysis mut be combined with random projecti
 on strategies to permit a statistical characterization of Internet backgro
 und traffic both accurate and robust to anomalies. In turn\, these random 
 projections can be further involved into automated anomaly detection and i
 nto the identification of the IP addresses involved. However\, scale-free 
 analysis remained so far mostly univariate\, applied independently to dire
 ctional counts of either bytes or packets\, while challenges in cybersecur
 ity naturally call for multivariate analysis. Elaborating on recent theore
 tical developments on eigenvalue-based multivariate self-similarity analys
 is\, this talk will provide evidence for multivariate self-similarity in 1
 7 years of Internet traffic data from the MAWI repository and will discuss
  the potential use of multivariate self-similarity for low volume anomaly 
 detection.\n\nCo-sponsored by: Fairleigh Dickinson University\n\nSpeaker(s
 ): Dr. Patrice Abry\n\nAgenda: \nFairleigh Dickinson University\n\n1000 Ri
 ver Road\, Building: Muscarelle Center\, Room Number: 105\n\nTeaneck\, New
  Jersey\, United States 07666\n\nFor additional information about the venu
 e and parking\, please contact\n\nDr. Hong Zhao\n\nzhao@fdu.edu\n\nVirtual
 : https://events.vtools.ieee.org/m/469441
LOCATION:Virtual: https://events.vtools.ieee.org/m/469441
ORGANIZER:tan@fdu.edu
SEQUENCE:64
SUMMARY:Internet Traffic Modeling and Analysis with Application to Cybersec
 urity: Automated Anomaly Detection\, Low Volume Anomaly Detection\, Fault 
 IP Address Identification
URL;VALUE=URI:https://events.vtools.ieee.org/m/469441
X-ALT-DESC:Description: &lt;br /&gt;&lt;p class=&quot;MsoNormal&quot;&gt;&lt;img src=&quot;https://events
 .vtools.ieee.org/vtools_ui/media/display/0e343025-8087-47ed-a0e1-2092f3cf2
 024&quot; alt=&quot;&quot; width=&quot;309&quot; height=&quot;306&quot;&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot;&gt;Internet t
 raffic modeling and analysis is critical for network design and for cybers
 ecurity. Internet traffic differs from Telephone traffic insofar as it cha
 racterized by long range dependent scale-free temporal dynamics. In this t
 alk\, we will describe multiscale analysis as a state-of-the-art tool to a
 ssess and quantify scale-free dynamics. We will also that show that wavele
 t analysis mut be combined with random projection strategies to permit a s
 tatistical characterization of Internet background traffic both accurate a
 nd robust to anomalies. In turn\, these random projections can be further 
 involved into automated anomaly detection and into the identification of t
 he IP addresses involved. However\, scale-free analysis remained so far mo
 stly univariate\, applied independently to directional counts of either by
 tes or packets\, while challenges in cybersecurity naturally call for mult
 ivariate analysis. Elaborating on recent theoretical developments on eigen
 value-based multivariate self-similarity analysis\, this talk will provide
  evidence for multivariate self-similarity in 17 years of Internet traffic
  data from the MAWI repository and will discuss the potential use of multi
 variate self-similarity for low volume anomaly detection.&lt;/p&gt;&lt;br /&gt;&lt;br /&gt;A
 genda: &lt;br /&gt;&lt;p&gt;Fairleigh Dickinson University&lt;/p&gt;\n&lt;p&gt;1000 River Road\, &amp;
 nbsp\;&lt;span class=&quot;sublabel&quot;&gt;Building:&lt;/span&gt; Muscarelle Center\, &lt;span cl
 ass=&quot;sublabel&quot;&gt;Room Number:&lt;/span&gt; 105&lt;/p&gt;\n&lt;p&gt;Teaneck\, New Jersey\, Unit
 ed States 07666&lt;/p&gt;\n&lt;p&gt;For additional information about the venue and par
 king\, please contact&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;Dr. Hong Zhao&lt;/strong&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;
 p&gt;&lt;a href=&quot;mailto:zhao@fdu.edu&quot; target=&quot;_blank&quot; rel=&quot;nofollow noopener nor
 eferrer&quot;&gt;zhao@fdu.edu&lt;/a&gt;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;
 /p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p&gt;&amp;n
 bsp\;&lt;/p&gt;
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