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1.
International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4620 Phishing Web Site Pratiksha Yewale1, Prajkata jadhav2, Prajkta Zende3 , Dhanashree Nikalje4 Diploma. Student, Department of Computer Engineering, AISSMS Engineering College, pune, India1 Associate Professor, Department of Computer Engineering, AISSMS Engineering College, pune , India2 ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - The number of phishing attacks against web services has seen a steady increase causing, for example, a negative effect on the ability of banking and financial institutions to deliver reliable services on the Internet. This paper presents Associate in Nursing automatic approach detecting phishing attacks. Our approach combines a customized whitelisting approach with machine learning techniques. The whitelist is used as filter that blocks phish web pages used to imitate innocuous user behavior. The phishing pages that are not blocked by the whitelist pass are further filtered using a Support Vector Machine classifier designed and optimized to classify these threats. Our experimental results show that the proposed approach improves over the current state-of the- art methods. Key Words: Phishing, sensitive information, whitelist, Machine learning, Support Vector Machine. 1. INTRODUCTION According to the Anti-Phishing Working Group (APWG), phishing is a criminal mechanism employing both social engineering and technical subterfuge to steal consumers âpersonal identification data, including financial account credentials.Usually,phisherstrickuserswithspoofede-mails which appear to be from a trusted source such as a bank or a Reputable commerce agency. There are two main classes of phishing attacks malware based phishing and deceptive phishing. Malware-based phishing methods installmalicious software by exploiting security holes in the userâs system. This software then records confidential and sensitive data and relays it to the phisher. In deceptive phishing an attacker sends misleading e-mails Which appear to come from trusted sources? These e-mails Invite users to access a web link leading to a fake web Site carefully designed to trick users into divulging targeted Sensitive data. The phisher in this type of attack uses several Techniques to dupe the user and Berthold et al. Classified these approaches according to the followingtypes: âą Social engineering, which includes all methods and scenarios Invented by phishers to create a convincing context. âą Imitation, which consists of forging websites that look Like legitimate ones. âą E-mail spoofing, which allows a phisher to spoof the Source address of an e-mail. URL hiding, which enables phishers to mask the URL to which a user is redirected? 1.1 Sub Heading In recent years, the boundaries between e-commerce and social networking have more blurred. Mane-commerce websites support the mechanism of social login where users can check in the websites victimization their social network identities such as their Facebook or Twitter accounts. Users can also post their new purchased products on micro blogs with links to the e-commerce product websites. In this project we have a tendency to propose a unique resolution for cross-site cold-start product suggestion that aims to recommend products from e-commerce websites to users at social networking sites in âcold-startâ situations, problem which has rarely been explored before. 1.2 Sub Heading A major challenge is a way to leverage knowledge extracted from social networking sites forcross-sitecold-startproduct recommendation. We propose to use the joined users across social networking sites and e-commerce websitesasabridge to map usersâ social networking features to another feature representation for product recommendation. Experimental results on a large dataset constructed from the biggest Chinese micro blogging service SINA WEIBO and therefore the largest ChineseB2Ce-commercewebsiteJINGDONGhave shown the effectiveness of our proposed framework. 2. HEADING Phishingattacks are an extremelycommonattackvectorthat has been used for many years, and the potential impacts and risk involved are well known to most Internet users. However, it is still a highly relevant attack vector being used in the wild, poignant many victims. How willasecuritythreat continue to have a significant impact, despite the fact that many internet users know about the risks and potential impact? We dive deeper into several recent phishing scams and provide insights into the modern phishing scam landscape and what makes these campaigns effective â and thus a continuously dangerous security threat. Negative campaigns (see Figure 1) activate the victimâs negative feelings â such as fear, uncertainty, and doubt â making them highly effective, but additionally triggering
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International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4621 defensive impulses in some cases. In contrast, âpositiveâ campaigns highlight feelingsof pleasure,hope,andgratitude, and are gaining momentum.As âpositiveâcampaignsinteract with victimsâ positive feelings, they are frequently combined with elements of social networks, making these campaigns much more effective. We area unit seeing growing momentum in the threat landscape of attacks that square measure starting to include elements of diversion, social networks, and prize winning. All of these elements serve the threat actorâs main goal: to gain the userâs trust and lead victims to divulge sensitive information. This trust is also used to spread the phishing campaign, by group action steps that require the target to share the content via the targetâs social network,therebyincreasingthecampaignâsimpactand distribution. On broaderperspectivephishingattackscanbeclassifiedinto two categories: social engineering or deceptive phishing and malware-based