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2021-06-01
Chen, Zhanhao, Cao, Yinzhi.  2020.  JSKernel: Fortifying JavaScript against Web Concurrency Attacks via a Kernel-Like Structure. 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :64—75.
As portals to the Internet, web browsers constitute prominent targets for attacks. Existing defenses that redefine web APIs typically capture information related to a single JavaScript function. Thus, they fail to defend against the so-called web concurrency attacks that use multiple interleaved functions to trigger a browser vulnerability. In this paper, we propose JSKernel, the first generic framework that introduces a kernel concept into JavaScript to defend against web concurrency attacks. The JavaScript kernel, inspired from operating system concepts, enforces the execution order of JavaScript events and threads to fortify security. We implement a prototype of JSKernel deployable as add-on extensions to three widely used web browsers, namely Google Chrome, Mozilla Firefox, and Microsoft Edge. These open-source extensions are available at (https://github.com/jskernel2019/jskernel) along with a usability demo at (https://jskernel2019.github.io/). Our evaluation shows the prototype to be robust to web concurrency attacks, fast, and backward compatible with legacy websites.
2021-05-20
Usher, Will, Pascucci, Valerio.  2020.  Interactive Visualization of Terascale Data in the Browser: Fact or Fiction? 2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV). :27—36.

Information visualization applications have become ubiquitous, in no small part thanks to the ease of wide distribution and deployment to users enabled by the web browser. Scientific visualization applications, relying on native code libraries and parallel processing, have been less suited to such widespread distribution, as browsers do not provide the required libraries or compute capabilities. In this paper, we revisit this gap in visualization technologies and explore how new web technologies, WebAssembly and WebGPU, can be used to deploy powerful visualization solutions for large-scale scientific data in the browser. In particular, we evaluate the programming effort required to bring scientific visualization applications to the browser through these technologies and assess their competitiveness against classic native solutions. As a main example, we present a new GPU-driven isosurface extraction method for block-compressed data sets, that is suitable for interactive isosurface computation on large volumes in resource-constrained environments, such as the browser. We conclude that web browsers are on the verge of becoming a competitive platform for even the most demanding scientific visualization tasks, such as interactive visualization of isosurfaces from a 1TB DNS simulation. We call on researchers and developers to consider investing in a community software stack to ease use of these upcoming browser features to bring accessible scientific visualization to the browser.

Antonio, Elbren, Fajardo, Arnel, Medina, Ruji.  2020.  Tracking Browser Fingerprint using Rule Based Algorithm. 2020 16th IEEE International Colloquium on Signal Processing Its Applications (CSPA). :225—229.

Browsers collects information for better user experience by allowing JavaScript's and other extensions. Advertiser and other trackers take advantage on this useful information to tracked users across the web from remote devices on the purpose of individual unique identifications the so-called browser fingerprinting. Our work explores the diversity and stability of browser fingerprint by modifying the rule-based algorithm. Browser fingerprint rely only from the gathered data through browser, it is hard to tell that this piece of information still the same when upgrades and or downgrades are happening to any browsers and software's without user consent, which is stability and diversity are the most important usage of generating browser fingerprint. We implemented device fingerprint to identify consenting visitors in our website and evaluate individual devices attributes by calculating entropy of each selected attributes. In this research, it is noted that we emphasize only on data collected through a web browser by employing twenty (20) attributes to identify promising high value information to track how device information evolve and consistent in a period of time, likewise, we manually selected device information for evaluation where we apply the modified rules. Finally, this research is conducted and focused on the devices having the closest configuration and device information to test how devices differ from each other after several days of using on the basis of individual user configurations, this will prove in our study that every device is unique.

Al-madani, Ali Mansour, Gaikwad, Ashok T., Mahale, Vivek, Ahmed, Zeyad A.T..  2020.  Decentralized E-voting system based on Smart Contract by using Blockchain Technology. 2020 International Conference on Smart Innovations in Design, Environment, Management, Planning and Computing (ICSIDEMPC). :176—180.

