Encyclopedia of Criminal Activities and the Deep Web
Countries all over the world are seeing significant increases in criminal activity through the use of technological tools. Such crimes as identity theft, cyberattacks, drug trafficking, and human trafficking are conducted through the deep and dark web, while social media is utilized by murderers, sex offenders, and pedophiles to elicit information and contact their victims. As criminals continue to harness technology to their advantage, law enforcement and government officials are left to devise alternative strategies to learn more about all aspects of these modern criminal patterns and behavior, to preserve the safety of society, and to ensure that proper justice is served. Regrettably, the lack of adequate research findings on these modern criminal activities is limiting everyone’s abilities to devise effective strategies and programs to combat these modern technology-related criminal activities.
In an effort to compile the most current research on this topic, a new major reference work titled Encyclopedia of Criminal Activities and the Deep Web is currently being developed. This comprehensive Encyclopedia is projected to encompass expert insights about the nature of these criminal activities, how they are conducted, and societal and technological limitations. It will also explore new methods and processes for monitoring and regulating the use of these tools, such as social media, online forums, and online ads, as well as hidden areas of the internet including the deep and dark web. Additionally, this Encyclopedia seeks to offer strategies for predicting and preventing criminals from using technology as a means to track, stalk, and lure their victims.
You are cordially invited to share your research to be featured in this Encyclopedia by submitting a chapter proposal/abstract using the link on the formal call for papers page here. If your chapter proposal is accepted, guidelines for preparing your full chapter submission (which should be between 5,000-7,500 total words in length) can be accessed at: http://www.igi-global.com/publish/contributor-resources/ (under the “For Authors” heading – “Encyclopedia Chapter Organization and Formatting”).
Recommended topics for papers include, but are not limited to:
Bitcoin and Crime
Botnets and Crime
Child Exploitation
Contract Killing
Criminology
Cryptocurrency
Cyber Espionage
Cyber Stalking
Cybercrime
Cybercriminals
Cybersecurity Legislation
Cyberterrorism Fraud
Dark Web
Dark Web Vendors
Darknets
Data Privacy
Dating Websites and Crime
Deep Web
Drug Trafficking
E-Banking Fraud
Email Scams
Fraud and Internet
Gaming and Crime
Government Regulations of the Dark Web
Hacking and Crime
Hacktivism
Human Trafficking
Identity Theft
International Regulations of the Dark Web
Internet Privacy
Internet Regulations
Internet Safety & Crime
Online Advertisement Websites and Crime
Online Blackmail
Online Forums and Crime
Online Hate Crimes
Online Predators
Online Privacy
Social Media Deception
Social Networking Traps
Undercover Dark Web Busts
Undercover Operations
Vigilante Justice
Virtual Currencies & Crime
Whistleblowing
IMPORTANT DATES: Chapter Proposal Submission Deadline: October 15, 2018; Full Chapters Due: December 15, 2018
Note: There are no publication fees, however, contributors will be requested to provide a courtesy to their fellow colleagues by serving as a peer reviewer for this project for at least 2-3 articles. This will ensure the highest level of integrity and quality for the publication.
Should you have any questions regarding this publication, or this invitation, please do not hesitate to contact: EncyclopediaCADW@igi-global.com
Mehdi Khosrow-Pour, DBA Editor-in-Chief Encyclopedia of Criminal Activities and the Deep Web EncyclopediaCADW@igi-global.com
When: Friday, September 28, 8:30am-3:00pm Where: Wilson Research Collaboration Studio, Wilson Library Cost: Free; advanced registration is required
1968 was one of the most turbulent years of the 20th century. 2018 marks the 50th anniversary of that year’s landmark political, social and cultural events–events that continue to influence our world today.
