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2022-12-20
Fargose, Rehan, Gaonkar, Samarth, Jadhav, Paras, Jadiya, Harshit, Lopes, Minal.  2022.  Browser Extension For A Safe Browsing Experience. 2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS). :1–6.
Due to the rise of the internet a business model known as online advertising has seen unprecedented success. However, it has also become a prime method through which criminals can scam people. Often times even legitimate websites contain advertisements that are linked to scam websites since they are not verified by the website’s owners. Scammers have become quite creative with their attacks, using various unorthodox and inconspicuous methods such as I-frames, Favicons, Proxy servers, Domains, etc. Many modern Anti-viruses are paid services and hence not a feasible option for most users in 3rd world countries. Often people don’t possess devices that have enough RAM to even run such software efficiently leaving them without any options. This project aims to create a Browser extension that will be able to distinguish between safe and unsafe websites by utilizing Machine Learning algorithms. This system is lightweight and free thus fulfilling the needs of most people looking for a cheap and reliable security solution and allowing people to surf the internet easily and safely. The system will scan all the intermittent URL clicks as well, not just the main website thus providing an even greater degree of security.
Janloy, Kiattisak, Boonyopakorn, Pongsarun.  2022.  The Comparison of Web History Forensic Tools with ISO and NIST Standards. 2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC). :1–4.
Nowadays, the number of new websites in Thailand has been increasing every year. However, there is a lack of security on some of those websites which causes negative effects and damage. This has also resulted in numerous violations. As a result, these violations cause delays in the situation analysis. Additionally, the cost of effective and well-established digital forensics tools is still expensive. Therefore, this paper has presented the idea of using freeware digital forensics tools to test their performances and compare them with the standards of the digital forensics process. The results of the paper suggest that the tested tools have significant differences in functions and process. WEFA Web Forensics tool is the most effective tool as it supports 3 standards up to 8 out of 10 processes, followed by Browser History View which supports 7 processes, Browser History Spy and Browser Forensic Web Tool respectively, supports 5 processes. The Internet history Browser supports 4 processes as compared to the basic process of the standardization related to forensics.
Şimşek, Merve Melis, Ergun, Tamer, Temuçin, Hüseyin.  2022.  SSL Test Suite: SSL Certificate Test Public Key Infrastructure. 2022 30th Signal Processing and Communications Applications Conference (SIU). :1–4.
Today, many internet-based applications, especially e-commerce and banking applications, require the transfer of personal data and sensitive data such as credit card information, and in this process, all operations are carried out over the Internet. Users frequently perform these transactions, which require high security, on web sites they access via web browsers. This makes the browser one of the most basic software on the Internet. The security of the communication between the user and the website is provided with SSL certificates, which is used for server authentication. Certificates issued by Certificate Authorities (CA) that have passed international audits must meet certain conditions. The criteria for the issuance of certificates are defined in the Baseline Requirements (BR) document published by the Certificate Authority/Browser (CA/B) Forum, which is accepted as the authority in the WEB Public Key Infrastructure (WEB PKI) ecosystem. Issuing the certificates in accordance with the defined criteria is not sufficient on its own to establish a secure SSL connection. In order to ensure a secure connection and confirm the identity of the website, the certificate validation task falls to the web browsers with which users interact the most. In this study, a comprehensive SSL certificate public key infrastructure (SSL Test Suite) was established to test the behavior of web browsers against certificates that do not comply with BR requirements. With the designed test suite, it is aimed to analyze the certificate validation behaviors of web browsers effectively.
ISSN: 2165-0608
Hassanshahi, Behnaz, Lee, Hyunjun, Krishnan, Paddy.  2022.  Gelato: Feedback-driven and Guided Security Analysis of Client-side Web Applications. 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). :618–629.
Modern web applications are getting more sophisticated by using frameworks that make development easy, but pose challenges for security analysis tools. New analysis techniques are needed to handle such frameworks that grow in number and popularity. In this paper, we describe Gelato that addresses the most crucial challenges for a security-aware client-side analysis of highly dynamic web applications. In particular, we use a feedback-driven and state-aware crawler that is able to analyze complex framework-based applications automatically, and is guided to maximize coverage of security-sensitive parts of the program. Moreover, we propose a new lightweight client-side taint analysis that outperforms the state-of-the-art tools, requires no modification to browsers, and reports non-trivial taint flows on modern JavaScript applications. Gelato reports vulnerabilities with higher accuracy than existing tools and achieves significantly better coverage on 12 applications of which three are used in production.
