Yuval Shavitt

TIST Journal 2017 Journal Article

On Network Neutrality Measurements

• Alex Maltinsky
• Ran Giladi
• Yuval Shavitt

Network level surveillance, censorship, and various man-in-the-middle attacks target only specific types of network traffic (e.g., HTTP, HTTPS, VoIP, or Email). Therefore, packets of these types will likely receive “special” treatment by a transit network or a man-in-the-middle attacker. A transit Internet Service Provider (ISP) or an attacker may pass the targeted traffic through special software or equipment to gather data or perform an attack. This creates a measurable difference between the performance of the targeted traffic versus the general case. In networking terms, it violates the principle of “network neutrality,” which states that all traffic should be treated equally. Many techniques were designed to detect network neutrality violations, and some have naturally suggested using them to detect surveillance and censorship. In this article, we show that the existing network neutrality measurement techniques can be easily detected and therefore circumvented. We then briefly propose a new approach to overcome the drawbacks of current measurement techniques.

SODA Conference 2011 Conference Paper

Approximating the Statistics of various Properties in Randomly Weighted Graphs

• Yuval Emek
• Amos Korman
• Yuval Shavitt

SODA Conference 2010 Conference Paper

Counting Stars and Other Small Subgraphs in Sublinear Time

• Mira Gonen
• Dana Ron
• Yuval Shavitt

AAMAS Conference 2007 Conference Paper

On the Benefits of Cheating by Self-Interested Agents in Vehicular Networks

• Raz Lin
• Sarit Kraus
• Yuval Shavitt

As more and more cars are equipped with GPS and Wi-Fi transmitters, it becomes easier to design systems that will allow cars to interact autonomously with each other, e. g. , regarding traffic on the roads. Indeed, car manufacturers are already equipping their cars with such devices. Though, currently these systems are a proprietary, we envision a nat- ural evolution where agent applications will be developed for vehicular systems, e. g. , to improve car routing in dense urban areas. Nonetheless, this new technology and agent ap- plications may lead to the emergence of self-interested car owners, who will care more about their own welfare than the social welfare of their peers. These car owners will try to manipulate their agents such that they transmit false data to their peers. Using a simulation environment, which mod- els a real transportation network in a large city, we demon- strate the benefits achieved by self-interested agents if no counter-measures are implemented.