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Ferdinando Papale

dblp:121/4964 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Malware analysis · 63% Network security · 37%
Computer networks
2 papers
Network measurement and analytics · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Malware analysis
botnet
0.422015
Analysis of a "/0" Stealth Scan From a Botnet · IEEE/ACM Trans. Netw. 2015
Analysis of a "/0" stealth scan from a botnet · Internet Measurement Conference 2012
Network measurement and analytics
traffic measurement
0.212015
Analysis of a "/0" Stealth Scan From a Botnet · IEEE/ACM Trans. Netw. 2015
Network security › intrusion detection and prevention
intrusion detection
0.112015
Analysis of a "/0" Stealth Scan From a Botnet · IEEE/ACM Trans. Netw. 2015
Network measurement and analytics › traffic analysis
darknet traffic analysis
0.012012
Analysis of a "/0" stealth scan from a botnet · Internet Measurement Conference 2012

Methods — techniques the papers use, named apart from their topics

traffic correlation · 0.7visualization · 0.4darknet measurement · 0.3
YearPublicationVenuePosition
2015 Analysis of a "/0" Stealth Scan From a Botnet
abstract
Botnets are the most common vehicle of cyber-criminal activity. They are used for spamming, phishing, denial-of-service attacks, brute-force cracking, stealing private information, and cyber warfare. Botnets carry out network scans for several reasons, including searching for vulnerable machines to infect and recruit into the botnet, probing networks for enumeration or penetration, etc. We present the measurement and analysis of a horizontal scan of the entire IPv4 address space conducted by the Sality botnet in February 2011. This 12-day scan originated from approximately 3 million distinct IP addresses and used a heavily coordinated and unusually covert scanning strategy to try to discover and compromise VoIP-related (SIP server) infrastructure. We observed this event through the UCSD Network Telescope, a /8 darknet continuously receiving large amounts of unsolicited traffic, and we correlate this traffic data with other public sources of data to validate our inferences. Sality is one of the largest botnets ever identified by researchers. Its behavior represents ominous advances in the evolution of modern malware: the use of more sophisticated stealth scanning strategies by millions of coordinated bots, targeting critical voice communications infrastructure. This paper offers a detailed dissection of the botnet's scanning behavior, including general methods to correlate, visualize, and extrapolate botnet behavior across the global Internet.
Alberto Dainotti, Alistair King, K. C. Claffy, Ferdinando Papale, Antonio Pescapè
IEEE/ACM Trans. Netw.4
2012 Analysis of a "/0" stealth scan from a botnet
abstract
Botnets are the most common vehicle of cyber-criminal activity. They are used for spamming, phishing, denial of service attacks, brute-force cracking, stealing private information, and cyber warfare. Botnets carry out network scans for several reasons, including searching for vulnerable machines to infect and recruit into the botnet, probing networks for enumeration or penetration, etc. We present the measurement and analysis of a horizontal scan of the entire IPv4 address space conducted by the Sality botnet in February of last year. This 12-day scan originated from approximately 3 million distinct IP addresses, and used a heavily coordinated and unusually covert scanning strategy to try to discover and compromise VoIP-related (SIP server) infrastructure. We observed this event through the UCSD Network Telescope, a /8 darknet continuously receiving large amounts of unsolicited traffic, and we correlate this traffic data with other public sources of data to validate our inferences. Sality is one of the largest botnets ever identified by researchers, its behavior represents ominous advances in the evolution of modern malware: the use of more sophisticated stealth scanning strategies by millions of coordinated bots, targeting critical voice communications infrastructure. This work offers a detailed dissection of the botnet's scanning behavior, including general methods to correlate, visualize, and extrapolate botnet behavior across the global Internet.
Alberto Dainotti, Alistair King, K. C. Claffy, Ferdinando Papale, Antonio Pescapè
Internet Measurement Conference4