ISSN: 1534-5351
von Zezschwitz, Emanuel, Chen, Serena, Stark, Emily.  2022.  "It builds trust with the customers" - Exploring User Perceptions of the Padlock Icon in Browser UI. 2022 IEEE Security and Privacy Workshops (SPW). :44–50.
We performed a large-scale online survey (n=1,880) to study the padlock icon, an established security indicator in web browsers that denotes connection security through HTTPS. In this paper, we evaluate users’ understanding of the padlock icon, and how removing or replacing it might influence their expectations and decisions. We found that the majority of respondents (89%) had misconceptions about the padlock’s meaning. While only a minority (23%-44%) referred to the padlock icon at all when asked to evaluate trustworthiness, these padlock-aware users reported that they would be deterred from a hypothetical shopping transaction when the padlock icon was absent. These users were reassured after seeing secondary UI surfaces (i.e., Chrome Page Info) where more verbose information about connection security was present.We conclude that the padlock icon, displayed by browsers in the address bar, is still misunderstood by many users. The padlock icon guarantees connection security, but is often perceived to indicate the general privacy, security, and trustworthiness of a website. We argue that communicating connection security precisely and clearly is likely to be more effective through secondary UI, where there is more surface area for content. We hope that this paper boosts the discussion about the benefits and drawbacks of showing passive security indicators in the browser UI.
ISSN: 2770-8411
Do, Quoc Huy, Hosseyni, Pedram, Küsters, Ralf, Schmitz, Guido, Wenzler, Nils, Würtele, Tim.  2022.  A Formal Security Analysis of the W3C Web Payment APIs: Attacks and Verification. 2022 IEEE Symposium on Security and Privacy (SP). :215–234.
Payment is an essential part of e-commerce. Merchants usually rely on third-parties, so-called payment processors, who take care of transferring the payment from the customer to the merchant. How a payment processor interacts with the customer and the merchant varies a lot. Each payment processor typically invents its own protocol that has to be integrated into the merchant’s application and provides the user with a new, potentially unknown and confusing user experience.Pushed by major companies, including Apple, Google, Master-card, and Visa, the W3C is currently developing a new set of standards to unify the online checkout process and “streamline the user’s payment experience”. The main idea is to integrate payment as a native functionality into web browsers, referred to as the Web Payment APIs. While this new checkout process will indeed be simple and convenient from an end-user perspective, the technical realization requires rather significant changes to browsers.Many major browsers, such as Chrome, Firefox, Edge, Safari, and Opera, already implement these new standards, and many payment processors, such as Google Pay, Apple Pay, or Stripe, support the use of Web Payment APIs for payments. The ecosystem is constantly growing, meaning that the Web Payment APIs will likely be used by millions of people worldwide.So far, there has been no in-depth security analysis of these new standards. In this paper, we present the first such analysis of the Web Payment APIs standards, a rigorous formal analysis. It is based on the Web Infrastructure Model (WIM), the most comprehensive model of the web infrastructure to date, which, among others, we extend to integrate the new payment functionality into the generic browser model.Our analysis reveals two new critical vulnerabilities that allow a malicious merchant to over-charge an unsuspecting customer. We have verified our attacks using the Chrome implementation and reported these problems to the W3C as well as the Chrome developers, who have acknowledged these problems. Moreover, we propose fixes to the standard, which by now have been adopted by the W3C and Chrome, and prove that the fixed Web Payment APIs indeed satisfy strong security properties.
ISSN: 2375-1207
Van Goethem, Tom, Joosen, Wouter.  2022.  Towards Improving the Deprecation Process of Web Features through Progressive Web Security. 2022 IEEE Security and Privacy Workshops (SPW). :20–30.
