This is the repository of codes for the paper "Zero-delay Lightweight Defenses against Website Fingerprinting" in USENIX Security 2020. Payap Sirinam, a computing and information sciences Ph.D. student, was tasked with exploring the potential for deep learning in the website fingerprinting attack. The WF attacker wishes to monitor a set of sensitive web pages and identify when a client visits these pages. Website Fingerprinting. One of members of the Tor project, Mike Perry, criticised this attack. This repository contains code and data for "Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks" paper, published in PETS 2020. machine-learning privacy deep-learning website-fingerprinting tor-network attacks privacy-enhancing-technologies timing-analysis tik-tok. In a website fingerprinting attack, an eavesdropper analyses the traffic between the Tor user and entry node of the Tor network to infer which websites the user has visited. Previous studies focus more on identifying individual webpages. Naval Research Laboratory, and Carmela Troncoso of EPFL SPRING Lab), these attacks could allow threat actors to observe the traffic patterns between the user and the . The adversary can reside in intermediate nodes such as the routers or the switches to eavesdrop on the network traffic. 10431 LNCS, Springer Verlag, pp. Attacks using (features extracted from) this information to infer the website a user visits are called Website Fingerprinting (WF) attacks. Inherent defenses of anonymous communication systems such as The Onion Router (Tor) cannot compete with current WF attacks. PETS 2016. Whilst existing difficulty in the preparation of many training samples, we study a more realistic problem — few-shot website fingerprinting attack where only a few training . The website fingerprinting attack aims to identify the content (i.e., a webpage accessed by a client) of encrypted and anonymized connections by observing patterns of data flows such as packet . Figure 1 shows the WF attack model. Passive Website Fingerprinting Attacks Tao Wang Department of Computer Science and Engineering Hong Kong University of Science and Technology taow@cse.ust.hk Ian Goldberg Cheriton School of Computer Science University of Waterloo iang@cs.uwaterloo.ca Abstract Website fingerprinting (WF) is a traffic analysis attack Paper links: T. Wang. Website fingerprinting is the act of recognizing web traffic through surveillance despite the use of encryption or anonymizing software. Website fingerprinting attacks, which use statistical analysis on network traffic to compromise user privacy, have been shown to be effective even if the traffic is sent over anonymity-preserving networks such as Tor. These attacks break the privacy expected by users of privacy technologies, including low-latency anonymity networks such as proxies, VPNs, or Tor. 122. Since the web page is transported in encrypted over GQUIC, IQUIC, or HTTPS, the adversary cannot identify what content . According to a team of academics (Giovanni Cherubin of Alan Turing Institute, Rob Jansen of U.S. Taking each website as a specific class, this is essentially a multiclass classification problem. Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning The MIT Faculty has made this article openly available. We apply this tool to a comprehensive set of features extracted from a large set of To cite the paper: Your story matters. Website Fingerprinting using Traffic Analysis Attacks Author: Mukta Created Date: 12/10/2012 10:13:13 AM . Data set used in this paper. In reality, the assumption may not hold because users tend to . Website Fingerprinting (WF) is a type of traffic analysis attack that enables a local passive eavesdropper to infer the victim's activity, even when the traffic is protected by a VPN or an . Robust Website Fingerprinting Through the Cache Occupancy Channel. Website traffic fingerprinting is an attack where the adversary attempts to recognize the encrypted traffic patterns of specific web pages without using any other information. We apply this tool to a comprehensive set of features extracted from a large set of websites and WF defense . The classical attack model used to evaluate website fingerprinting attacks assumes an on-path adversary, who can observe all traffic traveling between the user's computer and the . Website fingerprinting attacks can reveal the receiver in anonymous networks and cause a potential threat to users' privacy. The state-of-the-art attack based on deep learning can gain over 98% accuracy in Tor. Overall, insights used to develop Var-CNN can be applied to future deep learning based attacks, and substantially reduce the amount of training data needed to perform a successful website fingerprinting attack. Expand. Cybersecurity fingerprinting refers to a set of information that can be used to identify network protocols, operating systems, hardware devices, software among other things. Your story matters. A Critical Evaluation of Website Fingerprinting Attacks Marc Juarez1, Sadia Afroz2, Gunes Acar1, Claudia Diaz1, Rachel Greenstadt3 1KU Leuven, ESAT/COSIC and iMinds, Leuven, Belgium {name.surname}@esat.kuleuven.be 2UC Berkeley sadia.afroz@berkeley.edu 3Drexel University greenie@cs.drexel.edu The latency overhead is above 100% and the bandwidth overhead is at least 40%. Deep