The Experts below are selected from a list of 159 Experts worldwide ranked by ideXlab platform

Shambhu Upadhyaya - One of the best experts on this subject based on the ideXlab platform.

  • PHONEY: mimicking user response to detect phishing attacks
    2006
    Co-Authors: M. Chandrasekaran, Ramkumar Chinchani, Shambhu Upadhyaya
    Abstract:

    Phishing scams pose a serious threat to end-users and commercial institutions alike. Email continues to be the fa-vorite vehicle to perpetrate such scams mainly due to its widespread use combined with the ability to easily spoof them. Several approaches, both generic and specialized, have been proposed to address this problem. However, phishing techniques, growing in ingenuity as well as so-phistication, render these solutions weak. In this paper we propose a novel approach to detect phishing attacks using fake responses which mimic real users, essentially, revers-ing the role of the victim and the adversary. Our proto-type implementation called PHONEY, sits between a user’s mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks. Using live email data collected over a period of eight months we demonstrate data that our approach is able to detect a wider range of phishing attacks than existing schemes. Also, the performance analysis study shows that the implementation overhead introduced by our tool is very negligible. 1

  • WOWMOM - PHONEY: mimicking user response to detect phishing attacks
    2006 International Symposium on a World of Wireless Mobile and Multimedia Networks(WoWMoM'06), 1
    Co-Authors: M. Chandrasekaran, Ramkumar Chinchani, Shambhu Upadhyaya
    Abstract:

    Phishing scams pose a serious threat to end-users and commercial institutions alike. Email continues to be the favorite vehicle to perpetrate such scams mainly due to its widespread use combined with the ability to easily spoof them. Several approaches, both generic and specialized, have been proposed to address this problem. However, phishing techniques, growing in ingenuity as well as sophistication, render these solutions weak. In this paper we propose a novel approach to detect phishing attacks using fake responses which mimic real users, essentially, reversing the role of the victim and the adversary. Our prototype implementation called PHONEY, sits between a user's mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks. Using live email data collected over a period of eight months we demonstrate data that our approach is able to detect a wider range of phishing attacks than existing schemes. Also, the performance analysis study shows that the implementation overhead introduced by our tool is very negligible.

Nabil Hossain - One of the best experts on this subject based on the ideXlab platform.

  • ARES - Two-Pronged Phish Snagging
    2012 Seventh International Conference on Availability Reliability and Security, 2012
    Co-Authors: Rakesh M. Verma, Narasimha Shashidhar, Nabil Hossain
    Abstract:

    Phishing causes billions of dollars in damage every year and poses a serious threat to the Internet economy. Among the many possible communication channels, electronic mail still remains the most commonly used medium to launch phishing attacks. In this paper, we present a two dimensional approach to detecting phishing emails. We devise two independent, unsupervised classifiers, namely the link and header classifiers, and two combinations of these classifiers. We show that our schemes significantly outperform the previous unsupervised and supervised phishing detection schemes for emails in the literature. We also utilize contextual information, when available, to detect phishing. Finally, our protocol is designed to detect phishing at the email level rather than detecting fraudulent, masqueraded websites. Our implementation framework called PhishSnag, operates between a user's mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks even before reaching the inbox.

  • ESORICS - Detecting Phishing Emails the Natural Language Way
    Computer Security – ESORICS 2012, 2012
    Co-Authors: Rakesh M. Verma, Narasimha Shashidhar, Nabil Hossain
    Abstract:

    Phishing causes billions of dollars in damage every year and poses a serious threat to the Internet economy. Email is still the most commonly used medium to launch phishing attacks [1]. In this paper, we present a comprehensive natural language based scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Our scheme utilizes all the information present in an email, namely, the header, the links and the text in the body. Although it is obvious that a phishing email is designed to elicit an action from the intended victim, none of the existing detection schemes use this fact to identify phishing emails. Our detection protocol is designed specifically to distinguish between “actionable” and “informational” emails. To this end, we incorporate natural language techniques in phishing detection. We also utilize contextual information, when available, to detect phishing: we study the problem of phishing detection within the contextual confines of the user’s email box and demonstrate that context plays an important role in detection. To the best of our knowledge, this is the first scheme that utilizes natural language techniques and contextual information to detect phishing. We show that our scheme outperforms existing phishing detection schemes. Finally, our protocol detects phishing at the email level rather than detecting masqueraded websites. This is crucial to prevent the victim from clicking any harmful links in the email. Our implementation called PhishNet-NLP, operates between a user’s mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks even before reaching the inbox.

M. Chandrasekaran - One of the best experts on this subject based on the ideXlab platform.

  • PHONEY: mimicking user response to detect phishing attacks
    2006
    Co-Authors: M. Chandrasekaran, Ramkumar Chinchani, Shambhu Upadhyaya
    Abstract:

    Phishing scams pose a serious threat to end-users and commercial institutions alike. Email continues to be the fa-vorite vehicle to perpetrate such scams mainly due to its widespread use combined with the ability to easily spoof them. Several approaches, both generic and specialized, have been proposed to address this problem. However, phishing techniques, growing in ingenuity as well as so-phistication, render these solutions weak. In this paper we propose a novel approach to detect phishing attacks using fake responses which mimic real users, essentially, revers-ing the role of the victim and the adversary. Our proto-type implementation called PHONEY, sits between a user’s mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks. Using live email data collected over a period of eight months we demonstrate data that our approach is able to detect a wider range of phishing attacks than existing schemes. Also, the performance analysis study shows that the implementation overhead introduced by our tool is very negligible. 1

