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Behavioral profiles for advanced email features
2009
Proceedings of the 18th international conference on World wide web - WWW '09
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We believe that our results provide significant insights towards informed design of advanced email features, including those of social-networking type. ...
We highlight various novel threshold behaviors and provide support for existing hypotheses such as that of the least-effort reply. ...
This would be of interest for an advanced email service, complemented with socialnetworking features. Future work may study other prediction models for email replies. ...
doi:10.1145/1526709.1526805
dblp:conf/www/KaragiannisV09
fatcat:pwfxpv5ov5dbzpmezx635vd23y
That Ain't You: Detecting Spearphishing Emails Before They Are Sent
[article]
2014
arXiv
pre-print
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In this paper, we propose a radical change of focus in the techniques used for detecting such malicious emails: instead of looking for particular features that are indicative of attack emails, we look ...
We present IdentityMailer, a system that validates the authorship of emails by learning the typical email-sending behavior of users over time, and comparing any subsequent email sent from their accounts ...
Lin, Dermot Harnett, Joe Krug, David Cawley, and Nick Johnston for their support and comments. We would also like to thank Adam Doupè and Ali Zand for reviewing an early version of this paper. ...
arXiv:1410.6629v1
fatcat:cdkerm4dxfhrrpk6vfs7wezizq
That Ain't You: Blocking Spearphishing Through Behavioral Modelling
[chapter]
2015
Lecture Notes in Computer Science
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To fight the spearphishing threat, we propose a change of focus in the techniques that we use for detecting malicious emails: instead of looking for features that are indicative of attack emails, we look ...
We do this by modelling the email-sending behavior of users over time, and comparing any subsequent email sent by their accounts against this model. ...
Acknowledgments This work was supported by a Symantec Research Labs Graduate Fellowship for the year 2012. We would like to thank the anonymous reviewers for their useful comments. ...
doi:10.1007/978-3-319-20550-2_5
fatcat:5ccicmiu2ngabl7v5payaofnpi
EmailProfiler: Spearphishing Filtering with Header and Stylometric Features of Emails
2016
2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC)
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The approach first builds probabilistic models of both email metadata and stylometric features of email content. ...
Spearphishing is effective because it is fundamentally difficult for users to distinguish legitimate emails from spearphishing emails without additional defensive mechanisms. ...
compare an incoming email against the behavioral profile extracted for the sender. ...
doi:10.1109/compsac.2016.105
dblp:conf/compsac/DumanKERK16
fatcat:7ffmxlsodnarbpuc7iwtptlxoa
Reading Between the Lines: Content-Agnostic Detection of Spear-Phishing Emails
[chapter]
2018
Lecture Notes in Computer Science
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Based on these traits, we develop a method capable of learning profiles for a large set of senders and identifying spoofed emails as deviations thereof. ...
Spear-phishing is an effective attack vector for infiltrating companies and organisations. ...
These targeted attacks are more advanced than regular phishing or spam campaigns, as they are individually adapted to the environment and behavior of the victim. ...
doi:10.1007/978-3-030-00470-5_4
fatcat:pff5qid6jngjpdjv26e6ologqe
Direct and Indirect Human Computer Interaction Based Biometrics
2007
Journal of Computers
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We examine current research and analyze the types of features used to describe HCI behavior. ...
After comparing accuracy rates for verification of users using different HCI-based biometric approaches we address privacy issues which arise with the use of HCI dependant biometrics. ...
for the person's email behavior. ...
doi:10.4304/jcp.2.10.76-88
fatcat:efex2hxb3vcfzlm2jxbxannjwq
Detecting insider attacks in medical cyber–physical networks based on behavioral profiling
2018
Future generations computer systems
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Special Administrative Region h i g h l i g h t s • A trust-based mechanism is built to detect insider nodes via behavioral profiling. • We select four mobile and networking features to establish behavioral ...
A node's reputation can be judged by identifying the difference in Euclidean distance between two behavioral profiles. ...
Discussion Behavioral profile. In this work, we mainly consider four features to build a behavioral profile based on the advice from the healthcare mangers. ...
doi:10.1016/j.future.2018.06.007
fatcat:r6lcc6sgbvbepccn3ostmupi3u
A Behavior-Based Approach to Securing Email Systems
[chapter]
2003
Lecture Notes in Computer Science
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The Malicious Email Tracking (MET) system, reported in a prior publication, is a behavior-based security system for email services. ...
