An empirical study of spam traffic and the use of DNS black lists

Jung, Jaeyeon; Sit, Emil

doi:10.1145/1028788.1028838

Cited by 143 publications

(92 citation statements)

References 3 publications

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“…In [13], Jung and Sit check the use of DNS blacklists for address-based filtering of spams. There are some advantages and disadvantages of whitelists and blacklists.…”

Section: Related Workmentioning

confidence: 99%

Spam Reduction by using E-mail History and Authentication (SREHA)

Yasin

2016

IJCNIS

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Abstract-Spam messages are today one of the most serious threats to users of E-mail messages. There are several ways to prevent and detect spam message, the most important way is filtering spam. Sometimes Filtering fails to discover some spam messages or even fails in the classification of non-spam messages as a spam messages. In this paper, we suggest a new effective method that reduces the spam messages by integrating prevention and detection techniques in one scheme. The reduction achieved by considering history and user authentication. This method based on issuing a certificate to each reliable user during the process of Email account Creation. The certificate used by Email servers to discard or forward ingoing or outgoing Emails. Each Server has to maintain white, gray and blacklist according to Email classification spam or ham, which determined by the user or by the contents examination of the message in terms of empty or contained only links without any text or by searching for a specific keywords in the subject and in the content. We believe that there are no bad or good E-mails forever, so the proposed model dynamically allows the transition of E-mail from one state to another state based on the number of received spam and ham messages.

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“…In [13], Jung and Sit check the use of DNS blacklists for address-based filtering of spams. There are some advantages and disadvantages of whitelists and blacklists.…”

Section: Related Workmentioning

confidence: 99%

Spam Reduction by using E-mail History and Authentication (SREHA)

Yasin

2016

IJCNIS

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“…Blacklisting is the most commonly used technique. Back in 2004, Jung and Sit observed that 80% of the identified spam sources of their dataset were found in at least one DNS blacklist [11]. However, Ramachandran et al showed in [16] that DNS-based blacklists cannot keep up with bots, which is the main source of today's spamming activity.…”

Section: B Network-level Mitigation Techniquesmentioning

confidence: 99%

Network-level characteristics of spamming: An empirical analysis

Kokkodis

Faloutsos

Markopoulou

2011

2011 19th IEEE International Conference on Network Protocols

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Abstract-Has the behavior of spammers changed over the last few years? To answer this question, we conduct a study from three recent data sources. Specifically, we focus on the following broad questions: (a) how are email addresses harvested, (b) where is spam coming from, and (c) how does spam evolve over time. First, we discuss whether spammers still use email harvesting : 34% of the honeypot accounts we publicised received spam after 72 days on average. Interestingly, we find that simple email address obfuscation is quite effective against harvesting. Second, we identify significant skew in the spatial distribution of the origin of spam in both the IP-level and AS-level of granularity. We find that 20% of the active IPs are responsible for 80% of the total volume of spam and that 10% of the spamming ASes are responsible for the 90% of the volume. Finally, we study the temporal characteristics of the spamming IPs and find that spam activity has spread to new /8 subnetworks since 2006. Considering these spatio-temporal trends, the future of anti-spam is mixed: the current skewed spatial distribution of spam sources could be helpful in filtering spam, but the fact that spam sources are spreading in the IP space is a worrisome sign.

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“…There is a prediction that the spam will be 70% of the email traffic in 2007 [1]. There are lot of source filters are available in real time.…”

Section: Source Filtersmentioning

confidence: 99%

“…Even if one DNS black list is out of service the mail server can manage with other lists. In recent days the DNSBL lookups are increased tremendously of total DNS lookups compared to 5 years before [1]. Nearly 80% of the spam generated by relays that appear in one at least one of eight major blacklists [4].…”

Section: Bayesian Filtermentioning

confidence: 99%