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Global and Longitudinal Investigation of Network Connection Tampering
Global and Longitudinal Investigation of Network Connection Tampering
Global and Longitudinal Investigation of Network Connection Tampering

Detailed Information

자료유형  
 학위논문 서양
최종처리일시  
20250211153018
ISBN  
9798384046158
DDC  
621.3
저자명  
Sundara Raman, Ramakrishnan.
서명/저자  
Global and Longitudinal Investigation of Network Connection Tampering
발행사항  
[Sl] : University of Michigan, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
216 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-03, Section: A.
주기사항  
Advisor: Ensafi, Roya.
학위논문주기  
Thesis (Ph.D.)--University of Michigan, 2024.
초록/해제  
요약As the Internet's user base and criticality of online services continue to expand daily, nation-state adversaries like Internet censors are increasingly monitoring and restricting Internet traffic. These adversaries perform large-scale connection tampering attacks seeking to prevent users from accessing specific online content, compromising Internet availability and integrity. The community's understanding of the current state and global scope of such connection tampering attacks remains limited: most work has focused on the practices in particular regions or networks at specific points in time or the reachability and security of limited sets of online services. Creating a global, longitudinal, and data-driven view of connection tampering is an extremely challenging proposition since such practices are intentionally opaque and tampering mechanisms may vary. Moreover, advances in network technology and recurring instances of tampering events all over the world have necessitated high-quality measurement tools and data that can help researchers, journalists, policymakers, and advocacy groups characterize tampering technology and ensure accountability.I argue the following thesis: Connection tampering attacks such as Internet censorship are pervasive, evolving phenomena that need to be studied globally and longitudinally through data-driven network measurements. To evaluate this thesis, I present a range of empirical methods to longitudinally investigate connection tampering at the global scale. First, I explore the development of a global, longitudinal censorship measurement platform, the Censored Planet Observatory, that uses remote measurement techniques to safely measure Internet censorship in more than 200 countries. Censored Planet has collected more than 65 billion measurement data since 2018, and I overcome key challenges in the analysis of large-scale censorship measurement data. Next, I present novel measurement methods to investigate the network technology that enables connection tampering and propose frameworks to monitor their deployment around the world. I also advance methods to rapidly measure evolving tampering attacks with new threat models, such as the large-scale HTTPS interception attack in Kazakhstan in 2019. Finally, I envision intelligent censorship measurement platforms that optimize censorship measurements through reinforcement learning. My research collectively demonstrates that Internet censorship and large-scale tampering attacks consistently present new threat models, impacting a large segment of the Internet globally. 
일반주제명  
Computer engineering
일반주제명  
Computer science
일반주제명  
Web studies
일반주제명  
Information technology
키워드  
Computer security
키워드  
Computer networks
키워드  
Internet censorship
키워드  
Connection tampering
키워드  
Internet measurement
기타저자  
University of Michigan Computer Science & Engineering
기본자료저록  
Dissertations Abstracts International. 86-03A.
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

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■1001  ▼aSundara  Raman,  Ramakrishnan.
■24510▼aGlobal  and  Longitudinal  Investigation  of  Network  Connection  Tampering
■260    ▼a[Sl]▼bUniversity  of  Michigan▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a216  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-03,  Section:  A.
■500    ▼aAdvisor:  Ensafi,  Roya.
■5021  ▼aThesis  (Ph.D.)--University  of  Michigan,  2024.
■520    ▼aAs  the  Internet's  user  base  and  criticality  of  online  services  continue  to  expand  daily,  nation-state  adversaries  like  Internet  censors  are  increasingly  monitoring  and  restricting  Internet  traffic.  These  adversaries  perform  large-scale  connection  tampering  attacks  seeking  to  prevent  users  from  accessing  specific  online  content,  compromising  Internet  availability  and  integrity.  The  community's  understanding  of  the  current  state  and  global  scope  of  such  connection  tampering  attacks  remains  limited:  most  work  has  focused  on  the  practices  in  particular  regions  or  networks  at  specific  points  in  time  or  the  reachability  and  security  of  limited  sets  of  online  services.  Creating  a  global,  longitudinal,  and  data-driven  view  of  connection  tampering  is  an  extremely  challenging  proposition  since  such  practices  are  intentionally  opaque  and  tampering  mechanisms  may  vary.  Moreover,  advances  in  network  technology  and  recurring  instances  of  tampering  events  all  over  the  world  have  necessitated  high-quality  measurement  tools  and  data  that  can  help  researchers,  journalists,  policymakers,  and  advocacy  groups  characterize  tampering  technology  and  ensure  accountability.I  argue  the  following  thesis:  Connection  tampering  attacks  such  as  Internet  censorship  are  pervasive,  evolving  phenomena  that  need  to  be  studied  globally  and  longitudinally  through  data-driven  network  measurements.  To  evaluate  this  thesis,  I  present  a  range  of  empirical  methods  to  longitudinally  investigate  connection  tampering  at  the  global  scale.  First,  I  explore  the  development  of  a  global,  longitudinal  censorship  measurement  platform,  the  Censored  Planet  Observatory,  that  uses  remote  measurement  techniques  to  safely  measure  Internet  censorship  in  more  than  200  countries.  Censored  Planet  has  collected  more  than  65  billion  measurement  data  since  2018,  and  I  overcome  key  challenges  in  the  analysis  of  large-scale  censorship  measurement  data.  Next,  I  present  novel  measurement  methods  to  investigate  the  network  technology  that  enables  connection  tampering  and  propose  frameworks  to  monitor  their  deployment  around  the  world.  I  also  advance  methods  to  rapidly  measure  evolving  tampering  attacks  with  new  threat  models,  such  as  the  large-scale  HTTPS  interception  attack  in  Kazakhstan  in  2019.  Finally,  I  envision  intelligent  censorship  measurement  platforms  that  optimize  censorship  measurements  through  reinforcement  learning.  My  research  collectively  demonstrates  that  Internet  censorship  and  large-scale  tampering  attacks  consistently  present  new  threat  models,  impacting  a  large  segment  of  the  Internet  globally. 
■590    ▼aSchool  code:  0127.
■650  4▼aComputer  engineering
■650  4▼aComputer  science
■650  4▼aWeb  studies
■650  4▼aInformation  technology
■653    ▼aComputer  security
■653    ▼aComputer  networks
■653    ▼aInternet  censorship
■653    ▼aConnection  tampering
■653    ▼aInternet  measurement
■690    ▼a0984
■690    ▼a0464
■690    ▼a0489
■690    ▼a0646
■71020▼aUniversity  of  Michigan▼bComputer  Science  &  Engineering.
■7730  ▼tDissertations  Abstracts  International▼g86-03A.
■790    ▼a0127
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17164578▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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