commit 7c91387d8a44874614eae787f94dd7f3c52601bd Author: realaravinth Date: Mon Sep 20 15:49:45 2021 +0530 introduction and rating parameters diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..6a080af --- /dev/null +++ b/.gitignore @@ -0,0 +1,6 @@ +paper.aux +paper.bbl +paper.blg +paper.dvi +paper.log +paper.pdf diff --git a/init.sh b/init.sh new file mode 100755 index 0000000..e5b841a --- /dev/null +++ b/init.sh @@ -0,0 +1,15 @@ +#!/bin/bash + +install() { + export TEXMFDIST=/usr/share/texmf-dist + readonly tlmgr="$TEXMFDIST/scripts/texlive/tlmgr.pl --usermode" + $tlmgr install ieeetran + $tlmgr install ieeetrantools + $tlmgr install blindtext +} + +clean() { + rm -rf paper.aux paper.fdb_latexmk paper.fls paper.log paper.pdf +} + +clean diff --git a/paper.tex b/paper.tex new file mode 100644 index 0000000..a663e78 --- /dev/null +++ b/paper.tex @@ -0,0 +1,101 @@ +\documentclass[conference]{IEEEtran} +\usepackage[english]{babel} % To obtain English text with the blindtext package +\usepackage{blindtext} +\begin{document} +\title{Analysis of bot detection and spam prevention systems} +% TODO get author names from Prof. Sibi +\author { + \IEEEauthorblockN{Aravinth Manivannan, Sibi Chakkaravarth S, TODO} + \IEEEauthorblockA{SENSE, VIT AP, AP, India - pincode\\ + foo@example.com + } +} +\maketitle + +\begin{abstract} + CAPTCHA systems were originally designed to protect against automated + bot-based Denial of Service(DoS) attacks and spam. But over time, these + systems have become ineffective due to overfocus on identifying humans from + bots than combating DoS attacks and spam. As a result, they have become + privacy invasive systems that pose accessibility challenges with reduced + effectiveness and accuracy. mCaptcha is a proof of work based, + non-interactive DoS protection system designed to overcome the limitations + of traditional CAPTCHA systems' limitations while offering superior + protection services. The mechanism is stateless, so it is able accurately + defend against attacks over anonymous networks like TOR and the + non-interactive nature makes it ideal users with auditory, cognitive and + visual disabilities. +\end{abstract} + +\section{Introduction} +\label{sec:intro} + +Denial of Service(DoS) attacks and spam campaigns reduce the quality of service +for internet services. Different types of rate-limiters were employed to combat +such attacks. Today rate-limiters on the web are synonymous with CAPTCHAs. +CAPTCHA systems work on the premise that an automated bot user can inflict more +damage than a human user and attacks can be contained if they can accurately +differentiate a human from a bot. The rise of cheap human labor powered CAPTCHA +farms in third-world countries have given attackers a way to bypass CAPTCHA +systems. To combat this new threat, CAPTCHA implementers are constantly raising the +difficulty of the challenges. This universal raise in difficulty impacts bots +and unassuming alike. The web is becoming increasingly less accessible to users +with disabilities and non-English speaking users. Some CAPTCHA systems employ +multiple methods to in their process. Privacy invasive mechanisms like cookies +and IP tracking are popular methods that are used in conjunction with +traditional CAPTCHA mechanisms, both of which are ineffective against +anonymous networks like TOR and pose serious privacy risks to their users. + +The rest of this paper, rates different CAPTCHA mechanisms and systems based on +parameters mentioned below and describe how mCaptcha overcomes some of +them. + +\subsection{CAPTCHA rating parameters} +CAPTCHA systems use a variety of methods in their decision process. Every method +has it's own strengths and limitations but the following parameters have been +chosen to uniformly rate CAPTCHA methods and systems in an attempt to compare +them. +\begin{description}[\IEEEsetlabelwidth{Effectiveness}] +\item[Privacy] + \begin{itemize} + \item Does the method use trackers or any other identifying method? + \item Does the method work in anonymous networks like TOR? + \end{itemize} +\item[Effectiveness] + \begin{itemize} + \item Is the method/system effective in containing DoS attacks? + \item Can the method be circumvented? If yes, how practical/feasible + the attack? + + \end{itemize} +\item[Accessibility] + \begin{itemize} + \item Is the method posing any challenges to visually to users + with auditory, cognitive and visual disabilities? + \item How easy is it to use? + \item Does the method have a language dependency which poses a challenge to + non-English speakers? + \end{itemize} +\item[Accuracy] + \begin{itemize} + \item How accurate is the method in detecting potentially malicious + users? + \item Are there any factors that method's impact accuracy? + \end{itemize} +\end{description} + +\subsection{CAPTCHA methods analysed} +We analysed at the following CAPTCHA methods using the above mentioned +parameters. These are popular methods are currently in deployment. +%TODO add images +\begin{description} + \item Align object + \item Blurred Text + \item Context based + \item Audio based + \item IP tracking + \item Image identification + \item Proof of work based +\end{itemize} + +\end{document}