To keep up with the continuous modernization of web applications and to facilitate their development, a large number of new features are introduced to the web platform every year. Although new web features typically undergo a security review, issues affecting the privacy and security of users could still surface at a later stage, requiring the deprecation and removal of affected APIs. Furthermore, as the web evolves, so do the expectations in terms of security and privacy, and legacy features might need to be replaced with improved alternatives. Currently, this process of deprecating and removing features is an ad-hoc effort that is largely uncoordinated between the different browser vendors. This causes a discrepancy in terms of compatibility and could eventually lead to the deterrence of the removal of an API, prolonging potential security threats. In this paper we propose a progressive security mechanism that aims to facilitate and standardize the deprecation and removal of features that pose a risk to users’ security, and the introduction of features that aim to provide additional security guarantees.
ISSN: 2770-8411
Hariharan, Meenu, Thakar, Akash, Sharma, Parvesh.  2022.  Forensic Analysis of Private Mode Browsing Artifacts in Portable Web Browsers Using Memory Forensics. 2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS). :1–5.
The popularity of portable web browsers is increasing due to its convenient and compact nature along with the benefit of the data being stored and transferred easily using a USB drive. As technology gets updated frequently, developers are working on web browsers that can be portable in nature with additional security features like private mode browsing, built in ad blockers etc. The increased probability of using portable web browsers for carrying out nefarious activities is a result of cybercriminals with the thought that if they use portable web browsers in private mode it won't leave a digital footprint. Hence, the research paper aims at performing a comparative study of four portable web browsers namely Brave, TOR, Vivaldi, and Maxthon along with various memory acquisition tools to understand the quantity and quality of the data that can be recovered from the memory dump in two different conditions that is when the browser tabs were open and when the browser tabs were closed in a system to aid the forensic investigators.
Siewert, Hendrik, Kretschmer, Martin, Niemietz, Marcus, Somorovsky, Juraj.  2022.  On the Security of Parsing Security-Relevant HTTP Headers in Modern Browsers. 2022 IEEE Security and Privacy Workshops (SPW). :342–352.

Web browsers are among the most important but also complex software solutions to access the web. It is therefore not surprising that web browsers are an attractive target for attackers. Especially in the last decade, security researchers and browser vendors have developed sandboxing mechanisms like security-relevant HTTP headers to tackle the problem of getting a more secure browser. Although the security community is aware of the importance of security-relevant HTTP headers, legacy applications and individual requests from different parties have led to possible insecure configurations of these headers. Even if specific security headers are configured correctly, conflicts in their functionalities may lead to unforeseen browser behaviors and vulnerabilities. Recently, the first work which analyzed duplicated headers and conflicts in headers was published by Calzavara et al. at USENIX Security [1]. The authors focused on inconsistent protections by using both, the HTTP header X-Frame-Options and the framing protection of the Content-Security-Policy.We extend their work by analyzing browser behaviors when parsing duplicated headers, conflicting directives, and values that do not conform to the defined ABNF metalanguage specification. We created an open-source testbed running over 19,800 test cases, at which nearly 300 test cases are executed in the set of 66 different browsers. Our work shows that browsers conform to the specification and behave securely. However, all tested browsers behave differently when it comes, for example, to parsing the Strict-Transport-Security header. Moreover, Chrome, Safari, and Firefox behave differently if the header contains a character, which is not allowed by the defined ABNF. This results in the protection mechanism being fully enforced, partially enforced, or not enforced and thus completely bypassable.

ISSN: 2770-8411

2022-10-13
Cernica, Ionuţ, Popescu, Nirvana.  2020.  Computer Vision Based Framework For Detecting Phishing Webpages. 2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet). :1—4.
One of the most dangerous threats on the internet nowadays is phishing attacks. This type of attack can lead to data breaches, and with it to image and financial loss in a company. The most common technique to exploit this type of attack is by sending emails to the target users to trick them to send their credentials to the attacker servers. If the user clicks on the link from the email, then good detection is needed to protect the user credentials. Many papers presented Computer Vision as a good detection technique, but we will explain why this solution can generate lots of false positives in some important environments. This paper focuses on challenges of the Computer Vision detection technique and proposes a combination of multiple techniques together with Computer Vision technique in order to solve the challenges we have shown. We also will present a methodology to detect phishing attacks that will work with the proposed combination techniques.
