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Abstract: The Deep Web is about the web content that is invisible to public and not indexed by search engines. The purpose of the Deep Web is to ensure the privacy and anonymity of web publishers who want to remain anonymous and untraceable. A popular method to create a Deep Web is to host web content on a private network that is secret and restricted. Tor short for The Onion Router is a private Deep Web network that is accessible only by using a special web browser called the Tor browser. It uses special non-standard communication protocols to provide anonymity between its users and websites. Although the Tor network delivers exceptional capabilities in protecting the privacy of data and their publishers, the fact that it is free, open-source and accessible can raise suspicions that confidential, sometimes illicit data exist. Moreover, the Tor traffic can be easily blocked and its nodes blacklisted. This paper proposes an innovative method for building Deep Web networks on the public World Wide Web using Steganography. In a nutshell, the method uses a steganography algorithm to hide secret web content into a benign carrier image that is hosted on a carrier website on the public domain. When using a regular browser, the carrier website displays the benign carrier image. However, when a special proprietary browser is used, the secret web page is displayed. Experiments proved that the proposed method is plausible and can be implemented. Likewise, results showed that the entire process is seamless and transparent as a particular web content can simultaneously be part of the Deep Web and the Surface Web while drawing no suspicions whatsoever regarding the existence of any secret data. As future work, more advanced steganography algorithms are to be studied and developed in an attempt to provide an irreversible yet reliable algorithm.

Keywords: Deep Web, Dark Net, Steganography, Tor 

References:

1. Bin Zhou, Jian Pei, WoShun Luk, "A brief survey on anonymization techniques for privacy preserving publishing of social network data", ACM SIGKDD Explorations Newsletter, vol. 10, no. 2, pp. 12–22, 2008.
2. Devine, Jane, Egger-Sider, Francine, "Beyond Google: the invisible web in the academic library", The Journal of Academic Librarianship, vol. 30, no. 4, pp. 265–269, 2004.
3. Gayard, Laurent, "Darknet: Geopolitics and Uses. Hoboken, NJ: John Wiley & Sons", 2018, ISBN 9781786302021.
4. Senker, Cath, "Cybercrime & the Dark Net: Revealing the hidden underworld of the internet", London: Arcturus Publishing, 2016, ISBN 9781784285555
5. "Sealed Complaint 13 MAG 2328: United States of America v. Ross William Ulbricht", p. 6, retrieved January 2014.
6. Peter Wayner, “Disappearing cryptography: information hiding: steganography & watermarking”, 3rd Edition, Morgan Kaufmann Publishers, 2009.
7. Dong, Y., Li, Q., "A deep Web crawling approach based on query harvest model", Journal of Computer Information System, vol. 8, no. 3, pp.973-981, 2012.
8. Michael Bergman, "The Deep Web: Surfacing Hidden Value", The Journal of Electronic Publishing (JEP), vol 7, no. 1, 2000.
9. Wood, Jessica, "The Darknet: A Digital Copyright Revolution", Richmond Journal of Law and Technology, vol. 16, no. 4, pp. 15–17, 2010.
10. "Tor Project: FAQ", www.torproject.org, retrieved 25 Dec 2018.
11. Oppliger, Rolf, "Privacy protection and anonymity services for the World Wide Web". Future Generation Computer Systems, vol. 16, no. 4, pp. 379–391, 2000.
12. G. Reed, P.F. Syverson, D.M. Goldschlag, "Anonymous connections and onion routing", IEEE Journal on Selected Areas in Communications, vol. 16, n. 4, 1998.
13. Youssef Bassil, "Steganography & the Art of Deception: A Comprehensive Survey", Int. J Latest Trends Computing, vol. 4, no. 3, 2013.
14. Youssef Bassil, "An Image Steganography Scheme using Randomized Algorithm and Context-Free Grammar", Journal of Advanced Computer Science and Technology, vol. 1, issue. 4, pp. 291-305, 2012.
15. K. Jain, “Fundamentals of Digital Image Processing”, Englewood Cliffs publications, Prentice-Hall, 1989.
16. Charles Petzold, “Programming Microsoft Windows with C#”, Microsoft Press, 2002.

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Abstract: In the context of IT development, and with the growth of cyber crime, the IT experts still looking to improve techniques and investigative tools to defend against cyber crime. To achieve our objectives and in order to produce a better solution dedicated to make the forensics techniques and tools accessible to everyone to defend well against cyber crime, we will first present the world of forensics, define the steps necessary for an investigation, examine tow of the most popular solution SIFT and DEFT, model the process they use, and set a benchmark to produce our solution. The proposed solution is in the direction of specialization and is designed to facilitate access to these techniques and tools to improve the methodology used in the investigation to defend against cyber crime.

Keywords: Forensics, Digital Forensics, Forensic Appliance, Forensics tools, Forensics Techniques.

References:

1. Karen Kent, Suzanne Chevalier, Tim Grance, Hung Dang, Guide to Integrating Forensic Techniques into Incident Response, August 2006
2. Muhammad Sharjeel  Zareen,  Adeela  Waqar,  and  Baber  Aslam,  Digital  Forensics: Latest  Challenges and Response, 2013
3. Yunus Yusoff, Roslan Ismail and Zainuddin Hassan, Common Phases of Computer Forensics Investigation Models, June 2011
4. Sabah Al-Fedaghi and Bashayer Al-Babtain, Modeling the Forensics Process, October 2012
5. Mark Pollitt, The key to forensic success: examination planning is a key determinant of efficient and effective digital forensics,
6. Advances in Digital Forensics (Mark Pollitt, February 13-16, 2005)

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