Focusing on the importance of this 50 year anniversary we are calling out to all faculty, staff, students, and community partners to participate the workshop ‘Mapping 1968, Conflict and Change’. This all-day event is designed to bring people together into working groups based on common themes. Bring your talent and curiosity to apply an interdisciplinary approach to further explore the spatial context of these historic and/or current events. Learn new skills on mapping techniques that can be applied to any time in history. To compliment the expertise that you bring to the workshop, working groups will also have the support of library, mapping, and data science experts to help gather, create, and organize the spatial components of a given topic.
Workshop sponsors: Institute for Advanced Studies (IAS), U-Spatial, Liberal Arts Technologies & Innovation Services (LATIS), Digital Arts, Science & Humanities (DASH), and UMN Libraries.
Henneping County scanned the deeds, OCR, Python script to search. Data in an open source. covenant data. Local historian found microfishes, the language from the initial data. e.g. eugenics flavor: arian, truncate.
storymaps.arcgis.com/en/gallery https://storymaps.arcgis.com/en/gallery/#s=0 cloud-based mapping software. ArcGIS Online. organizational account for the U, 600 users. over 700 storymaps creates within the U, some of them are not active, share all kind of data: archive data on spreadsheet, but also a whole set of data within the software; so add the data or use the ArcGIS data and use templates. web maps into the storymap app, Living Atlas: curated set of data: hunderd sets of data, from sat images, to different contents. 846 layers of data, imagery, besides org account, one can create maps within the free account with limited access. data browser to use my own data – Data Enrichment to characterized my data. census data from 2018 and before,
make plan, create a storyboard, writing for the web, short and precise (not as writing for a journal), cartographic style, copyright, citing the materials, choosing the right map scale for each page. online learning materials, some only thru org account ESRI academy has course catalogue. Mapping 101, Dekstop GIS 101, Collector 101, Imagery 101, SQL 101, Story Maps 101,
The “Mapping 1968, Conflict and Change” planning committee is very pleased with the amount of interest and the wonderful attendance at Friday’s gathering. Thank you for attending and actively participating in this interdisciplinary workshop!
To re-cap and learn more on your thoughts and expectations of the workshop we would be grateful if you can take a few moments to complete the workshop evaluation. Please complete the evaluation even if you were unable to attend last Friday, there are questions regarding continued communication and the possibility for future events of this kind.
Artificial intelligence (AI) and machine learning are no longer fantastical prospects seen only in science fiction. Products like Amazon Echo and Siri have brought AI into many homes,
Kelly Calhoun Williams, an education analyst for the technology research firm Gartner Inc., cautions there is a clear gap between the promise of AI and the reality of AI.
Artificial intelligence is a broad term used to describe any technology that emulates human intelligence, such as by understanding complex information, drawing its own conclusions and engaging in natural dialog with people.
Machine learning is a subset of AI in which the software can learn or adapt like a human can. Essentially, it analyzes huge amounts of data and looks for patterns in order to classify information or make predictions. The addition of a feedback loop allows the software to “learn” as it goes by modifying its approach based on whether the conclusions it draws are right or wrong.
AI can process far more information than a human can, and it can perform tasks much faster and with more accuracy. Some curriculum software developers have begun harnessing these capabilities to create programs that can adapt to each student’s unique circumstances.
For instance, a Seattle-based nonprofit company calledEnlearn has developed an adaptive learning platform that uses machine learning technology to create highly individualized learning paths that can accelerate learning for every student. (My note: about learning and technology, Alfie Kohn in https://blog.stcloudstate.edu/ims/2018/09/11/educational-technology/)
GoGuardian, a Los Angeles company, uses machine learning technology to improve the accuracy of its cloud-based Internet filtering and monitoring software for Chromebooks. (My note: that smells Big Brother).Instead of blocking students’ access to questionable material based on a website’s address or domain name, GoGuardian’s software uses AI to analyze the actual content of a page in real time to determine whether it’s appropriate for students. (my note: privacy)
serious privacy concerns. It requires an increased focus not only on data quality and accuracy, but also on the responsible stewardship of this information. “School leaders need to get ready for AI from a policy standpoint,” Calhoun Williams said. For instance: What steps will administrators take to secure student data and ensure the privacy of this information?
