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TABLE II CONSOLIDATED QUOTE BINARY FORMAT AND BYTE SIZE *

by unknown authors

Table 1: Botnet scan commands captured on a live /15 academic network during May 2005. The table shows that 70% of the captured commands were targeted at a specific /8 or /16 network.

in The dark oracle: Perspective-aware unused and unreachable address discovery

by Evan Cooke, Michael Bailey, Farnam Jahanian, Richard Mortier 2006

"... In PAGE 3: ... We looked for the specific command signatures of Agobot/Phatbot [7], rBot/SDBot [19], and Ghost-Bot in the payloads of traf- fic captured in a large academic network. Table1 shows a list of commands from approximately 11 bots detected by the system during May 2005. Each command in- structs the bot to begin scanning a range of IP addresses.... ..."

Cited by 6

Table 2: Comparison of total / average number of collected malware samples for number of captures, binaries, variants, and families between Nepenthes and HoneyBow

in Collecting Autonomous Spreading Malware Using

by High-interaction Honeypots, Jianwei Zhuge, Thorsten Holz, Xinhui Han, Chengyu Song, Wei Zou

"... In PAGE 10: ...7% of the samples in the last scan one whole month after the samples was collected. Table2 summarizes the comparison of collected malware samples for both Ne- penthes and HoneyBow. On average, Nepenthes collects 1,539 samples per day and HoneyBow 1,359, thus Nepenthes captures slightly more samples per day.... In PAGE 11: ...abel Trojan.Delf-1470 and binary B the label Trojan.Delf-142, both belong to the same family, but are di erent variants. As shown in Table2 , during the measurement period, Nepenthes collected 467 di erent malware variations of 64 families, but HoneyBow... ..."

Table 1. Encoding primitive operations for binary counters

in Representing normal programs with clauses

by Tomi Janhunen 2004

"... In PAGE 3: ...valuates to true (resp. false) under stable model semantics. In order to capture level numberings with binary counters, we need certain primitive operations to be used as subpro- grams of the forthcoming translation TrAT(P). The first set of subprograms, as listed in upper half of Table1 , concen- trates on setting counters to particular values. Each subpro- gram is to be activated only when an additional controlling atom c cannot be inferred by other rules.... ..."

Cited by 4

Table 1. Individual Bots vs. CF of Users

in Combining Collaborative Filtering with Personal Agents for Better Recommendations

by Nathaniel Good, J. Ben Schafer, Joseph A. Konstan, Al Borchers, Badrul Sarwar, Jon Herlocker, John Riedl 1999

Cited by 137

Table 3. Summary of bot command detection.

in Characterizing bots’ remote control behavior

by Elizabeth Stinson, John C. Mitchell 2007

"... In PAGE 10: ... Bots in general exhibit a great volume and diversity of behaviors. Table3 provides a summary of our test results. Row 1 identifies the total number of commands provided by each of the tested bots.... ..."

Cited by 2

Table 4: ShopBot CBMG.

in Analyzing Web Robots and Their Impact on Caching

by Virglio Almeida, Daniel Menascé, Rudolf Riedi, Flávia Peligrinelli, Rodrigo Fonseca, Wagner Meira, Jr. 2001

"... In PAGE 7: ...05 14 search 99.83 30391 Table 5: ShopBots Function Distribution and Number of Visits Table4 shows the averaged CBMG for the ShopBots. It shows a simple structure: the rst state is almost always \search apos;, and the robot leaves the \search quot; state with a very low probability.... ..."

Cited by 3

Table 6: Description of channel service bot commands.

in An inquiry into the nature and causes . . .

by Jason Franklin, Vern Paxson, Adrian Perrig, Stefan Savage

"... In PAGE 8: ...3 Market Services and Treachery The channel service bot is an interactive script run by channel administrators for the purpose of providing useful services such as credit card limit checks and access to a BIN list. Table6 describes commonly issued commands. Command Distribution: Measurement Methodology.... ..."

Table 5: ShopBots Function Distribution and