Fingerprinting is presented, a new website fingerprinting attack against Tor that leverages a type of deep learning called Convolutional Neural Networks with a sophisticated architecture design and is the only attack that is effective against WTF-PAD with over 90% accuracy. itored website was among the websites visited by Tor clientsatthetimeofavictim'strace.Oursimulations show that combining a WO witha WF attack—which werefertoasaWF+WOattack—significantlyreduces false positives for about half of all website visits and for the vast majority of websites visited over Tor. The privacy of Tor users is, however, threatened by website fingerprinting attacks: passive eavesdroppers can identify the websites visited by a user through applying machine learning techniques to the (encrypted) network traffic between the user and the entrance to the Tor network. Few-Shot Website Fingerprinting Attack Mantun Chen, Yongjun Wang, Zhiquan Qin, Xiatian Zhu This work introduces a novel data augmentation method for few-shot website fingerprinting (WF) attack where only a handful of training samples per website are available for deep learning model optimization. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We present a novel web page fingerprinting attack that is able to defeat several recently proposed defenses against traffic analysis attacks, including the application-level de-fenses HTTPOS [15] and randomized pipelining over Tor [18]. X. Cai, R. Nithyanand, T. Wang, R. Johnson and I. Goldberg. Website Fingerprinting attack and defense codes in Python. By website fingerprinting (WF) technologies, local listeners are enabled to track the specific website visited by users through an investigation of the encrypted traffic between the users and the Tor network entry node. The website fingerprinting attack aims to identify the content (i.e., a webpage accessed by a client) of encrypted and anonymized connections by observing patterns of data flows such as packet size and direction. Identifying the website based solely from the network packets' size and number from anonymized and encrypted network traffic is called website fingerprinting. Regardless of the defense scheme, our attack was able to guess which of 100 web . Such attacks magnify the gap between privacy and security — a client who encrypts her communication traffic may . The current triplet fingerprinting (TF) technique proved the possibility of small sample WF attacks. Some recent work apply deep learning algorithms, however, most of them do not fully exploit the packet timing information. . Website fingerprinting has been recognized as a traffic analysis attack against encrypted traffic induced by anonymity networks (e.g., Tor) and encrypted proxies. Suppose an adversary wants to infer a specified website visiting by users. Unlike the state-of-the-art . Recent research demonstrated the feasibility of website fingerprinting attacks on Tor anonymous networks with only a few samples. Pull requests. Please share how this access benefits you. Highly Influential. Ejeta, TG & Kim, HJ 2017, Website fingerprinting attack on Psiphon and its forensic analysis. Overall, insights used to develop Var-CNN can be applied to future deep learning based attacks, and substantially reduce the amount of training data needed to perform a successful website fingerprinting attack. Some of his main concerns were that the academic papers consider wrong adversary model and the… We use this experimental evaluation to demonstrate the general feasibility of website fingerprinting on encryption data link layer traffic in LTE. Website fingerprinting (WF) is a passive traffic analysis attack that threatens website privacy which poses a great threat to user's privacy and web security. Recent WF attacks on Tor have reached high enough accuracy (up to Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks. A Critical Evaluation of Website Fingerprinting Attacks Marc Juarez1 , Sadia Afroz2 , Gunes Acar1 , Claudia Diaz1 , Rachel Greenstadt3 KU Leuven, ESAT/COSIC and iMinds, Leuven, Belgium {name.surname}@esat.kuleuven.be UC Berkeley sadia.afroz@berkeley.edu Drexel University greenie@cs.drexel.edu ABSTRACT Recent studies on Website Fingerprinting (WF) claim to have found highly effective attacks on . Mohammad Saidur Rahman Rochester Institute of Technology Supervisor: Dr. Matthew Wright Website Fingerprinting (WF) enables an eavesdropper to discover what sites the user is visiting despite the use of a VPN or even the Tor anonymity sys-tem. Previous researchers have demonstrated the effectiveness of WF attacks under a strong Single Page Assumption: the network flow extracted by the adversary belongs to a single web page. The attacker is not attempting to break the encryption algorithm or the anonymity protocol. Recent studies have demonstrated the effectiveness of WF attacks through a large number of experiments. On Realistically Attacking Tor with Website Fingerprinting . Paper. Effective Attacks and Provable Defenses for Website Fingerprinting . However, this is highly unrealistic as a user visits multiple sites at the same time. Deep fingerprinting. A recently conducted analysis sheds new light on website fingerprinting (WF) attacks on Tor. Website fingerprinting attacks allow attackers to determine the websites that users are linked to, by