70 percent of teens now say they use social media more than once a day, compared to 34 percent of teens in 2012.
Snapchat is now the most popular social media platform among teens, with 41 percent saying it’s the one use most frequently.
35 percent of teens now say texting is their preferred mode of communication with friends, more than the 32 percent who prefer in-person communication. In 2012, 49 percent of teens preferred in-person communication.
One-fourth of teens say using social media makes them feel less lonely, compared to 3 percent who say it makes them feel more lonely.
Nearly three-fourths of teens believe tech companies manipulate them to get them to spend more time on their devices and platforms.
Back in 2012, Facebook dominated the landscape, and social media was something for teens to periodically check in on.
In 2018, though, “social media” is no longer a monolith. Teens now communicate, express themselves, share experiences and ideas, rant, gossip, flirt, plan, and stay on top of current events using a mix of platforms that compete ferociously for their attention.
Sixty-three percent of teens say they use Snapchat, and 41 percent say it’s the platform they use most frequently.
Instagram, meanwhile, is used by 61 percent of teens.
And Facebook’s decline among teens has been “precipitous,” according to the new report. Just 15 percent of teens now say Facebook is their main social media site, down from 68 percent six years ago
But the rationale that I find most disturbing—despite, or perhaps because of, the fact that it’s rarely made explicit—is the idea that technology will increase our efficiency…at teaching the same way that children have been taught for a very long time. Perhaps it hasn’t escaped your notice that ed tech is passionately embraced by very traditional schools: Their institutional pulse quickens over whatever is cutting-edge: instruction that’s blended, flipped, digitally personalized.
We can’t answer the question “Is tech useful in schools?” until we’ve grappled with a deeper question: “What kinds of learning should be taking place in those schools?”
Tarting up a lecture with a SmartBoard, loading a textbook on an iPad, looking up facts online, rehearsing skills with an “adaptive learning system,” writing answers to the teacher’s (or workbook’s) questions and uploading them to Google Docs—these are examples of how technology may make the process a bit more efficient or less dreary but does nothing to challenge the outdated pedagogy. To the contrary: These are shiny things that distract us from rethinking our approach to learning and reassure us that we’re already being innovative.
putting grades online (thereby increasing their salience and their damaging effects), using computers to administer tests and score essays, and setting up “embedded” assessment that’s marketed as “competency-based.” (If your instinct is to ask “What sort of competency? Isn’t that just warmed-over behaviorism?”
But as I argued not long ago, we shouldn’t confuse personalized learning with personal learning. The first involves adjusting the difficulty level of prefabricated skills-based exercises based on students’ test scores, and it requires the purchase of software. The second involves working with each student to create projects of intellectual discovery that reflect his or her unique needs and interests, and it requires the presence of a caring teacher who knows each child well.a recent review found that studies of tech-based personalized instruction “show mixed results ranging from modest impacts to no impact” – despite the fact that it’s remarkably expensive.
an article in Education Week, “a host of national and regional surveys suggest that teachers are far more likely to use tech to make their own jobs easier and to supplement traditional instructional strategies than to put students in control of their own learning.”
OECD reportednegative outcomes when students spent a lot of time using computers, while Stanford University’s Center for Research on Education Outcomes (CREDO) concluded that online charter schools were basically a disaster.
Larry Cuban, Sherry Turkle, Gary Stager, and Will Richardson.
Emily Talmage points out, uncannily aligned with the wish list of the Digital Learning Council, a group consisting largely of conservative advocacy groups and foundations, and corporations with a financial interest in promoting ed tech.
It will be eons before AI thinks with a limbic brain, let alone has consciousness
AI programmes themselves generate additional computer programming code to fine-tune their algorithms—without the need for an army of computer programmers. In AI speak, this is now often referred to as “machine learning”.
