Abstract: It is well known that spam bots mostly utilize compromised machines with certain address characteristics, such as dynamically allocated addresses, machines in specific geographic areas and IP ranges from AS’ with more tolerant spam policies. Such machines tend to be less diligently administered and may exhibit less stability, more volatility, and shorter uptimes. However, few studies have attempted to quantify how such spambot address characteristics compare with non-spamming hosts.
Quantifying these characteristics may help provide important information for comprehensive spam mitigation.
We use two large datasets, namely a commercial blacklist
and an Internet-wide address visibility study to quantify address characteristics of spam and non-spam networks. We find that spam networks exhibit significantly less availability and uptime, and higher volatility than non-spam networks. In addition, we conduct a collateral damage study of a common practice where an ISP blocks the entire /24 prefix if spammers are detected in that range. We find that such a policy blacklists a significant portion of legitimate mail servers belonging to the same prefix.

We have also updated our web-based IPv4 address browser to provide information about to what organizations each address block is allocated. The map now visualizes the whois allocation data; we thank the five regional internet registries for sharing this data with us and authorizing this visualization.

Finally, our web-based IPv4 address browser now has better time travel, with nearly 30 different census from Dec. 2005 to Nov. 2010, and we continue to update the map regularly.

Data collection for this work is through the LANDER project, and the map browser improvements are due to AMITE, both supported by DHS. Video preparation was supported by these projects and NSF through the MADCAT project.

From the abstract:

Although the Internet is widely used today, we have little information about the edge of the network. Decentralized management, firewalls, and sensitivity to probing prevent easy answers and make measurement difficult. Building on frequent ICMP probing of 1% of the Internet address space, we develop clustering and analysis methods to estimate how Internet addresses are used. We show that adjacent addresses often have similar characteristics and are used for similar purposes (61% of addresses we probe are consistent blocks of 64 neighbors or more). We then apply this block-level clustering to provide data to explore several open questions in how networks are managed. First, we provide information about how effectively network address blocks appear to be used, finding that a significant number of blocks are only lightly used (most addresses in about one-fifth of /24 blocks are in use less than 10% of the time), an important issue as the IPv4 address space nears full allocation. Second, we provide new measurements about dynamically managed address space, showing nearly 40% of /24 blocks appear to be dynamically allocated, and dynamic addressing is most widely used in countries more recent to the Internet (more than 80% in China, while less than 30% in the U.S.). Third, we distinguish blocks with low-bitrate last-hops and show that such blocks are often underutilized.

Citation: Xue Cai and John Heidemann. Understanding Block-level Address Usage in the Visible Internet. In Proceedings of the ACM SIGCOMM Conference , p. to appear. New Delhi, India, ACM. August, 2010. <http://www.isi.edu/~johnh/PAPERS/Cai10a.html>.

The abstract summarizes the tech report:

Although the Internet is widely used today, there are few sound estimates of network demographics. Decentralized network management means questions about Internet use cannot be answered by a central authority, and firewalls and sensitivity to probing means that active measurements must be done carefully and validated against known data. Building on frequent ICMP probing of 1% of the Internet address space, we develop a clustering algorithm to estimate how Internet addresses are used. We show that adjacent addresses often have similar characteristics and are used for similar purposes (61% of addresses we probe are consistent blocks of 64 neighbors or more). We then apply this block-level clustering to provide data to explore several open questions in how networks are managed. First, the nearing full allocation of IPv4 addresses makes it increasingly important to estimate the costs of better management of the IPv4 space as a component of an IPv6 transition. We provide about how effectively network addresses blocks appear to be used, finding that a significant number of blocks are only lightly used (about one-fifth of /24 blocks ha
ve most addresses in use less than 10% of the time). Second, we provide new measurements about dynamically managed address space, showing nearly 40% of /24 blocks appear to be dynamically allocated, and dynamic addressing is most widely used in countries more recently to the Internet (more than 80% in China, while less then 30% in the U.S.).

Xue Cai and John Heidemann. Understanding Address Usage in the Visible Internet. Technical Report N. ISI-TR-2009-656, USC/Information Sciences Institute, February, 2009. http://www.isi.edu/~johnh/PAPERS/Cai09b.html