Jeffrey K. MacKie-Mason

A Social Mechanism for Supporting Home Computer Security (Download full paper)

Rick Wash and Jeffrey K. MacKie-Mason

Published on: October, 2008

Abstract: Hackers have learned to leverage the enormous number of poorly protected home computers by turning them into a large distributed system (known as a botnet), making home computers an important frontier for security research. They present special problems: owners are unophisticated, and usage profiles are varied making onesize-fits-all firewall policies ineffective. We propose a social firewall that collects security decisions and both user and usage characteristics, and provides users with personalized information to assist with allow/deny recommendations. To succeed, a social firewall must deal with at least three user behavior issues: why contribute private information? why make effort to provide quality information? and, how to prevent manipulation by adversaries? We sketch an incentive-centered design approach to each problem. We provide an economic model and some analytic results for a solution to the fundamental problem: why contribute? We show that an excludable public goods mechanism can achieve a better outcome than a system without social motivators.

The Case for Market-based Push Caching (Download full paper)

MacKie-Mason, Jeffrey K. Chan, Yee Man Womer, Jonathan Jamin, Sugih

Published on: November, 1999

Biased Replacement Policies for Web Caches: Differential Quality-of-Service and Aggregate User Value (Download full paper)

MacKie-Mason, Jeffrey K. Kelly, Terence P. Chan, Yee Man Jamin, Sugih

Published on: January, 1999

Abstract: Disk space in shared Web caches can be diverted to serve some system users at the expense of others. Cache hits reduce server loads, and if servers desire load reduction to different degrees, a replacement policy which prioritizes cache space across servers can provide differential quality-of-service (QoS). We present a simple generalization of least-frequently-used (LFU) replacement that is sensitive to varying levels of server valuation for cache hits. Through trace-driven simulation we show that under a particular assumption about server valuations our algorithm delivers a reasonable QoS relationship: higher byte hit rates for servers that value hits more. We furthermore adopt the economic perspective that value received by system users is a more appropriate performance metric than hit rate or byte hit rate, and demonstrate that our algorithm delivers higher "social welfare" (aggregate value to servers) than LRU or LFU.

An AOL/Time Warner Merger Will Harm Competition in Internet Online Services (Download full paper)

MacKie-Mason, Jeffrey K.

Abstract: America Online (AOL) is the largest, and in some aspects dominant, firm in the aggregation and distribution of content and services over the Internet. AOL is also the largest provider of Internet access in the U.S. Overall, it is the most successful firm in the business of online services, or the joint provision of Internet access and content and service distribution. This is a business that AOL essentially invented, and no other firm has been able to compete effectively with AOL. Time-Warner (including its Road Runner subsidiary) is one of the most important present and future competitors in this business because it is the number two aggregator and distributor via high-speed (broadband) Internet connections, the next generation of Internet access. This merger thus combines AOL and one of its most significant competitors in online services, creating significant horizontal anti-competitive effects. The merger between AOL and Time Warner will horizontally and vertically increase AOL's power in the market for Internet online services. The anti-competitive effects of this merger will harm consumers.