phishingattacks.Socialengineeringphishing attacks generally engage psychological exploitation of users or tricking company employees into handing over their private data. [14â16] These attacks occurs through fake emails, which seems legitimate otherwise or some other social platforms that appeals to certain emotions in the victim, where victim ends up in click a malicious link, or releasing sensitive information, The users withlesstechnical expertise fell easily for social engineering attacks, so endeavors must put efforts to educate employees against these attacks, in order to staytwo steps ahead of hackersand prevent these attacks from succeeding Similarly, malware- based phishing engages running malicious software or unnecessary programs on the userâs machine Fig -1: Sample Image Negative campaigns (see Figure 1) activate the victimâs negative feelings â such as fear, uncertainty, and doubt â making them highly effective, but additionally triggering defensive impulses in some cases. In contrast, âpositiveâ campaigns highlight feelingsof pleasure,hope,andgratitude, and are gaining momentum.As âpositiveâcampaignsinteract with victimsâ positive feelings, they are frequently combined with elements of social networks, making these campaigns much more effective. We area unit seeing growing momentum in the threat landscape of attacks that square measure starting to include elements of diversion, social networks, and prize winning. All of these elements serve the threat actorâs main goal: to gain the userâs trust and lead victims to divulge sensitive information. This trust is also used to spread the phishing campaign, by group action steps that require the target to share the content via the targetâs social network,therebyincreasingthecampaignâsimpactand distribution. On broaderperspectivephishingattackscanbeclassifiedinto two categories: social engineering or deceptive phishing and malware-based phishingattacks.Socialengineeringphishing attacks generally engage psychological exploitation of users or tricking company employees into handing over their private data. [14â16] These attacks occurs through fake emails, which seems legitimate otherwise or some other social platforms that appeals to certain emotions in the victim, where victim ends up in click a malicious link, or releasing sensitive information, The users withlesstechnical expertise fell easily for social engineering attacks, so endeavors must put efforts to educate employees against these attacks, in order to staytwo steps ahead of hackersand prevent these attacks from succeeding Similarly, malware- based phishing engages running malicious software or unnecessary programs on the userâs machine. Conclusion It has been approximately 20 years since the phishing problem was acknowledged. But, still it is used to steal personal Himani Thakur et al, International Journal of Advanced Research in Computer Science, 7 (4)July-August2016,64-68 © 2015-19, IJARCS All Rights Reserved 67 information, online documentations and credit card details. There are diverse solutions offered, but whenever a resultis proposed to overcome these attacks, phishers come up with the vulnerabilities of that solution to maintain with such an attack. Phishing attacks can be classified generally into two categories: Social engineering, which refers to obtaining userâs testimonial using emails or fake websites, and malware attacks, which use malicious code or software to obtain the data required. There are several approaches to shield the user from email and website phishing and were examined in this document.The appraisal helps new researchers to identify with the history, current inclinations of attacks and failure of variousaccessiblesolutions.Defense
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International Research Journal
of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 4622 against phishing attacks is one ofthehardestconfrontsfaced by the network security these days. REFERENCES [1] The Phishing Guide Understanding & Preventing Phishing Attacks By: Gunter Ollmann, Director of Security Strategy, IBM Internet Security Systems, 2007 [2] Phishing: Cutting the Identity Theft Line Published by Wiley Publishing, Inc. 10475 Crosspoint Boulevard Indianapolis, IN 46256 www.wiley.com, 2005, Rachael Lininger and Russell Dean Vines [3] Anti-Phishing Working Group (APWG), ââPhishing activity trends reportâfirst quarter 2013.dsreportq12013.pd f, accessed September 2014 [4] Aloul F (2010) The need for effective information security awareness. Int J Intell ComputRes1(3):176â183[5] James L (2005) [5] Phishing exposed. Syngress Publishing, Burlington 6. Anti-Phishing Working Group (APWG) (2015) Phishing activity trends report- fourth quarter 2015 . [6] Anti-Phishing Working Group (APWG) (2014) Phishing activity trends reportâfirst quarter 2014. Accessed Sept 2014 [7] Anti-Phishing Working Group (APWG) (2014) Phishing activity trends reportâfourth quarter 2013. Accessed Sept 2014 [8] Anti-Phishing Working Group (APWG) (2014) Phishing activity trends reportâsecond quarter 2013. [9] Anti-Phishing Working Group (APWG) (2014) Global Phishing Surveyâsecond half 2013. [10] IT Business Edge (2014) Spear phishing, targeted attacks and data breach trends. [11] Pierluigi Paganini (2014) Phishing: a very dangerous cyber threat [12] Krebs B (2014) HBGary federal hacked by anonymous. [13] eCrime Trends Report: Fourth Quarter (2013) http://Internetidentity.com/resource-tags/quarterly- ecrimereports/. Accessed Sept 2014 [14] Jakobsson M, Myers S (2007) Phishing & countermeasures:understanding the increasing problem of electronic identity theft. Wiley, New York [15] Sheng S, Magnien B, Kumaraguru P, Acquisti A, Cranor LF, Hong J, Nunge E (2007) Anti-phishing phil: the design and evaluation of a game that teaches people not to fall for phish. In: Proceedings of the SOUPS, Pittsburg, pp 88â99
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