Singh, Shweta, Singh, M.P., Pandey, Ramprakash.  2020.  Phishing Detection from URLs Using Deep Learning Approach. 2020 5th International Conference on Computing, Communication and Security (ICCCS). :1—4.
Today, the Internet covers worldwide. All over the world, people prefer an E-commerce platform to buy or sell their products. Therefore, cybercrime has become the center of attraction for cyber attackers in cyberspace. Phishing is one such technique where the unidentified structure of the Internet has been used by attackers/criminals that intend to deceive users with the use of the illusory website and emails for obtaining their credentials (like account numbers, passwords, and PINs). Consequently, the identification of a phishing or legitimate web page is a challenging issue due to its semantic structure. In this paper, a phishing detection system is implemented using deep learning techniques to prevent such attacks. The system works on URLs by applying a convolutional neural network (CNN) to detect the phishing webpage. In paper [19] the proposed model has achieved 97.98% accuracy whereas our proposed system achieved accuracy of 98.00% which is better than earlier model. This system doesn’t require any feature engineering as the CNN extract features from the URLs automatically through its hidden layers. This is other advantage of the proposed system over earlier reported in [19] as the feature engineering is a very time-consuming task.
A.A., Athulya, K., Praveen.  2020.  Towards the Detection of Phishing Attacks. 2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184). :337—343.
Phishing is an act of creating a website similar to a legitimate website with a motive of stealing user's confidential information. Phishing fraud might be the most popular cybercrime. Phishing is one of the risks that originated a couple of years back but still prevailing. This paper discusses various phishing attacks, some of the latest phishing evasion techniques used by attackers and anti-phishing approaches. This review raises awareness of those phishing strategies and helps the user to practice phishing prevention. Here, a hybrid approach of phishing detection also described having fast response time and high accuracy.
2022-08-26
Prakash, Jay, Yu, Clarice Chua Qing, Thombre, Tanvi Ravindra, Bytes, Andrei, Jubur, Mohammed, Saxena, Nitesh, Blessing, Lucienne, Zhou, Jianying, Quek, Tony Q.S.  2021.  Countering Concurrent Login Attacks in “Just Tap” Push-based Authentication: A Redesign and Usability Evaluations. 2021 IEEE European Symposium on Security and Privacy (EuroS&P). :21—36.
In this paper, we highlight a fundamental vulnerability associated with the widely adopted “Just Tap” push-based authentication in the face of a concurrency attack, and propose the method REPLICATE, a redesign to counter this vulnerability. In the concurrency attack, the attacker launches the login session at the same time the user initiates a session, and the user may be fooled, with high likelihood, into accepting the push notification which corresponds to the attacker's session, thinking it is their own. The attack stems from the fact that the login notification is not explicitly mapped to the login session running on the browser in the Just Tap approach. REPLICATE attempts to address this fundamental flaw by having the user approve the login attempt by replicating the information presented on the browser session over to the login notification, such as by moving a key in a particular direction, choosing a particular shape, etc. We report on the design and a systematic usability study of REPLICATE. Even without being aware of the vulnerability, in general, participants placed multiple variants of REPLICATE in competition to the Just Tap and fairly above PIN-based authentication.
2022-08-01
Wiefling, Stephan, Tolsdorf, Jan, Iacono, Luigi Lo.  2021.  Privacy Considerations for Risk-Based Authentication Systems. 2021 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). :320—327.
Risk-based authentication (RBA) extends authentication mechanisms to make them more robust against account takeover attacks, such as those using stolen passwords. RBA is recommended by NIST and NCSC to strengthen password-based authentication, and is already used by major online services. Also, users consider RBA to be more usable than two-factor authentication and just as secure. However, users currently obtain RBA’s high security and usability benefits at the cost of exposing potentially sensitive personal data (e.g., IP address or browser information). This conflicts with user privacy and requires to consider user rights regarding the processing of personal data. We outline potential privacy challenges regarding different attacker models and propose improvements to balance privacy in RBA systems. To estimate the properties of the privacy-preserving RBA enhancements in practical environments, we evaluated a subset of them with long-term data from 780 users of a real-world online service. Our results show the potential to increase privacy in RBA solutions. However, it is limited to certain parameters that should guide RBA design to protect privacy. We outline research directions that need to be considered to achieve a widespread adoption of privacy preserving RBA with high user acceptance.