An AI programme “catastrophically forgets” the learnings from its first set of data and would have to be retrained from scratch with new data. The website futurism.com says a completely new set of algorithms would have to be written for a programme that has mastered face recognition, if it is now also expected to recognize emotions. Data on emotions would have to be manually relabelled and then fed into this completely different algorithm for the altered programme to have any use. The original facial recognition programme would have “catastrophically forgotten” the things it learnt about facial recognition as it takes on new code for recognizing emotions. According to the website, this is because computer programmes cannot understand the underlying logic that they have been coded with.
Irina Higgins, a senior researcher at Google DeepMind, has recently announced that she and her team have begun to crack the code on “catastrophic forgetting”.
As far as I am concerned, this limbic thinking is “catastrophic thinking” which is the only true antipode to AI’s “catastrophic forgetting”. It will be eons before AI thinks with a limbic brain, let alone has consciousness.
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Stephen Hawking warns artificial intelligence could end mankind
By Rory Cellan-JonesTechnology correspondent,2 December 2014
“Social media is the future of customer service,” says Anna Yates, a content marketer for The Social Reach, a digital marketing agency. “Not only are consumers turning to social media more and more to learn about products and services, but new tools are available to make customer service faster, easier, and smarter.”
the three Ps — be patient, persistent, and polite. Companies tend to flip into “crisis” mode when you send angry messages that threaten lawsuits, bodily harm, or the end of civilization.
From: The EDUCAUSE Blended and Online Learning Constituent Group Listserv <BLEND-ONLINE@LISTSERV.EDUCAUSE.EDU> on behalf of Robert, Jenay <jrr296@PSU.EDU> Sent: Wednesday, September 5, 2018 9:58:49 AM
Dear colleagues,
I am collaborating on a project comparing the efficacy of two types of instructional videos. We are looking for literature that describes similar research. For example, a study might compare students who have watched voice-over ppt slides and students who have watched Khan-style videos, examining students’ content knowledge and/or some affective constructs. Alternatively, a study might compare the lengths or speeds of only one type of video.
Given the dearth of literature addressing these variables, I am hoping this community can help us uncover some additional research for our literature review. I am happy to compile and share everything that is shared with me over the coming days.
Jenay Robert, Ph.D. Research Project Manager Teaching and Learning with Technology The Pennsylvania State University
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Clossen, A. S. (2018). Trope or Trap? Roleplaying Narratives and Length in Instructional Video. Information Technology & Libraries, 37(1), 27-38.
It is impossible to please everyone all the time—at least that is what survey results suggest. There are several takeaways to this study: Video length matters, especially as a consideration before the video is viewed. Timestamps should be included in video creation, or it is highly likely that the video will not be viewed. The video player is key here, as some video players include video length, while others do not. Videos that exceed four minutes are unlikely to be viewed unless they are required. Voice quality in narration matters. Although preference in type of voice inevitably varies, the actor’s voice is noticed over production value. It is important that the narrator speaks evenly and clearly. For brief how-to videos, there is a small preference for screencast instructional videos over a narrative roleplay scenario. The results of the survey indicate that roleplay videos should be wellproduced, brief, and high quality. However, what constitutes high quality is not very well established.15 Finally, screencast videos should include an example scenario, however brief, to ground the viewer in the task.
Lin, S., Aiken, J. M., Seaton, D. T., Douglas, S. S., Greco, E. F., Thoms, B. D., & Schatz, M. F. (2017). Exploring Physics Students’ Engagement with Online Instructional Videos in an Introductory Mechanics Course. Physical Review Physics Education Research, 13(2), 020138-1.
Kruse, N. B., & Veblen, K. K. (2012). Music teaching and learning online: Considering YouTube instructional videos. Journal Of Music, Technology & Education, 5(1), 77-87. doi:10.1386/jmte.5.1.77_1
Buzzetto-More, N. A. (2014). An Examination of Undergraduate Student’s Perceptions and Predilections of the Use of YouTube in the Teaching and Learning Process. Interdisciplinary Journal Of E-Learning & Learning Objects, 1017-32.