Nowadays the use of the Internet is growing; E-voting system has been used by different countries because it reduces the cost and the time which used to consumed by using traditional voting. When the voter wants to access the E-voting system through the web application, there are requirements such as a web browser and a server. The voter uses the web browser to reach to a centralized database. The use of a centralized database for the voting system has some security issues such as Data modification through the third party in the network due to the use of the central database system as well as the result of the voting is not shown in real-time. However, this paper aims to provide an E-voting system with high security by using blockchain. Blockchain provides a decentralized model that makes the network Reliable, safe, flexible, and able to support real-time services.

Razaque, Abdul, Frej, Mohamed Ben Haj, Sabyrov, Dauren, Shaikhyn, Aidana, Amsaad, Fathi, Oun, Ahmed.  2020.  Detection of Phishing Websites using Machine Learning. 2020 IEEE Cloud Summit. :103—107.

Phishing sends malicious links or attachments through emails that can perform various functions, including capturing the victim's login credentials or account information. These emails harm the victims, cause money loss, and identity theft. In this paper, we contribute to solving the phishing problem by developing an extension for the Google Chrome web browser. In the development of this feature, we used JavaScript PL. To be able to identify and prevent the fishing attack, a combination of Blacklisting and semantic analysis methods was used. Furthermore, a database for phishing sites is generated, and the text, links, images, and other data on-site are analyzed for pattern recognition. Finally, our proposed solution was tested and compared to existing approaches. The results validate that our proposed method is capable of handling the phishing issue substantially.

Olejnik, Lukasz.  2020.  Shedding light on web privacy impact assessment: A case study of the Ambient Light Sensor API. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :310—313.

As modern web browsers gain new and increasingly powerful features the importance of impact assessments of the new functionality becomes crucial. A web privacy impact assessment of a planned web browser feature, the Ambient Light Sensor API, indicated risks arising from the exposure of overly precise information about the lighting conditions in the user environment. The analysis led to the demonstration of direct risks of leaks of user data, such as the list of visited websites or exfiltration of sensitive content across distinct browser contexts. Our work contributed to the creation of web standards leading to decisions by browser vendors (i.e. obsolescence, non-implementation or modification to the operation of browser features). We highlight the need to consider broad risks when making reviews of new features. We offer practically-driven high-level observations lying on the intersection of web security and privacy risk engineering and modeling, and standardization. We structure our work as a case study from activities spanning over three years.

2021-05-18
Wingerath, Wolfram, Gessert, Felix, Witt, Erik, Kuhlmann, Hannes, Bücklers, Florian, Wollmer, Benjamin, Ritter, Norbert.  2020.  Speed Kit: A Polyglot GDPR-Compliant Approach For Caching Personalized Content. 2020 IEEE 36th International Conference on Data Engineering (ICDE). :1603–1608.
Users leave when page loads take too long. This simple fact has complex implications for virtually all modern businesses, because accelerating content delivery through caching is not as simple as it used to be. As a fundamental technical challenge, the high degree of personalization in today's Web has seemingly outgrown the capabilities of traditional content delivery networks (CDNs) which have been designed for distributing static assets under fixed caching times. As an additional legal challenge for services with personalized content, an increasing number of regional data protection laws constrain the ways in which CDNs can be used in the first place. In this paper, we present Speed Kit as a radically different approach for content distribution that combines (1) a polyglot architecture for efficiently caching personalized content with (2) a natively GDPR-compliant client proxy that handles all sensitive information within the user device. We describe the system design and implementation, explain the custom cache coherence protocol to avoid data staleness and achieve Δ-atomicity, and we share field experiences from over a year of productive use in the e-commerce industry.
2021-04-27
Calzavara, S., Focardi, R., Grimm, N., Maffei, M., Tempesta, M..  2020.  Language-Based Web Session Integrity. 2020 IEEE 33rd Computer Security Foundations Symposium (CSF). :107—122.
Session management is a fundamental component of web applications: despite the apparent simplicity, correctly implementing web sessions is extremely tricky, as witnessed by the large number of existing attacks. This motivated the design of formal methods to rigorously reason about web session security which, however, are not supported at present by suitable automated verification techniques. In this paper we introduce the first security type system that enforces session security on a core model of web applications, focusing in particular on server-side code. We showcase the expressiveness of our type system by analyzing the session management logic of HotCRP, Moodle, and phpMyAdmin, unveiling novel security flaws that have been acknowledged by software developers.
Mane, Y. D., Khot, U. P..  2020.  A Systematic Way to Implement Private Tor Network with Trusted Middle Node. 2020 International Conference for Emerging Technology (INCET). :1—6.

