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Encryption plugin for Pidgin, providing up to 4096 bit RSA encryption using the NSS crypto library from Mozilla. Keys are automatically transmitted and stored, making it very easy to use, but also resistant to man-in-the-middle attacks.
Cloud MapReduce was initially developed at Accenture Technology Labs. It is a MapReduce implementation on top of the Amazon Cloud OS.
Cloud MapReduce has minimal risk w.r.t. the MapReduce patent, compared to other open source implementations, as it is implemented in a completely different architecture than described in the Google paper.
Steghide is a steganography program that is able to hide data in various kinds of image- and audio-files. The color- respectivly sample-frequencies are not changed thus making the embedding resistant against first-order statistical tests.
A utility for detecting and resisting BIDIRECTIONAL ARP spoofing. It can anti-spoof for not only the local host, but also other hosts in the same subnet. It is as well a handy helper for gateways which don't work well with ARP.
ApacheDS is an embeddable directory server entirely written in Java, which has been certified LDAPv3 compatible by the Open Group. Besides LDAP it supports Kerberos 5 and the Change Password Protocol. It has been designed to introduce triggers, stored procedures, queues and views to the world of LDAP which has lacked these rich constructs.
Malaria kills more than 1 million people a year, mostly children in sub-Saharan Africa. Antimalarial drug resistance is one of the greatest challenges facing malaria control today. Ronald is a Domain-Specific Language to model the fundamental forces driving antimalarial drug resistance including drug pharmacokinetics and pharmacodynamics, drug regimens and parasite genotypes. Example of applications of this language include the study of the consequences of counterfeit or lower quality drugs, the
SkewReduce is a framework to reduce impact of stragglers in a distributed data analysis task. The project provides two components: partition optimizer and runtime. The partition optimizer derives a good partition of input data based on user-supplied cost model of the algorithm and sample input data. The runtime schedules a series of MapReduce job in Hadoop according to the partition plan. For more detail, please refer the paper published in ACM Symposium on Cloud Computing 2010 -- Skew-resistant