An Analysis of Optimal Link Bombs

We analyze the phenomenon of collusion for the purpose of boosting the pagerank of a node in an interlinked environment. We investigate the optimal attack pattern for a group of nodes (attackers) attempting to improve the ranking of a specific node (the victim). We consider attacks where the attackers can only manipulate their own outgoing links. We show that the optimal attacks in this scenario are uncoordinated, i.e. the attackers link directly to the victim and no one else. nodes do not link to each other. We also discuss optimal attack patterns for a group that wants to hide itself by not pointing directly to the victim. In these disguised attacks, the attackers link to nodes $l$ hops away from the victim. We show that an optimal disguised attack exists and how it can be computed. The optimal disguised attack also allows us to find optimal link farm configurations. A link farm can be considered a special case of our approach: the target page of the link farm is the victim and the other nodes in the link farm are the attackers for the purpose of improving the rank of the victim. The target page can however control its own outgoing links for the purpose of improving its own rank, which can be modeled as an optimal disguised attack of 1-hop on itself. Our results are unique in the literature as we show optimality not only in the pagerank score, but also in the rank based on the pagerank score. We further validate our results with experiments on a variety of random graph models.Comment: Full Version of a version which appeared in AIRweb 200

Fake News Detection with Deep Diffusive Network Model

In recent years, due to the booming development of online social networks, fake news for various commercial and political purposes has been appearing in large numbers and widespread in the online world. With deceptive words, online social network users can get infected by these online fake news easily, which has brought about tremendous effects on the offline society already. An important goal in improving the trustworthiness of information in online social networks is to identify the fake news timely. This paper aims at investigating the principles, methodologies and algorithms for detecting fake news articles, creators and subjects from online social networks and evaluating the corresponding performance. This paper addresses the challenges introduced by the unknown characteristics of fake news and diverse connections among news articles, creators and subjects. Based on a detailed data analysis, this paper introduces a novel automatic fake news credibility inference model, namely FakeDetector. Based on a set of explicit and latent features extracted from the textual information, FakeDetector builds a deep diffusive network model to learn the representations of news articles, creators and subjects simultaneously. Extensive experiments have been done on a real-world fake news dataset to compare FakeDetector with several state-of-the-art models, and the experimental results have demonstrated the effectiveness of the proposed model

Essays on the Computation of Economic Equilibria and Its Applications.

The computation of economic equilibria is a central problem in algorithmic game theory. In this dissertation, we investigate the existence of economic equilibria in several markets and games, the complexity of computing economic equilibria, and its application to rankings. It is well known that a competitive economy always has an equilibrium under mild conditions. In this dissertation, we study the complexity of computing competitive equilibria. We show that given a competitive economy that fully respects all the conditions of Arrow-Debreu's existence theorem, it is PPAD-hard to compute an approximate competitive equilibrium. Furthermore, it is still PPAD-Complete to compute an approximate equilibrium for economies with additively separable piecewise linear concave utility functions. Degeneracy is an important concept in game theory. We study the complexity of deciding degeneracy in games. We show that it is NP-Complete to decide whether a bimatrix game is degenerate. With the advent of the Internet, an agent can easily have access to multiple accounts. In this dissertation we study the path auction game, which is a model for QoS routing, supply chain management, and so on, with multiple edge ownership. We show that the condition of multiple edge ownership eliminates the possibility of reasonable solution concepts, such as a strategyproof or false-name-proof mechanism or Pareto efficient Nash equilibria. The stationary distribution (an equilibrium point) of a Markov chain is widely used for ranking purposes. One of the most important applications is PageRank, part of the ranking algorithm of Google. By making use of perturbation theories of Markov chains, we show the optimal manipulation strategies of a Web spammer against PageRank under a few natural constraints. Finally, we make a connection between the ranking vector of PageRank or the Invariant method and the equilibrium of a Cobb-Douglas market. Furthermore, we propose the CES ranking method based on the Constant Elasticity of Substitution (CES) utility functions.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64821/1/duye_1.pd

Optimal Link Bombs are Uncoordinated *

Abstract We analyze the recent phenomenon termed a Link Bomb, and investigate the optimal attack pattern for a group of web pages attempting to link bomb a specific web page. The typical modus operandi of a link bomb is to associate a particular page with a search text and then boost that page's pagerank. (The attacking pages can only control their own content and outgoing links.) Thus, when a search is initiated with the text, a high prominence will be given to the attacked page. We show that the best organization of links among the attacking group to maximize the increase in rank of the attacked node is the direct individual attack, where every attacker points directly to the victim and nowhere else. We also discuss optimal attack patterns for a group that wants to hide itself by not pointing directly to the victim. We quantify our results with experiments on a variety of random graph models

Abstract Optimal Link Bombs are Uncoordinated ∗

We analyze the recent phenomenon termed a Link Bomb, and investigate the optimal attack pattern for a group of web pages attempting to link bomb a specific web page. The typical modus operandi of a link bomb is to associate a particular page with a search text and then boost that page’s pagerank. (The attacking pages can only control their own content and outgoing links.) Thus, when a search is initiated with the text, a high prominence will be given to the attacked page. We show that the best organization of links among the attacking group to maximize the increase in rank of the attacked node is the direct individual attack, where every attacker points directly to the victim and nowhere else. We also discuss optimal attack patterns for a group that wants to hide itself by not pointing directly to the victim. We quantify our results with experiments on a variety of random graph models.