Initially, legitimate users were working under a normal web browser to do all activities over the internet [1]. To get more secure service and to get protection against Bot activity, the legitimate users switched their activity from Normal web browser to low latency anonymous communication such as Tor Browser. The Traffic monitoring in Tor Network is difficult as the packets are traveling from source to destination in an encrypted fashion and the Tor network hides its identity from destination. But lately, even the illegitimate users such as attackers/criminals started their activity on the Tor browser. The secured Tor network makes the detection of Botnet more difficult. The existing tools for botnet detection became inefficient against Tor-based bots because of the features of the Tor browser. As the Tor Browser is highly secure and because of the ethical issues, doing practical experiments on it is not advisable which could affect the performance and functionality of the Tor browser. It may also affect the endanger users in situations where the failure of Tor's anonymity has severe consequences. So, in the proposed research work, Private Tor Networks (PTN) on physical or virtual machines with dedicated resources have been created along with Trusted Middle Node. The motivation behind the trusted middle node is to make the Private Tor network more efficient and to increase its performance.

Hammoud, O. R., Tarkhanov, I. A..  2020.  Blockchain-based open infrastructure for URL filtering in an Internet browser. 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT). :1—4.
This research is dedicated to the development of a prototype of open infrastructure for users’ internet traffic filtering on a browser level. We described the advantages of a distributed approach in comparison with current centralized solutions. Besides, we suggested a solution to define the optimum size for a URL storage block in Ethereum network. This solution may be used for the development of infrastructure of DApps applications on Ethereum network in future. The efficiency of the suggested approach is supported by several experiments.
Korać, D., Damjanović, B., Simić, D..  2020.  Information Security in M-learning Systems: Challenges and Threats of Using Cookies. 2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH). :1—6.
The trend of rapid development of mobile technologies has highlighted new challenges and threats regarding the information security by the using cookies in mobile learning (m-learning) systems. In order to overcome these challenges and threats, this paper has identified two main objectives. First, to give a review of most common types to cookies and second, to consider the challenges and threats regarding cookies with aspects that are directly related to issues of security and privacy. With these objectives is possible to bridge security gaps in m-learning systems. Moreover, the identified potential challenges and threats are discussed with the given proposals of pragmatic solutions for their mitigating or reducing. The findings of this research may help students to rise security awareness and security behavior in m-learning systems, and to better understand on-going security challenges and threats in m-learning systems.
Kondracki, B., Aliyeva, A., Egele, M., Polakis, J., Nikiforakis, N..  2020.  Meddling Middlemen: Empirical Analysis of the Risks of Data-Saving Mobile Browsers. 2020 IEEE Symposium on Security and Privacy (SP). :810—824.
Mobile browsers have become one of the main mediators of our online activities. However, as web pages continue to increase in size and streaming media on-the-go has become commonplace, mobile data plan constraints remain a significant concern for users. As a result, data-saving features can be a differentiating factor when selecting a mobile browser. In this paper, we present a comprehensive exploration of the security and privacy threat that data-saving functionality presents to users. We conduct the first analysis of Android's data-saving browser (DSB) ecosystem across multiple dimensions, including the characteristics of the various browsers' infrastructure, their application and protocol-level behavior, and their effect on users' browsing experience. Our research unequivocally demonstrates that enabling data-saving functionality in major browsers results in significant degradation of the user's security posture by introducing severe vulnerabilities that are not otherwise present in the browser during normal operation. In summary, our experiments show that enabling data savings exposes users to (i) proxy servers running outdated software, (ii) man-in-the-middle attacks due to problematic validation of TLS certificates, (iii) weakened TLS cipher suite selection, (iv) lack of support of security headers like HSTS, and (v) a higher likelihood of being labelled as bots. While the discovered issues can be addressed, we argue that data-saving functionality presents inherent risks in an increasingly-encrypted Web, and users should be alerted of the critical savings-vs-security trade-off that they implicitly accept every time they enable such functionality.
Obaidat, M., Brown, J., Hayajneh, A. A..  2020.  Web Browser Extension User-Script XSS Vulnerabilities. 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech). :316—321.