examining the encrypted traffic between the users and the anonymous network portals. We develop a methodology and tools to measure the amount of leaked information about a website. We first present Deep Fingerprinting (DF), a new WF attack based on deep learning, and we evaluate this attack against WTF-PAD and Walkie-Talkie. Code is fairly simple to reproduce as we are only changing the attacks/defenses to work on the one-page setting (2 classes instead of 101). Website Fingerprinting by Power Estimation Based Side-Channel Attacks on Android 7 Yi Qin and Chuan Yue Department of Computer Science Colorado School of Mines Golden, CO, USA 80401 Email: fyiqin, chuanyueg@mines.edu Abstract—Power consumption data on smartphones can be used to infer user information like web browsing activities and location. CCS 2014. Website Fingerprinting at Internet Scale Andriy Panchenko , Fabian Lanze , Andreas Zinneny, Martin Henzez, Jan Pennekamp , Klaus Wehrlez, and Thomas Engel University of Luxembourg (LU), yRheinMain University of Applied Sciences (DE), zRWTH Aachen University (DE) E-mail: ffirstname.lastnameg@uni.lu, yandreas.zinnen@hs-rm.de, zflastnameg@comsys.rwth-aachen.de The website fingerprinting (WF) attack on Tor shows that it is possible to detect which website a user is visiting with high accuracy just by looking at the traffic. "Var-CNN: A Data-Efficient Website Fingerprinting vol. In simulations, our algorithm reduces the accuracy of attacks to 14% with zero latency overhead and about 20% bandwidth overhead. The basic website traffic fingerprinting refers to recognize the web traffic by analyzing the patterns, responses, and packets sent and received in a particular direction- everything despite the . "Var-CNN: A Data-Efficient Website Fingerprinting In the Abstract:Website Fingerprinting (WF) attacks have posed a serious threat to users' privacy, which allow an adversary to infer the anonymous communication content by using traffic analysis. Repository for my research. Previous research methods only concentrate on extracting the overall . Moving beyond earlier WF methods relying on manually-engineered feature representations, more advanced deep learning alternatives demonstrate that learning feature representations . To cite the paper: Website fingerprinting attacks. "While attacks can exceed 95% accuracy when monitoring a . Attacks using (features extracted from) this information to infer the website a user visits are called Website Fingerprinting (WF) attacks. Recent studies have demonstrated that, leveraging machine learning techniques and numerous side-channel. Hackers use fingerprinting as the first step of their attack to gather maximum information about targets. no code yet • 17 Nov 2018. Website Fingerprinting using Traffic Analysis Attacks Salini Selvaraj Kowsalya University of Wisconsin, Madison Abstract. Tor developers were considering two defenses against website fingerprinting that could cut the attack's accuracy in half. The common observations are data traffic traces produced by one visit to a website . in Digital Forensics and Watermarking - 16th International Workshop, IWDW 2017, Proceedings. Please share how this access benefits you. In website fingerprinting (WF) attack, the objective is to detect which website a target user is visiting. This work introduces a novel data augmentation method for few-shot website fingerprinting (WF) attack where only a handful of training samples per website are available for deep learning model optimization. We then build a web site fingerprinting attack that is able to identify whether a victim is visiting a particular web site with over 90% accuracy in our experiments. This shortens the time needed for data collection and lowers the likelihood of having data staleness issues. In order to evaluate the severity of the website fingerprinting attack in reality, we collected the most . Website Fingerprinting using Traffic Analysis Attacks Salini S K . In Website Fingerprinting (WF) attack, a local passive eavesdropper utilizes network flow information to identify which web pages a user is browsing. In this work we investigate these attacks under a different attack model, in which the adversary is capable of running a small amount of unprivileged code on the target user's computer. The One-Page Setting: A Higher Standard for Evaluating Website Fingerprinting Defenses.. CCS 2021. Website fingerprinting (WF) attacks can infer website names from encrypted network traffic when the victim is browsing the website. The goal of a fingerprinting attack is to deanonymize a user and figure out the website that they are visiting, even if the have anonymous routing and encryption of data. A new analysis of website fingerprinting (WF) attacks aimed at the Tor web browser has revealed that it's possible for an adversary to glean a website frequented by a victim, but only in scenarios where the threat actor is interested in a specific subset of the websites visited by users. Website fingerprinting attacks allow a local, passive eavesdropper to determine a client's web activity by leveraging features from her packet sequence. Updated on May 25, 2021. using deep learning to perform Website Fingerprinting (WF) attacks on the Tor anonymity system. However, it is a common scenario . Issues. Citation Bhat, Sanjit