Artificial Intelligence in Electronic Commerce

Compared to past years the way how the world functions today is very different. This is achieved as a result of several important improvements in the field of technology and internet. These improvements have influenced every aspect of our lives starting from the way we learn, the way we work, the way we travel, the way we shop and a lot of other activities. One of the fields that were drastically changed is the field of business and commerce. The purpose of this paper is to give information about the role and impact of artificial intelligence in electronic business. The readers of the paper will get familiar and gain solid information about the field of artificial intelligence and its implementation in electronic commerce

A Study of Scams and Frauds using Social Engineering in “The Kathmandu Valley” of Nepal

Social Engineering scams are common in Nepal. Coupled with inability of government to enforce policies over technology giants and large swaths of population that are uneducated, social engineering scams and frauds are a real issue. The purpose of the thesis is to find out the extent and impact of social engineering attacks in “The Kathmandu valley” of Nepal. The Kathmandu valley consists of 3 cities including the capital city of Nepal. To conduct the research, the newspaper “The Kathmandu Post” from the year 2019 to 2022 was downloaded and searched for keywords “scam” and “fraud”. After which the results were manually examined to separate news reports of social engineering attacks in Nepal and other countries. Also, a survey was conducted by visiting parks in the Kathmandu valley. A total of 149 people were interviewed to collect data by asking 21 questions regarding social engineering attack faced by the interviewee. Further, literature review of the research papers published related to social engineering and phishing was conducted. The main finding of the thesis was that public awareness program are effective reducing the extent and impact of social engineering attacks in Nepal. The survey suggests large percentage of population have become victims of social engineering attack attempts. More than 70 percent have received messages on WhatsApp regarding fake lottery wins

An Emerging Solution for Detection of Phishing Attacks

In this era of computer age, as more and more people use internet to carry out their day to day work so as hackers performs various security attacks on web browsers and servers to steal user’s vital data. Now Electronic mail (E-mail) is used by everyone including organizations, agency and becoming official communication for the society as a whole in day to day basis. Even though a lot of modern techniques, tools and prevention methods are being developed to secure the users vital information but still they are prone to security attacks by the fraudsters. Phishing is one such attack and its detection with high accuracy is one of the prominent research issues in the area of cyber security. Phisher fraudulently acquire confidential information like user-id, passwords, visa card and master card details through various social engineering methods. Mostly blacklist based methodology is used for detection of phishing attacks but this method has a limitation that it cannot be used for detection of white listed phishing. This chapter aims to use machine learning algorithms to classify between phishing E-mails and genuine E-mails and helps the user in detecting attacks. The architectural model proposed in this chapter is to identify phishing and use J48 decision tree classifier to classify the fake E-mail from real E-mail. The algorithm presented here goes through several stages to identify phishing attack and helps the user in a great way to protect their vital information

FP-Redemption: Studying Browser Fingerprinting Adoption for the Sake of Web Security

International audienceBrowser fingerprinting has established itself as a stateless technique to identify users on the Web. In particular, it is a highly criticized technique to track users. However, we believe that this identification technique can serve more virtuous purposes, such as bot detection or multi-factor authentication. In this paper, we explore the adoption of browser fingerprinting for security-oriented purposes. More specifically, we study 4 types of web pages that require security mechanisms to process user data: sign-up, sign-in, basket and payment pages. We visited 1, 485 pages on 446 domains and we identified the acquisition of browser fingerprints from 405 pages. By using an existing classification technique, we identified 169 distinct browser fingerprinting scripts included in these pages. By investigating the origins of the browser fingerprinting scripts, we identified 12 security-oriented organizations who collect browser fingerprints on sign-up, sign-in, and payment pages. Finally, we assess the effectiveness of browser fingerprinting against two potential attacks, namely stolen credentials and cookie hijacking. We observe browser fingerprinting being successfully used to enhance web security

Hiding in Plain Sight: A Longitudinal Study of Combosquatting Abuse

Domain squatting is a common adversarial practice where attackers register domain names that are purposefully similar to popular domains. In this work, we study a specific type of domain squatting called "combosquatting," in which attackers register domains that combine a popular trademark with one or more phrases (e.g., betterfacebook[.]com, youtube-live[.]com). We perform the first large-scale, empirical study of combosquatting by analyzing more than 468 billion DNS records---collected from passive and active DNS data sources over almost six years. We find that almost 60% of abusive combosquatting domains live for more than 1,000 days, and even worse, we observe increased activity associated with combosquatting year over year. Moreover, we show that combosquatting is used to perform a spectrum of different types of abuse including phishing, social engineering, affiliate abuse, trademark abuse, and even advanced persistent threats. Our results suggest that combosquatting is a real problem that requires increased scrutiny by the security community.Comment: ACM CCS 1

4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022)

Research methods in economics and social sciences are evolving with the increasing availability of Internet and Big Data sources of information. As these sources, methods, and applications become more interdisciplinary, the 4th International Conference on Advanced Research Methods and Analytics (CARMA) is a forum for researchers and practitioners to exchange ideas and advances on how emerging research methods and sources are applied to different fields of social sciences as well as to discuss current and future challenges. Due to the covid pandemic, CARMA 2022 is planned as a virtual and face-to-face conference, simultaneouslyDoménech I De Soria, J.; Vicente Cuervo, MR. (2022). 4th. International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. https://doi.org/10.4995/CARMA2022.2022.1595

Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites

Dark patterns are user interface design choices that benefit an online service by coercing, steering, or deceiving users into making unintended and potentially harmful decisions. We present automated techniques that enable experts to identify dark patterns on a large set of websites. Using these techniques, we study shopping websites, which often use dark patterns to influence users into making more purchases or disclosing more information than they would otherwise. Analyzing ~53K product pages from ~11K shopping websites, we discover 1,818 dark pattern instances, together representing 15 types and 7 broader categories. We examine these dark patterns for deceptive practices, and find 183 websites that engage in such practices. We also uncover 22 third-party entities that offer dark patterns as a turnkey solution. Finally, we develop a taxonomy of dark pattern characteristics that describes the underlying influence of the dark patterns and their potential harm on user decision-making. Based on our findings, we make recommendations for stakeholders including researchers and regulators to study, mitigate, and minimize the use of these patterns.Comment: 32 pages, 11 figures, ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2019

ONLINE PLATFORMS AND HOW TO REGULATE THEM: AN EU OVERVIEW. Bertelsmann Stiftung Policy Paper No. 227 14 June 2018

The rapid rise of online market places such as Amazon, peer-to-peer platforms like Uber, social networks and other forms of online platforms has characterized the digital transformation of the last decade. These online platforms now play a key role in today’s economy and the functioning and governance of the internet. They have brought real benefits for consumers and businesses in the EU by giving them easier access to products and services and facilitating transactions between them. At the same time, their meteoric growth has caused concerns about market dominance and the widening information and power asymmetry between platforms and citizens, businesses and regulators alike. Online platforms, moreover, challenge the regulatory framework of the Single Market. These challenges often culminate in the call for more “platform regulation” at European level. The aim of this paper is to shed light on these challenges and the European debate on platform regulation. In particular, it seeks to 1.) Provide an overview of existing regulation of online platforms in the Single Market; 2.) Examine current regulatory challenges for the platform economy in the EU; and 3.) Propose guidelines for the future European debate on platform regulation