Chekuri, C., & Tiecheng, L. (2007). Extracting content from instructional videos by statistical modelling and classification. Pattern Analysis & Applications, 10(2), 69-81.
My note; too old as data but interesting as methodology
40 virtual reality headsets with haptic handsets for them to manipulate in the VR/AR space, and I connected them to content from New York Times VR and WITHIN. The content placed students in settings such as on the ground in a refugee crisis or in the midst of the Millions March in New York City.
At the beginning of every class, they would go into this virtual space and engage with the content instead of just reading it. They’d respond to me about what it was like to be immersed in the experience.
The content from the WITHIN app provided one of the more visceral experiences for students.
At the end of the course, for example, students met with a shark tank-type group—investors from the community, business, and industry folks—and pitched them business ideas that would utilize VR to provide a solution to problems that were local, regional, national or even global in scope.
Were you able to measure this success?
The way that I measured it was completion. How many of my students actually got through my class successfully? It was over 85%. My research from the two classes where I used VR and this approach shows students were engaged, and ultimately more successful in my classes.
Five tips to help you create a personal brand and a positive digital reputation
1. What will they find when they Google you?
2. What is branding?
Your brand is what you represent, the content that you share, your audience, your Personal Learning Network (PLN), and your teaching philosophy. You want your brand to demonstrate that you are trustworthy, and offer quality content, insightful comments, and experience. Your brand tells your audience that what you offer is of value. Together, the elements that create your brand should communicate a distinct, cohesive story. For instance, when you visit any of my social media profiles, you will see a consistent message. The avatar and logo for my website Shake Up Learning are more recognizable than my face, and that’s intentional. That isn’t to say that every brand needs an avatar. But do find a creative way to tell your personal story.
3. Choose the right platforms
There is no right or wrong platform. Choosing where you want to build your online presence depends on the audience that you want to engage. If you want to reach parents and school community stakeholders, Facebook is a strong bet. If you want to reach other educators, Twitter and Pinterest are big winners. The bottom line is that you don’t have to use them all. Find and connect with your audience where your audience resides.
4. Claim your social media real estate
Before you settle on a username, check that it’s available on all of the social media platforms that you want to use—and then keep it consistent. You will lose your audience if you make it hard to find you. Also keep your handle simple and short, and try to avoid special characters. When a new platform arrives, claim your username early even if you aren’t sure that you will maintain a presence there.
5. Optimize your social media profiles
Guy Kawasaki, co-author of The Art of Social Media, khas nearly 1.5 million followers on Twitter alone, and he offers effective social media tips in his book. Here are the basics:
Add a picture of your face or logo. Your picture validates who you are. No more eggheads! Using the default egg avatar on Twitter says you don’t have a brand, and doesn’t tell your audience that you are trustworthy.
Use your real name. Sure, you can lie, but that isn’t going to help you build a brand and online presence. Many platforms allow you to show your name as well as your handle.
Link to your website, blog or About.me page. Don’t have one? Get one! You may not be ready to start a blog, but anyone can easily set up an About.me page—which is like an online resume.
Compose a meaningful bio, which will help others find and follow you. It should describe your experience in the field of education and highlight topics that you follow like Maker Ed, Google Apps, or edtech.
Add a cover image. Choose an image that tells your story. Who are you? What do you do that sets you apart? Canva is a graphic design tool that makes creating a cover image easy. It offers ready-made templates in the right size for all of the major social media platforms.
Be consistent across all mediums. You want your followers to see the same brand on all of your social media profiles. This also means you shouldn’t change your profile picture every five minutes. Be recognizable.
Tools to build your brand and online presence
About.me: A quick and easy personal homepage that shows your audience who you are and how to connect with you.
Canva: An easy-to-use design tool for creating images, with templates for social media.
Fiverr: A marketplace for services that you can use to commission a logo, avatar, or web design.