EMT includes a variety of behavior models for email attachments, user accounts and groups of accounts. Each model computed is used to detect anomalous and errant email behaviors. ...
EMT is also being extended to include the profiles of the sender and recipient email accounts, and their clique behavior, as features for the supervised learning component. ...
doi:10.1007/978-3-540-45215-7_5
fatcat:xilqudmaurei3fmfgzyrm464dm
Towards Fully Automated Digital Alibis with Social Interaction
[chapter]
2014
IFIP Advances in Information and Communication Technology
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This paper demonstrates that forged alibis can be created for online activities and social interactions. ...
The framework simulates user activity and supports communications via email as well as instant messaging using a chatbot. ...
and usual concurrent actions must be configured in advance. ...
doi:10.1007/978-3-662-44952-3_20
fatcat:r7vyeadpg5ao5jrpi4htvzxlla
Goal-oriented Email Stream Classifier with A Multi-agent System Approach
2021
International Journal of Advanced Computer Science and Applications
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The need to automate the email stream management increases for reasons such as multifolder categorization, and spam email classification. ...
The behavior of agents was taking from an existing classifier. ...
For example, features selection is intended to identify only those features with the highest discriminatory capacity to improve classifier performance [6] . ...
doi:10.14569/ijacsa.2021.0120965
fatcat:5t5bxtotmrhczgj3gmfjuuf7ci
Intelligent email
2008
Proceedings of the 13th international conference on Intelligent user interfaces - IUI '08
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Both problems use the same underlying email classification system and task specific features. Each task is evaluated for both single-user and cross-user settings. ...
We present two prediction problems under the rubric of Intelligent Email that are designed to support enhanced email interfaces that relieve the stress of email overload. ...
Profiles were constructed for each Enron user from emails not in the evaluation corpus. ...
doi:10.1145/1378773.1378820
dblp:conf/iui/DredzeBCMBP08
fatcat:xobewclo7fd4jdj27vdm44ffqm
Analyzing social and stylometric features to identify spear phishing emails
2014
2014 APWG Symposium on Electronic Crime Research (eCrime)
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We used a combination of social features from LinkedIn profiles, and stylometric features extracted from email subjects, bodies, and attachments. ...
Targeted social engineering attacks in the form of spear phishing emails, are often the main gimmick used by attackers to infiltrate organizational networks and implant stateof-the-art Advanced Persistent ...
Feature vectors for this analysis were prepared from 4,742 SPEAR emails, and 9,353 SPAM emails, combined with social features extracted from the LinkedIn profiles of receivers of these emails. ...
doi:10.1109/ecrime.2014.6963160
dblp:conf/ecrime/DewanKK14
fatcat:jcg7xsh6obda5n2jlmo2rwlloy
A Study of Spam Detection Algorithm on Social Media Networks
[chapter]
2013
Advances in Intelligent Systems and Computing
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The growing popularity of social networking sites has made them prime targets for spammers. ...
Features on social network tries to extract both the sending behavior of mobile users and closeness for categorizing spammer and legitimate user. ...
Spammer follows one of the strategy such as being active on web for longer time period and sending friend request. The honey profile monitors spammers behavior by assigning bots. ...
doi:10.1007/978-81-322-1680-3_22
fatcat:zbmffnwkufabrp3d6a5dd444ei
Analyzing Social and Stylometric Features to Identify Spear phishing Emails
[article]
2014
arXiv
pre-print
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We used a combination of social features from LinkedIn profiles, and stylometric features extracted from email subjects, bodies, and attachments. ...
Our dataset consists of 4,742 targeted attack emails sent to 2,434 victims, and 9,353 non targeted attack emails sent to 5,912 non victims; and publicly available information from their LinkedIn profiles ...
Feature vectors for this analysis were prepared from 4,742 SPEAR emails, and 9,353 SPAM emails, combined with social features extracted from the LinkedIn profiles of receivers of these emails. ...
arXiv:1406.3692v1
fatcat:arj7tj4ozngkvcrdcud5fma6z4
Impact of demand response contracts on load forecasting in a smart grid environment
2012
2012 IEEE Power and Energy Society General Meeting
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Demand response, as a valuable feature in smart grid, is growing dramatically as an effective demand management method. ...
However, traditional load forecasting tools have limitations to reflect demand response customer behaviors into load predictions. ...
Email: weisun@ieee.org. appliances) [5] . ...
doi:10.1109/pesgm.2012.6345079
fatcat:uruahcj22bgxdds23pudpk4uwe
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