Browser extensions have by and large become a normal and accepted omnipresent feature within modern browsers. However, since their inception, browser extensions have remained under scrutiny for opening vulnerabilities for users. While a large amount of effort has been dedicated to patching such issues as they arise, including the implementation of extension sandboxes and explicit permissions, issues remain within the browser extension ecosystem through user-scripts. User-scripts, or micro-script extensions hosted by a top-level extension, are largely unregulated but inherit the permissions of the top-level application manager, which popularly includes extensions such as Greasemonkey, Tampermonkey, or xStyle. While most user-scripts are docile and serve a specific beneficial functionality, due to their inherently open nature and the unregulated ecosystem, they are easy for malicious parties to exploit. Common attacks through this method involve hijacking of DOM elements to execute malicious javascript and/or XSS attacks, although other more advanced attacks can be deployed as well. User-scripts have not received much attention, and this vulnerability has persisted despite attempts to make browser extensions more secure. This ongoing vulnerability remains an unknown threat to many users who employ user-scripts, and circumvents security mechanisms otherwise put in place by browsers. This paper discusses this extension derivative vulnerability as it pertains to current browser security paradigms.

2021-03-09
Muslim, A. A., Budiono, A., Almaarif, A..  2020.  Implementation and Analysis of USB based Password Stealer using PowerShell in Google Chrome and Mozilla Firefox. 2020 3rd International Conference on Computer and Informatics Engineering (IC2IE). :421—426.

Along with the development of the Windows operating system, browser applications to surf the internet are also growing rapidly. The most widely used browsers today are Google Chrome and Mozilla Firefox. Both browsers have a username and password management feature that makes users login to a website easily, but saving usernames and passwords in the browser is quite dangerous because the stored data can be hacked using brute force attacks or read through a program. One way to get a username and password in the browser is to use a program that can read Google Chrome and Mozilla Firefox login data from the computer's internal storage and then show those data. In this study, an attack will be carried out by implementing Rubber Ducky using BadUSB to run the ChromePass and PasswordFox program and the PowerShell script using the Arduino Pro Micro Leonardo device as a USB Password Stealer. The results obtained from this study are the username and password on Google Chrome and Mozilla Firefox successfully obtained when the USB is connected to the target device, the average time of the attack is 14 seconds then sending it to the author's email.

2021-03-04
Algehed, M., Flanagan, C..  2020.  Transparent IFC Enforcement: Possibility and (In)Efficiency Results. 2020 IEEE 33rd Computer Security Foundations Symposium (CSF). :65—78.

