Phani Vadrevu

Phani Vadrevu
University of New Orleans | UNO · Department of Computer Science

Assistant Professor

About

8
Publications
1,828
Reads
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119
Citations
Additional affiliations
August 2017 - December 2017
University of Georgia
Position
  • PhD Student

Publications

Publications (8)
Chapter
We conducted a large-scale evaluation of some popular Anti-Phishing Entities (APEs). As part of this, we submitted arrays of CAPTCHA challenge-laden honey sites to 7 APEs. An analysis of the “click-through rates” during the visits from the APEs showed strong evidence for the presence of formidable human analysis systems in conjunction with automate...
Preprint
Full-text available
The rapid growth of online advertising has fueled the growth of ad-blocking software, such as new ad-blocking and privacy-oriented browsers or browser extensions. In response, both ad publishers and ad networks are constantly trying to pursue new strategies to keep up their revenues. To this end, ad networks have started to leverage the Web Push te...
Conference Paper
Malicious ads often use social engineering (SE) tactics to coax users into downloading unwanted software, purchasing fake products or services, or giving up valuable personal information. These ads are often served by low-tier ad networks that may not have the technical means (or simply the will) to patrol the ad content they serve to curtail abuse...
Conference Paper
Full-text available
In an attempt to coerce useful information about the behavior of new malware families, threat analysts commonly force newly collected malicious software samples to run within a sandboxed environment. The main goal is to gather intelligence that can later be leveraged to detect and enumerate new malware infections within a network. Currently, most a...
Conference Paper
Full-text available
In this paper, we present AMICO, a novel system for measuring and detecting malware downloads in live web traffic. AMICO learns to distinguish between malware and benign file downloads from the download behavior of the network users themselves. Given a labeled dataset of past benign and malware file downloads, AMICO learns a provenance classifier t...

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