introduction and rating parameters

.gitignore

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+paper.aux
+paper.bbl
+paper.blg 
+paper.dvi
+paper.log 
+paper.pdf 

init.sh

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+#!/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

paper.tex

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+\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}