Information Flow Control (IFC) is a collection of techniques for ensuring a no-write-down no-read-up style security policy known as noninterference. Traditional methods for both static (e.g. type systems) and dynamic (e.g. runtime monitors) IFC suffer from untenable numbers of false alarms on real-world programs. Secure Multi-Execution (SME) promises to provide secure information flow control without modifying the behaviour of already secure programs, a property commonly referred to as transparency. Implementations of SME exist for the web in the form of the FlowFox browser and as plug-ins to several programming languages. Furthermore, SME can in theory work in a black-box manner, meaning that it can be programming language agnostic, making it perfect for securing legacy or third-party systems. As such SME, and its variants like Multiple Facets (MF) and Faceted Secure Multi-Execution (FSME), appear to be a family of panaceas for the security engineer. The question is, how come, given all these advantages, that these techniques are not ubiquitous in practice? The answer lies, partially, in the issue of runtime and memory overhead. SME and its variants are prohibitively expensive to deploy in many non-trivial situations. The natural question is why is this the case? On the surface, the reason is simple. The techniques in the SME family all rely on the idea of multi-execution, running all or parts of a program multiple times to achieve noninterference. Naturally, this causes some overhead. However, the predominant thinking in the IFC community has been that these overheads can be overcome. In this paper we argue that there are fundamental reasons to expect this not to be the case and prove two key theorems: (1) All transparent enforcement is polynomial time equivalent to multi-execution. (2) All black-box enforcement takes time exponential in the number of principals in the security lattice. Our methods also allow us to answer, in the affirmative, an open question about the possibility of secure and transparent enforcement of a security condition known as Termination Insensitive Noninterference.

2021-02-10
Kerschbaumer, C., Ritter, T., Braun, F..  2020.  Hardening Firefox against Injection Attacks. 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :653—663.
Web browsers display content in the form of HTML, CSS and JavaScript retrieved from the world wide web. The loaded content is subject to the web security model and considered untrusted and potentially malicious. To complicate security matters, Firefox uses the same technologies to render its user interface as it does to render untrusted web content which blurs the distinction between the two privilege levels.Getting interactions between the two correct turns out to be complicated and has led to numerous real-world security vulnerabilities. We study those vulnerabilities to discover common threats and explain how we address them systematically to harden Firefox.
Mishra, P., Gupta, C..  2020.  Cookies in a Cross-site scripting: Type, Utilization, Detection, Protection and Remediation. 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). :1056—1059.
In accordance to the annual report by the Cisco 2018, web applications are exposed to several security vulnerabilities that are exploited by hackers in various ways. It is becoming more and more frequent, specific and sophisticated. Of all the vulnerabilities, more than 40% of attempts are performed via cross-site scripting (XSS). A number of methods have been postulated to examine such vulnerabilities. Therefore, this paper attempted to address an overview of one such vulnerability: the cookies in the XSS. The objective is to present an overview of the cookies, it's type, vulnerability, policies, discovering, protecting and their mitigation via different tools/methods and via cryptography, artificial intelligence techniques etc. While some future issues, directions, challenges and future research challenges were also being discussed.
Kishimoto, K., Taniguchi, Y., Iguchi, N..  2020.  A Practical Exercise System Using Virtual Machines for Learning Cross-Site Scripting Countermeasures. 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan). :1—2.

Cross-site scripting (XSS) is an often-occurring major attack that developers should consider when developing web applications. We develop a system that can provide practical exercises for learning how to create web applications that are secure against XSS. Our system utilizes free software and virtual machines, allowing low-cost, safe, and practical exercises. By using two virtual machines as the web server and the attacker host, the learner can conduct exercises demonstrating both XSS countermeasures and XSS attacks. In our system, learners use a web browser to learn and perform exercises related to XSS. Experimental evaluations confirm that the proposed system can support learning of XSS countermeasures.