2022-07-12
Wang, Peiran, Sun, Yuqiang, Huang, Cheng, Du, Yutong, Liang, Genpei, Long, Gang.  2021.  MineDetector: JavaScript Browser-side Cryptomining Detection using Static Methods. 2021 IEEE 24th International Conference on Computational Science and Engineering (CSE). :87—93.
Because of the rise of the Monroe coin, many JavaScript files with embedded malicious code are used to mine cryptocurrency using the computing power of the browser client. This kind of script does not have any obvious behaviors when it is running, so it is difficult for common users to witness them easily. This feature could lead the browser side cryptocurrency mining abused without the user’s permission. Traditional browser security strategies focus on information disclosure and malicious code execution, but not suitable for such scenes. Thus, we present a novel detection method named MineDetector using a machine learning algorithm and static features for automatically detecting browser-side cryptojacking scripts on the websites. MineDetector extracts five static feature groups available from the abstract syntax tree and text of codes and combines them using the machine learning method to build a powerful cryptojacking classifier. In the real experiment, MineDetector achieves the accuracy of 99.41% and the recall of 93.55% and has better performance in time comparing with present dynamic methods. We also made our work user-friendly by developing a browser extension that is click-to-run on the Chrome browser.
2022-01-31
Baumann, Lukas, Heftrig, Elias, Shulman, Haya, Waidner, Michael.  2021.  The Master and Parasite Attack. 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :141—148.
We explore a new type of malicious script attacks: the persistent parasite attack. Persistent parasites are stealthy scripts, which persist for a long time in the browser's cache. We show to infect the caches of victims with parasite scripts via TCP injection. Once the cache is infected, we implement methodologies for propagation of the parasites to other popular domains on the victim client as well as to other caches on the network. We show how to design the parasites so that they stay long time in the victim's cache not restricted to the duration of the user's visit to the web site. We develop covert channels for communication between the attacker and the parasites, which allows the attacker to control which scripts are executed and when, and to exfiltrate private information to the attacker, such as cookies and passwords. We then demonstrate how to leverage the parasites to perform sophisticated attacks, and evaluate the attacks against a range of applications and security mechanisms on popular browsers. Finally we provide recommendations for countermeasures.
Li, Xigao, Azad, Babak Amin, Rahmati, Amir, Nikiforakis, Nick.  2021.  Good Bot, Bad Bot: Characterizing Automated Browsing Activity. 2021 IEEE Symposium on Security and Privacy (SP). :1589—1605.
As the web keeps increasing in size, the number of vulnerable and poorly-managed websites increases commensurately. Attackers rely on armies of malicious bots to discover these vulnerable websites, compromising their servers, and exfiltrating sensitive user data. It is, therefore, crucial for the security of the web to understand the population and behavior of malicious bots.In this paper, we report on the design, implementation, and results of Aristaeus, a system for deploying large numbers of "honeysites", i.e., websites that exist for the sole purpose of attracting and recording bot traffic. Through a seven-month-long experiment with 100 dedicated honeysites, Aristaeus recorded 26.4 million requests sent by more than 287K unique IP addresses, with 76,396 of them belonging to clearly malicious bots. By analyzing the type of requests and payloads that these bots send, we discover that the average honeysite received more than 37K requests each month, with more than 50% of these requests attempting to brute-force credentials, fingerprint the deployed web applications, and exploit large numbers of different vulnerabilities. By comparing the declared identity of these bots with their TLS handshakes and HTTP headers, we uncover that more than 86.2% of bots are claiming to be Mozilla Firefox and Google Chrome, yet are built on simple HTTP libraries and command-line tools.
Kurako, Evgeny, Orlov, Vladimir.  2021.  Threat Comparison for Large-Scale Systems Using Different Browsers. 2021 14th International Conference Management of large-scale system development (MLSD). :1—5.
The main threats in complex networks for large-scale information systems using web browsers or service browsers are analyzed. The necessary security features for these types of systems are compared. The advantages of systems developed with service-browser technology are shown.
