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Grant: Idea to Innovation

University of Victoria

$124,650.00

Identity and behavior-based secure personalized message classification system

EF 2018-19

Résumé
Phishing is still currently one of the most impactful forms of attack delivered through electronic messages (i.e. emails, short messages, tweets). Targeted spearheaded phishing poses even more challenges as it relies on intimate knowledge of the victim gathered from online data dumps (e.g. in the dark web) or by hijacking online accounts. Recent high-profile hacking incidents have shown the limits of traditional anti-phishing solutions, such as spam filters and anti-virus systems. Those methods are heavily focused on analyzing the ""message"" and not the ""messenger"". As such it is easy to evade them by crafting the ""message"" to fit expected messaging standards (e.g. by removing spam idiosyncrasies and keywords, proof-reading the message, and using familiar terms and names). We have developed a new approach to protect against targeted spearheaded phishing attacks based on verifying the genuineness of the messenger's identity, and checking whether key message characteristics match the messaging behavior of the claimed messenger identity with respect to the recipient. The genuineness of the messenger's identity is established through stylometric authorship verification, which is known to be very challenging when dealing with short unstructured text. Messaging behavior is based on message origin location patterns (i.e. typical locations from where genuine messages were sent by this messenger), file attachment patterns (i.e. likelihood for the messenger to attach files of certain characteristics), and embedded URLs patterns (i.e. likelihood for the messenger to embed URLs). The proposed model is used to verify both incoming and outgoing messages. Checking outgoing messages allows determining whether a legitimate account has been hijacked and is being leveraged to send out phishing messages to victims known by the account owner. Checking incoming messages protects against phishing attacks by establishing whether the sender is genuine and known by the recipient. The goal of the proposed project is to further develop and extensively test a fully working prototype, in order to establish the commercial value of the technology in anticipation of transferring it to existing cybersecurity companies.*
Programme
Idea to Innovation
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
531909-2018
Name nom
Traore, Issa
Department département
Electrical and Computer Engineering
Organization id
7
Institution établissement
University of Victoria
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
124650
Program id
I2IPJ
Program name en
Idea to Innovation
Program name fr
De l'idée à l'innovation
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
802
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Information systems and technology
Area of application fr
Systèmes d'information et technologie de l'information
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Partie
1
Nb partie
1
Application title
Identity and behavior-based secure personalized message classification system
Keyword
NSERC
Application summary
Phishing is still currently one of the most impactful forms of attack delivered through electronic messages (i.e. emails, short messages, tweets). Targeted spearheaded phishing poses even more challenges as it relies on intimate knowledge of the victim gathered from online data dumps (e.g. in the dark web) or by hijacking online accounts. Recent high-profile hacking incidents have shown the limits of traditional anti-phishing solutions, such as spam filters and anti-virus systems. Those methods are heavily focused on analyzing the ""message"" and not the ""messenger"". As such it is easy to evade them by crafting the ""message"" to fit expected messaging standards (e.g. by removing spam idiosyncrasies and keywords, proof-reading the message, and using familiar terms and names). We have developed a new approach to protect against targeted spearheaded phishing attacks based on verifying the genuineness of the messenger's identity, and checking whether key message characteristics match the messaging behavior of the claimed messenger identity with respect to the recipient. The genuineness of the messenger's identity is established through stylometric authorship verification, which is known to be very challenging when dealing with short unstructured text. Messaging behavior is based on message origin location patterns (i.e. typical locations from where genuine messages were sent by this messenger), file attachment patterns (i.e. likelihood for the messenger to attach files of certain characteristics), and embedded URLs patterns (i.e. likelihood for the messenger to embed URLs). The proposed model is used to verify both incoming and outgoing messages. Checking outgoing messages allows determining whether a legitimate account has been hijacked and is being leveraged to send out phishing messages to victims known by the account owner. Checking incoming messages protects against phishing attacks by establishing whether the sender is genuine and known by the recipient. The goal of the proposed project is to further develop and extensively test a fully working prototype, in order to establish the commercial value of the technology in anticipation of transferring it to existing cybersecurity companies.*