Romano, A., Zheng, Y., Wang, W..  2020.  MinerRay: Semantics-Aware Analysis for Ever-Evolving Cryptojacking Detection. 2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE). :1129—1140.
Recent advances in web technology have made in-browser crypto-mining a viable funding model. However, these services have been abused to launch large-scale cryptojacking attacks to secretly mine cryptocurrency in browsers. To detect them, various signature-based or runtime feature-based methods have been proposed. However, they can be imprecise or easily circumvented. To this end, we propose MinerRay, a generic scheme to detect malicious in-browser cryptominers. Instead of leveraging unreliable external patterns, MinerRay infers the essence of cryptomining behaviors that differentiate mining from common browser activities in both WebAssembly and JavaScript contexts. Additionally, to detect stealthy mining activities without user consents, MinerRay checks if the miner can only be instantiated from user actions. MinerRay was evaluated on over 1 million websites. It detected cryptominers on 901 websites, where 885 secretly start mining without user consent. Besides, we compared MinerRay with five state-of-the-art signature-based or behavior-based cryptominer detectors (MineSweeper, CMTracker, Outguard, No Coin, and minerBlock). We observed that emerging miners with new signatures or new services were detected by MinerRay but missed by others. The results show that our proposed technique is effective and robust in detecting evolving cryptominers, yielding more true positives, and fewer errors.
Tanana, D., Tanana, G..  2020.  Advanced Behavior-Based Technique for Cryptojacking Malware Detection. 2020 14th International Conference on Signal Processing and Communication Systems (ICSPCS). :1—4.
With rising value and popularity of cryptocurrencies, they inevitably attract cybercriminals seeking illicit profits within blockchain ecosystem. Two of the most popular methods are ransomware and cryptojacking. Ransomware, being the first and more obvious threat has been extensively studied in the past. Unlike that, scientists have often neglected cryptojacking, because it’s less obvious and less harmful than ransomware. In this paper, we’d like to propose enhanced detection program to combat cryptojacking, additionally briefly touching history of cryptojacking, also known as malicious mining and reviewing most notable previous attempts to detect and combat cryptojacking. The review would include out previous work on malicious mining detection and our current detection program is based on its previous iteration, which mostly used CPU usage heuristics to detect cryptojacking. However, we will include additional metrics for malicious mining detection, such as network usage and calls to cryptographic libraries, which result in a 93% detection rate against the selected number of cryptojacking samples, compared to 81% rate achieved in previous work. Finally, we’ll discuss generalization of proposed detection technique to include GPU cryptojackers.
2021-02-03
Lee, J..  2020.  CanvasMirror: Secure Integration of Third-Party Libraries in a WebVR Environment. 2020 50th Annual IEEE-IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S). :75—76.

Web technology has evolved to offer 360-degree immersive browsing experiences. This new technology, called WebVR, enables virtual reality by rendering a three-dimensional world on an HTML canvas. Unfortunately, there exists no browser-supported way of sharing this canvas between different parties. As a result, third-party library providers with ill intent (e.g., stealing sensitive information from end-users) can easily distort the entire WebVR site. To mitigate the new threats posed in WebVR, we propose CanvasMirror, which allows publishers to specify the behaviors of third-party libraries and enforce this specification. We show that CanvasMirror effectively separates the third-party context from the host origin by leveraging the privilege separation technique and safely integrates VR contents on a shared canvas.