Gurjar, Neelam Singh, S R, Sudheendra S, Kumar, Chejarla Santosh, K. S, Krishnaveni.  2021.  WebSecAsst - A Machine Learning based Chrome Extension. 2021 6th International Conference on Communication and Electronics Systems (ICCES). :1631—1635.
A browser extension, also known as a plugin or an addon, is a small software application that adds functionality to a web browser. However, security threats are always linked with such software where data can be compromised and ultimately trust is broken. The proposed research work jas developed a security model named WebSecAsst, which is a chrome plugin relying on the Machine Learning model XGBoost and VirusTotal to detect malicious websites visited by the user and to detect whether the files downloaded from the internet are Malicious or Safe. During this detection, the proposed model preserves the privacy of the user's data to a greater extent than the existing commercial chrome extensions.
Mabe, Abigail, Nelson, Michael L., Weigle, Michele C..  2021.  Extending Chromium: Memento-Aware Browser. 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL). :310—311.
Users rely on their web browser to provide information about the websites they are visiting, such as the security state of the web page their viewing. Current browsers do not differentiate between the live Web and the past Web. If a user loads an archived web page, known as a memento, they have to rely on user interface (UI) elements within the page itself to inform them that the page they are viewing is not the live Web. Memento-awareness extends beyond recognizing a page that has already been archived. The browser should give users the ability to easily archive live web pages as they are browsing. This report presents a proof-of-concept browser that is memento-aware and is created by extending Google's open-source web browser Chromium.
Varshney, Gaurav, Shah, Naman.  2021.  A DNS Security Policy for Timely Detection of Malicious Modification on Webpages. 2021 28th International Conference on Telecommunications (ICT). :1—5.
End users consider the data available through web as unmodified. Even when the web is secured by HTTPS, the data can be tampered in numerous tactical ways reducing trust on the integrity of data at the clients' end. One of the ways in which the web pages can be modified is via client side browser extensions. The extensions can transparently modify the web pages at client's end and can include new data to the web pages with minimal permissions. Clever modifications can be addition of a fake news or a fake advertisement or a link to a phishing website. We have identified through experimentation that such attacks are possible and have potential for serious damages. To prevent and detect such modifications we present a novel domain expressiveness based approach that uses DNS (Domain Name System) TXT records to express the Hash of important web pages that gets verified by the browsers to detect/thwart any modifications to the contents that are launched via client side malicious browser extensions or via cross site scripting. Initial experimentation suggest that the technique has potential to be used and deployed.
Shrestha, Prakash, Saxena, Nitesh, Shukla, Diksha, Phoha, Vir V..  2021.  Press \$@\$@\$\$ to Login: Strong Wearable Second Factor Authentication via Short Memorywise Effortless Typing Gestures. 2021 IEEE European Symposium on Security and Privacy (EuroS P). :71—87.
The use of wearable devices (e.g., smartwatches) in two factor authentication (2FA) is fast emerging, as wearables promise better usability compared to smartphones. Still, the current deployments of wearable 2FA have significant usability and security issues. Specifically, one-time PIN-based wearable 2FA (PIN-2FA) requires noticeable user effort to open the app and copy random PINs from the wearable to the login terminal's (desktop/laptop) browser. An alternative approach, based on one-tap approvals via push notifications (Tap-2FA), relies upon user decision making to thwart attacks and is prone to skip-through. Both approaches are also vulnerable to traditional phishing attacks. To address this security-usability tension, we introduce a fundamentally different design of wearable 2FA, called SG-2FA, involving wrist-movement “seamless gestures” captured near transparently by the second factor wearable device while the user types a very short special sequence on the browser during the login process. The typing of the special sequence creates a wrist gesture that when identified correctly uniquely associates the login attempt with the device's owner. The special sequence can be fixed (e.g., “\$@\$@\$\$”), does not need to be a secret, and does not need to be memorized (could be simply displayed on the browser). This design improves usability over PIN-2FA since only this short sequence has to be typed as part of the login process (no interaction with or diversion of attention to the wearable and copying of random PINs is needed). It also greatly improves security compared to Tap-2FA since the attacker can not succeed in login unless the user's wrist is undergoing the exact same gesture at the exact same time. Moreover, the approach is phishing-resistant and privacy-preserving (unlike behavioral biometrics). Our results show that SG-2FA incurs only minimal errors in both benign and adversarial settings based on appropriate parameterizations.