  • WOWMOM - PHONEY: mimicking user response to detect phishing attacks
    2006 International Symposium on a World of Wireless Mobile and Multimedia Networks(WoWMoM'06), 1
    Co-Authors: M. Chandrasekaran, Ramkumar Chinchani, Shambhu Upadhyaya
    Abstract:

    Phishing scams pose a serious threat to end-users and commercial institutions alike. Email continues to be the favorite vehicle to perpetrate such scams mainly due to its widespread use combined with the ability to easily spoof them. Several approaches, both generic and specialized, have been proposed to address this problem. However, phishing techniques, growing in ingenuity as well as sophistication, render these solutions weak. In this paper we propose a novel approach to detect phishing attacks using fake responses which mimic real users, essentially, reversing the role of the victim and the adversary. Our prototype implementation called PHONEY, sits between a user's mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks. Using live email data collected over a period of eight months we demonstrate data that our approach is able to detect a wider range of phishing attacks than existing schemes. Also, the performance analysis study shows that the implementation overhead introduced by our tool is very negligible.

Rakesh M. Verma - One of the best experts on this subject based on the ideXlab platform.

  • ARES - Two-Pronged Phish Snagging
    2012 Seventh International Conference on Availability Reliability and Security, 2012
    Co-Authors: Rakesh M. Verma, Narasimha Shashidhar, Nabil Hossain
    Abstract:

    Phishing causes billions of dollars in damage every year and poses a serious threat to the Internet economy. Among the many possible communication channels, electronic mail still remains the most commonly used medium to launch phishing attacks. In this paper, we present a two dimensional approach to detecting phishing emails. We devise two independent, unsupervised classifiers, namely the link and header classifiers, and two combinations of these classifiers. We show that our schemes significantly outperform the previous unsupervised and supervised phishing detection schemes for emails in the literature. We also utilize contextual information, when available, to detect phishing. Finally, our protocol is designed to detect phishing at the email level rather than detecting fraudulent, masqueraded websites. Our implementation framework called PhishSnag, operates between a user's mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks even before reaching the inbox.

  • ESORICS - Detecting Phishing Emails the Natural Language Way
    Computer Security – ESORICS 2012, 2012
    Co-Authors: Rakesh M. Verma, Narasimha Shashidhar, Nabil Hossain
    Abstract:

    Phishing causes billions of dollars in damage every year and poses a serious threat to the Internet economy. Email is still the most commonly used medium to launch phishing attacks [1]. In this paper, we present a comprehensive natural language based scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Our scheme utilizes all the information present in an email, namely, the header, the links and the text in the body. Although it is obvious that a phishing email is designed to elicit an action from the intended victim, none of the existing detection schemes use this fact to identify phishing emails. Our detection protocol is designed specifically to distinguish between “actionable” and “informational” emails. To this end, we incorporate natural language techniques in phishing detection. We also utilize contextual information, when available, to detect phishing: we study the problem of phishing detection within the contextual confines of the user’s email box and demonstrate that context plays an important role in detection. To the best of our knowledge, this is the first scheme that utilizes natural language techniques and contextual information to detect phishing. We show that our scheme outperforms existing phishing detection schemes. Finally, our protocol detects phishing at the email level rather than detecting masqueraded websites. This is crucial to prevent the victim from clicking any harmful links in the email. Our implementation called PhishNet-NLP, operates between a user’s mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks even before reaching the inbox.

Ramkumar Chinchani - One of the best experts on this subject based on the ideXlab platform.

  • PHONEY: mimicking user response to detect phishing attacks
    2006
    Co-Authors: M. Chandrasekaran, Ramkumar Chinchani, Shambhu Upadhyaya
    Abstract:

    Phishing scams pose a serious threat to end-users and commercial institutions alike. Email continues to be the fa-vorite vehicle to perpetrate such scams mainly due to its widespread use combined with the ability to easily spoof them. Several approaches, both generic and specialized, have been proposed to address this problem. However, phishing techniques, growing in ingenuity as well as so-phistication, render these solutions weak. In this paper we propose a novel approach to detect phishing attacks using fake responses which mimic real users, essentially, revers-ing the role of the victim and the adversary. Our proto-type implementation called PHONEY, sits between a user’s mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks. Using live email data collected over a period of eight months we demonstrate data that our approach is able to detect a wider range of phishing attacks than existing schemes. Also, the performance analysis study shows that the implementation overhead introduced by our tool is very negligible. 1

  • WOWMOM - PHONEY: mimicking user response to detect phishing attacks
    2006 International Symposium on a World of Wireless Mobile and Multimedia Networks(WoWMoM'06), 1
    Co-Authors: M. Chandrasekaran, Ramkumar Chinchani, Shambhu Upadhyaya
    Abstract:

    Phishing scams pose a serious threat to end-users and commercial institutions alike. Email continues to be the favorite vehicle to perpetrate such scams mainly due to its widespread use combined with the ability to easily spoof them. Several approaches, both generic and specialized, have been proposed to address this problem. However, phishing techniques, growing in ingenuity as well as sophistication, render these solutions weak. In this paper we propose a novel approach to detect phishing attacks using fake responses which mimic real users, essentially, reversing the role of the victim and the adversary. Our prototype implementation called PHONEY, sits between a user's mail transfer agent (MTA) and mail user agent (MUA) and processes each arriving email for phishing attacks. Using live email data collected over a period of eight months we demonstrate data that our approach is able to detect a wider range of phishing attacks than existing schemes. Also, the performance analysis study shows that the implementation overhead introduced by our tool is very negligible.