2020-09-28
Li, Lin, Wei, Linfeng.  2019.  Automatic XSS Detection and Automatic Anti-Anti-Virus Payload Generation. 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). :71–76.
In the Web 2.0 era, user interaction makes Web application more diverse, but brings threats, among which XSS vulnerability is the common and pernicious one. In order to promote the efficiency of XSS detection, this paper investigates the parameter characteristics of malicious XSS attacks. We identify whether a parameter is malicious or not through detecting user input parameters with SVM algorithm. The original malicious XSS parameters are deformed by DQN algorithm for reinforcement learning for rule-based WAF to be anti-anti-virus. Based on this method, we can identify whether a specific WAF is secure. The above model creates a more efficient automatic XSS detection tool and a more targeted automatic anti-anti-virus payload generation tool. This paper also explores the automatic generation of XSS attack codes with RNN LSTM algorithm.
Lv, Chengcheng, Zhang, Long, Zeng, Fanping, Zhang, Jian.  2019.  Adaptive Random Testing for XSS Vulnerability. 2019 26th Asia-Pacific Software Engineering Conference (APSEC). :63–69.
XSS is one of the common vulnerabilities in web applications. Many black-box testing tools may collect a large number of payloads and traverse them to find a payload that can be successfully injected, but they are not very efficient. And previous research has paid less attention to how to improve the efficiency of black-box testing to detect XSS vulnerability. To improve the efficiency of testing, we develop an XSS testing tool. It collects 6128 payloads and uses a headless browser to detect XSS vulnerability. The tool can discover XSS vulnerability quickly with the ART(Adaptive Random Testing) method. We conduct an experiment using 3 extensively adopted open source vulnerable benchmarks and 2 actual websites to evaluate the ART method. The experimental results indicate that the ART method can effectively improve the fuzzing method by more than 27.1% in reducing the number of attempts before accomplishing a successful injection.
2020-09-11
Shukla, Ankur, Katt, Basel, Nweke, Livinus Obiora.  2019.  Vulnerability Discovery Modelling With Vulnerability Severity. 2019 IEEE Conference on Information and Communication Technology. :1—6.
Web browsers are primary targets of attacks because of their extensive uses and the fact that they interact with sensitive data. Vulnerabilities present in a web browser can pose serious risk to millions of users. Thus, it is pertinent to address these vulnerabilities to provide adequate protection for personally identifiable information. Research done in the past has showed that few vulnerability discovery models (VDMs) highlight the characterization of vulnerability discovery process. In these models, severity which is one of the most crucial properties has not been considered. Vulnerabilities can be categorized into different levels based on their severity. The discovery process of each kind of vulnerabilities is different from the other. Hence, it is essential to incorporate the severity of the vulnerabilities during the modelling of the vulnerability discovery process. This paper proposes a model to assess the vulnerabilities present in the software quantitatively with consideration for the severity of the vulnerabilities. It is possible to apply the proposed model to approximate the number of vulnerabilities along with vulnerability discovery rate, future occurrence of vulnerabilities, risk analysis, etc. Vulnerability data obtained from one of the major web browsers (Google Chrome) is deployed to examine goodness-of-fit and predictive capability of the proposed model. Experimental results justify the fact that the model proposed herein can estimate the required information better than the existing VDMs.
Arvind, S, Narayanan, V Anantha.  2019.  An Overview of Security in CoAP: Attack and Analysis. 2019 5th International Conference on Advanced Computing Communication Systems (ICACCS). :655—660.
Over the last decade, a technology called Internet of Things (IoT) has been evolving at a rapid pace. It enables the development of endless applications in view of availability of affordable components which provide smart ecosystems. The IoT devices are constrained devices which are connected to the internet and perform sensing tasks. Each device is identified by their unique address and also makes use of the Constrained Application Protocol (CoAP) as one of the main web transfer protocols. It is an application layer protocol which does not maintain secure channels to transfer information. For authentication and end-to-end security, Datagram Transport Layer Security (DTLS) is one of the possible approaches to boost the security aspect of CoAP, in addition to which there are many suggested ways to protect the transmission of sensitive information. CoAP uses DTLS as a secure protocol and UDP as a transfer protocol. Therefore, the attacks on UDP or DTLS could be assigned as a CoAP attack. An attack on DTLS could possibly be launched in a single session and a strong authentication mechanism is needed. Man-In-The-Middle attack is one the peak security issues in CoAP as cited by Request For Comments(RFC) 7252, which encompasses attacks like Sniffing, Spoofing, Denial of Service (DoS), Hijacking, Cross-Protocol attacks and other attacks including Replay attacks and Relay attacks. In this work, a client-server architecture is setup, whose end devices communicate using CoAP. Also, a proxy system was installed across the client side to launch an active interception between the client and the server. The work will further be enhanced to provide solutions to mitigate these attacks.