2022-01-25
Meyer, Fabian, Gehrke, Christian, Schäfer, Michael.  2021.  Evaluating User Acceptance using WebXR for an Augmented Reality Information System. 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). :418—419.
Augmented Reality has a long history and has seen major technical advantages in the last years. With WebXR, a new web standard, Mobile Augmented Reality (MAR) applications are now available in the web browser. With our work, we implemented an Augmented Reality Information System and conducted a case study to evaluate the user acceptance of such an application build with WebXR. Our results indicate that the user acceptance regarding web-based MAR applications for our specific use case seems to be given. With our proposed architecture we also lay the foundation for other AR information systems.
2022-01-10
Takey, Yuvraj Sanjayrao, Tatikayala, Sai Gopal, Samavedam, Satyanadha Sarma, Lakshmi Eswari, P R, Patil, Mahesh Uttam.  2021.  Real Time early Multi Stage Attack Detection. 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). 1:283–290.
In recent times, attackers are continuously developing advanced techniques for evading security, stealing personal financial data, Intellectual Property (IP) and sensitive information. These attacks often employ multiple attack vectors for gaining initial access to the systems. Analysts are often challenged to identify malware objective, initial attack vectors, attack propagation, evading techniques, protective mechanisms and unseen techniques. Most of these attacks are frequently referred to as Multi stage attacks and pose a grave threat to organizations, individuals and the government. Early multistage attack detection is a crucial measure to counter malware and deactivate it. Most traditional security solutions use signature-based detection, which frequently fails to thwart zero-day attacks. Manual analysis of these samples requires enormous effort for effectively counter exponential growth of malware samples. In this paper, we present a novel approach leveraging Machine Learning and MITRE Adversary Tactic Technique and Common knowledge (ATT&CK) framework for early multistage attack detection in real time. Firstly, we have developed a run-time engine that receives notification while malicious executable is downloaded via browser or a launch of a new process in the system. Upon notification, the engine extracts the features from static executable for learning if the executable is malicious. Secondly, we use the MITRE ATT&CK framework, evolved based on the real-world observations of the cyber attacks, that best describes the multistage attack with respect to the adversary Tactics, Techniques and Procedure (TTP) for detecting the malicious executable as well as predict the stages that the malware executes during the attack. Lastly, we propose a real-time system that combines both these techniques for early multistage attack detection. The proposed model has been tested on 6000 unpacked malware samples and it achieves 98 % accuracy. The other major contribution in this paper is identifying the Windows API calls for each of the adversary techniques based on the MITRE ATT&CK.
2021-10-12
Zaeem, Razieh Nokhbeh, Anya, Safa, Issa, Alex, Nimergood, Jake, Rogers, Isabelle, Shah, Vinay, Srivastava, Ayush, Barber, K. Suzanne.  2020.  PrivacyCheck's Machine Learning to Digest Privacy Policies: Competitor Analysis and Usage Patterns. 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). :291–298.
Online privacy policies are lengthy and hard to comprehend. To address this problem, researchers have utilized machine learning (ML) to devise tools that automatically summarize online privacy policies for web users. One such tool is our free and publicly available browser extension, PrivacyCheck. In this paper, we enhance PrivacyCheck by adding a competitor analysis component-a part of PrivacyCheck that recommends other organizations in the same market sector with better privacy policies. We also monitored the usage patterns of about a thousand actual PrivacyCheck users, the first work to track the usage and traffic of an ML-based privacy analysis tool. Results show: (1) there is a good number of privacy policy URLs checked repeatedly by the user base; (2) the users are particularly interested in privacy policies of software services; and (3) PrivacyCheck increased the number of times a user consults privacy policies by 80%. Our work demonstrates the potential of ML-based privacy analysis tools and also sheds light on how these tools are used in practice to give users actionable knowledge they can use to pro-actively protect their privacy.