Arash Molavi Kakhki

PhD student - Researcher - Nerd - Wanderer

about me

My name is Arash Molavi Kakhki (a.k.a Kakhk), I am a PhD student in Computer Science at Northeastern University, working under Professors Alan Mislove and Dave Choffnes . My research interest broadly lies in the areas of networking, network measurements, and online privacy. You can checkout a selected number of my past/current projects here and my resume here.


Taking a Long Look at QUIC: An Approach for Rigorous Evaluation of Rapidly Evolving Transport Protocols (IMC'17)

Arash Molavi Kakhki, Samuel Jero, David Choffnes, Alan Mislove, Cristina Nita-Rotaru.
[PDF (coming soon)] [Project page (coming soon)]

lib·erate, (n): A library for exposing (traffic-classification) rules and avoiding them efficiently (IMC'17)

Fangfan Li, Abbas Razaghpanah, Arash Molavi Kakhki, Arian Akhavan Niaki, David Choffnes, Phillipa Gill, Alan Mislove.
[PDF (coming soon)] [Project page (coming soon)]

Classifiers Unclassified: An Efficient Approach to Revealing IP-Traffic Classification Rules (IMC'16)

Fangfan Li, Arash Molavi Kakhki, David Choffnes, Phillipa Gill, Alan Mislove.
[PDF] [Project page]

Binge On Under the Microscope: Understanding T-Mobile’s Zero-Rating Implementation (SIGCOMM'16-Internet QoE)

Arash Molavi Kakhki, Fangfan Li, David Choffnes, Alan Mislove, Ethan Katz-Bassett.
[PDF] [Slides] [Project page]

Identifying traffic differentiation in mobile networks (IMC'15)

Arash Molavi Kakhki, Abbas Razaghpanah, Anke Li, Hyungjoon Koo, Rajesh Golani, David Choffnes, Phillipa Gill, Alan Mislove.
In Proceedings of the 15th ACM Internet Measurement Conference (IMC'15), Tokyo, Japan, October 2015.
[PDF] [Slides] [BibTex] [Project page]

Systems and methods for securing online content ratings (patent)

Arash Molavi Kakhki, Alan Mislove.
Application number US 14/210,214.
[PDF] [BibTex] [Project page]

Identifying traffic differentiation on cellular data networks (SIGCOMM'14-poster)

Arash Molavi Kakhki, Abbas Razaghpanah, Rajesh Golani, David Choffnes, Phillipa Gill, Alan Mislove.
2nd place at Student Research Competition.
[PDF] [BibTex] [Project page]

Iolaus: Securing online content rating systems (WWW'13)

Arash Molavi Kakhki, Chloe Kilman-Silver, and Alan Mislove.
[PDF] [BibTex] [Project page]

Measuring Personalization of Web Search (WWW'13)

A. Hannak, P. Sapiezynski, A. Molavi Kakhki, B. Krishnamurthy, D. Lazer, A. Mislove, and C. Wilson.
[PDF] [BibTex] [Project page]

Using the Middle to Meddle with Mobile (Tech. Report)

Ashwin Rao, Arash Molavi Kakhki, Abbas Razaghpanah, Amy Tang, Shen Wang, Justine Sherry, Phillipa Gill, Arvind Krishnamurthy, Arnaud Legout, Alan Mislove, and David Choffnes.
[PDF] [BibTex] [Project page]

Mitigating multiple identity attacks on content rating systems (SOSP'11-poster)

Arash Molavi Kakhki, Aniko Hannak, Alan Mislove, and Ravi Sundaram.
[PDF] [BibTex] [Project page]

A comparison of linear and non-linear transmitter and receiver antenna array processing for interference nulling and diversity with non-zero CSI feedback delay (IWCMC'09)

Arash Molavi Kakhki, and H. Reza.
[PDF] [BibTex]


Rigorous Evaluation of Performance and Policy Impacts of Transport Protocols and In-Network Devices (PhD Thesis)

Arash Molavi Kakhki, College of Computer and Information Science, Northeastern University, Boston, August 2017.
[PDF (coming soon)]


INRIA, Paris, France. Research Intern (Winter 2016)

Analysis of self-throttling by online video streaming providers.

Verisign Labs, Reston, VA, USA. Research Intern (Summer 2014)

Analysis and characterization of drop-and-catch domain registration ecosystem.

Telefonica, Barcelona, Spain. Research Intern (Summer 2013)

Designed and Implemented an information market which provides users with privacy and gives them control over their browsing data and enables them to selectively sell this data to data aggregators.

Selected projects

Classifiers Unclassified
[project page]

In this work, we develop a general approach for identifying classification rules that map network traffic to applications. Specifically, we use an efficient binary search and catedully-generated network flows to minimize the number of testes needed to reverse engineer the rules. We also characterize the classification rules for HTTP(S) traffic implemented in today's carrier-grade middleboxes and identify examples of misclassification.

Binge On Under the Microscope
[project page]

In this work, we conduct a study of T-Mobile’s zero-rating service, Binge On, to understand its implications for users and content providers in terms of data quota, performance, and video-streaming quality. We focus on T-Mobile and Binge On due to their recent prominence, but we believe that lessons learned from this exercise will readily apply to other carriers using similar technologies.

Differentiation Detector
[project page]

Have you ever wondered if your ISP is slowing down certain traffic relative to others? Unfortunately, you mobile device and carriers currently give you little or no way to tell if this is the case. In fact, with the recently passed FCC rules for net neutrality, it is possibly illegal for mobile carriers to block, shape or modify nearly any kind of network traffic. With Differentiation Detector, we give you a way to test if this is happening to your traffic.

[project page]

Iolaus is a system that leverages the underlying social network of online content rating systems to defend against such attacks. Iolaus uses two novel techniques: (a) weighing ratings to defend against multiple identity attacks and (b) relative ratings to mitigate the effect of “bought” ratings.

[project page]

The increasing personalization is leading to concerns about Filter Bubble effects, where certain users are simply unable to access information that the search engines’ algorithm decides is irrelevant. we develop a methodology for measuring personaliza- tion in Web search results.

Personalization tools
[project page]

Development of a browser extension to highlight personalized search results on Google. Development of JavaScript reimplementation of the Geolocation API which was used in this paper to explore the impact of location-based personalization on Google Search results.

Information Market
[project page]

In this study, we take a step towards realizing a system for online privacy that is mutually beneficial to users and online advertisers: an information market. This system not only maintains economic viability for online services, but provides users with financial compensation to encourage them to participate. We prototype and evaluate an information market that provides privacy and revenue to users while preserving and sometimes improving their Web performance.


Guest Lecturer

Network neutrality (Systems and Networks -- Spring 2015).
TCP congestion control (Systems and Networks -- Spring 2014).
C debugging (Systems and Networks -- Spring 2013).
Memory Management (Systems and Networks -- Fall 2012).
BitTorrent (Systems and Networks -- Spring 2012)

Teaching Assistant

Social Computing (Spring 2013).
Algorithms and Data Structures (Fall 2011).


PhD in computer science

College of Computer and Information Science, Northeastern University.

MS in Communications and Signal Processing

Department of Electrical Engineering, Imperial College London.

BS in Electrical Engineering

Department of Electrical Engineering, Sharif University of Technology