et al. Regardless of the defense scheme, our attack was able to guess which of 100 web . USENIX 2014. This is the repository of codes for the paper "Zero-delay Lightweight Defenses against Website Fingerprinting" in USENIX Security 2020. [] Key Method. A website fingerprinting (WF) attack is one where an attacker identifies a user's web browsing information by merely observing that user's network traffic. Poster: Website Fingerprinting Attacks with Timing-based Features using Capsule Networks Payap Sirinam, Mohammad Saidur Rahman, Kantha Girish Gangadhara, Matthew Wright Center for Cybersecurity, Rochester Institute of Technology fpayap.sirinam, saidur.rahman, kantha.gangadharag@mail.rit.edu fmatthew.wrightg@rit.edu It collects network packets generated while a user accesses website, and then uses a series of techniques to discover patterns of network packets to infer the type of website user accesses. Website Fingerprinting attack and defense codes in Python. We introduce a new realistic cover traffic algorithm, based on a user's previous network traffic, to mitigate website fingerprinting attacks. Website Fingerprinting (WF) attacks allow passive network eavesdroppers to use these features to identify the client's destination web page, compromising her privacy. Recent studies have demonstrated that, leveraging machine learning techniques and numerous side-channel. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract—Website fingerprinting attacks allow a local, pas-sive eavesdropper to identify a web browsing client's desti-nation web page by extracting noticeable and unique features from her traffic. 10431 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. This paper presents a novel passive website fingerprinting attack to defeat Tor's anonymity mechanism with a significant improvement in comparison with similar methods. What is Traffic Analysis . A website fingerprinting attack is one way in which to compromise the anonymity provided by Tor, by matching users and the websites that they visit. Our attack is based on a simple model of network behavior and out-performs previously proposed ad hoc attacks. They also neglect the hyperlink transition information, because it induces extra 'noise' to classify the original webpage. This shortens the time needed for data collection and lowers the likelihood of having data staleness issues. Website Fingerprinting Attacks on Tor. Some code used in this paper. The value of timing information to WF has often been discounted in recent works due to the volatility of low-level timing information. T. Wang and I. Goldberg. The DF attack attains over 98% 42-51, 16th . CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): We present a novel web page fingerprinting attack that is able to defeat several recently proposed defenses against traffic analysis attacks, including the application-level de-fenses HTTPOS [15] and randomized pipelining over Tor [18]. We develop a methodology and tools to measure the amount of leaked information about a website. Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks. Citation Bhat, Sanjit et al. Submission history Millions of Internet users rely on The Onion Router (Tor) software for anonymous, untraceable use of the web. A Systematic Approach to Developing and Evaluating Website Fingerprinting Defenses . The only information available to the attacker is the metadata information msrocean/Tik_Tok • • 18 Feb 2019 To further investigate the value of timing information, we perform an information leakage analysis on our proposed handcrafted features. Website Fingerprinting: Attacks and Defenses by Tao Wang A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Computer Science Waterloo, Ontario, Canada, 2015 c Tao Wang 2015 We conducted a website fingerprinting attack in our lab setup of an LTE network and tested different devices on a selection of the 50 most popular websites on the Internet. to leak. Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning The MIT Faculty has made this article openly available. Browser fingerprinting is a powerful method that websites use to collect information about your browser type and version, as well as your operating system, active plugins, time zone, language, screen resolution and various other active settings. In the case of Tor, this attack would take place between the user and the Guard node, or at the Guard node itself. Website fingerprinting (WF) attack stands opposite against privacy protection in using the Internet, even when the content details are encrypted, such as Tor networks. WF is a class of traffic analysis attack that enables an eavesdropper between the client and the first Tor node on her path to identify which websites the client is visiting. A passive local eavesdropper can leverage Website Fingerprinting (WF) to deanonymize the web browsing activity of Tor users. This local passive adversary could The overall idea is to leverage the fact that many web sites The Website fingerprinting has been recognized as a traffic analysis attack against encrypted traffic induced by anonymity networks (e.g., Tor) and encrypted proxies. Previous research on website fingerprinting attacks have focused on visiting one website at a time; the accuracy of the attack is 90%. 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