Information Privacy - Science topic

To ensure ethical compliance, organizations must implement comprehensive measures, including diverse dataset usage, regular bias audits, clear regulatory guidelines, and mandatory ethics training for developers. Additionally, establishing strong governance structures will help balance technological advancement with social responsibility, ensuring AI development aligns with human values and promotes equitable outcomes for all members of society.

Eduard Babulak Sir, we are working on this (automated threat defense system) for industry, city and also for smart home. Already we proposed a model and we have submitted it on a prestigious IEEE conference (IEEE ICAISC 2025, Saudi). You can advise us as well as help us to grow.

I have just been bombarded with fake 'recommendations'. An 'article' was listed twice in RG, one of which lists the British Journal of Aesthetics as the publication source. I 'followed' it to read later. Within hours I received several 'recommendations', spiking quickly within a few days. I had time this morning to check out one of the 'articles' more carefully, and it even has a fake DOI. I've been asked for full texts, and approached on LinkedIn. And this morning I got an email which said that a colleague 'found me on Research Gate', and I was being asked to publish with their 'World Culture' series. And I am now stuck with a load of recommendations that are clearly questionable as the profile from which the recommendation stems has nothing to do with my research area - and is also fake or impersonating someone.

Here's a structured approach to writing an abstract for your research on "Analyzing the Concept of Data Privacy in Big Data Analytics in Banking." Follow this outline to ensure you cover all essential components:

Abstract Outline

It was my pleasure, Md. Afroz Alam.

I think Addressing IoT security and privacy requires a multi-faceted approach:

By implementing these measures, we can mitigate the risks associated with IoT devices and protect user data privacy. It's essential for manufacturers, developers, and users to work together to create a secure and trustworthy IoT ecosystem.

When you say you've completed research "without getting approval from the ethics committee" does that mean you approached an ethics committee, explained your research, and they clarified ethical approval wasn't required (as can sometimes be the case for some topics of research).

Or was it that you and colleagues decided that because you felt no ethical approval was required you simply didn't apply for it? That would be more concerning.

If your research involves human participants and an ethics committee is available to you, then you should seek clarification from them rather than decide for yourself what requires approval or not.

Although it's always the responsibility of the researcher(s) to ensure all areas of research are ethical (which is a very broad category of considerations), it's important to check whether and what kind of ethics approval may be necessary.

It might be for some studies and data sources there is no need for ethical approval. But if you're planning expert interviews and Delphi studies then yes, I would ask for clarification and expect an application would be necessary.

If you ran surveys previously where any kind of demographic data was collected, for example, then you did collect personal information. This also applies for any future work you want to do.

It's also not just about identifiable information, it's about a whole host of other issues including researcher and participant welfare, rigour, integrity and more.

Alongside seeking clarification from your ethics committee it may be worth asking them if they offer training or enquiring if any is available at your institution. This should help clarify some of the questions you have.

I will try my best to answer it in terms of Governance, Product organization, or the person tasked with integration, their or his/her commitment in terms of policies and procedures might help showcase their seriousness towards protecting the confidential data of their customers. Compliance with Industry standards and regulations is another step towards trust and faith.

Independent attestations are a piece of excellent evidence.

In terms of technical controls and security, various alternatives can be looked at, starting with access management, data anonymization, encryption, and control/data plane segregation, to name a few.

ResearchGate Link:

(PDF) Improving Lean engagement through utilising improved communication, recognition and digitalisation during the COVID-19 pandemic in JLR's powertrain machining facility (researchgate.net)

Companies can effectively leverage digital technologies to create engaging, personalized, and seamless customer experiences by adopting a holistic and customer-centric approach. Firstly, investing in robust customer relationship management (CRM) systems allows companies to gather and analyze customer data, enabling them to understand preferences, behaviors, and interactions. This data serves as the foundation for personalized experiences.

Implementing artificial intelligence (AI) and machine learning (ML) algorithms can further enhance personalization by predicting customer preferences and recommending tailored products or services. Chatbots and virtual assistants powered by AI streamline customer interactions, providing instant and personalized support.

Moreover, companies should prioritize omnichannel strategies, ensuring a consistent and seamless experience across various digital touchpoints. This involves integrating online platforms, mobile apps, social media, and physical stores to create a unified customer journey.

To maintain engagement, personalized content delivery is crucial. Utilizing data-driven insights, companies can deliver targeted marketing messages, product recommendations, and promotions. This not only captures customer attention but also enhances brand loyalty.

Michael Aubertin Thank You

What an insightful question! It's understandable to have concerns, but it's important to note that both the LGBTQ and Muslim communities have faced discrimination and prejudice across the continent. Muslim are even worse though, From Palestinian, Rohingya, Muslims of India, to Uyghurs, in Europe, in USA, in Canada, and other developed nations, Muslims are subject to Airport interrogation, severe discrimination, and public assault due to physical grooming and belief framework. Worse labelled as terrorists while zionists are killing Palestinian every single day since the Balfour Declaration of 1947. Islamophobia is a supernatural phenomenon that no single leader in the world is able to stop this Psychologically disorder. However, when it comes to the world of academia, unique ideas and perspectives are highly valued. It's all about finding the right publication and publisher who appreciate originality in research and writing. Best of luck with your submission, Doctor!

Data privacy policies play a crucial role in digital innovation management by balancing the need for innovation and technological advancements with the protection of individuals' privacy and personal data. Here are some key roles of data privacy policies in digital innovation management:

In summary, data privacy policies provide a framework for responsible and ethical digital innovation management. They ensure the protection of individuals' privacy rights, foster trust, and enable organizations to innovate while managing risks associated with personal data handling. By integrating privacy considerations into the innovation process, organizations can build sustainable and privacy-respecting digital solutions.

A very good example of something which demonstrated this inclusion approach is this article from Wired:

May 26, 2023 6:00 AM

New photo manipulation tools from Google and Adobe are blurring the lines between real memories and those dreamed up by AI.

The short films were mostly demonstrations of technology; well-constructed narratives took a backseat. Some were surreal, and in one instance intentionally macabre. The last film shown made the hair stand up on the back of my neck. It felt as though the filmmaker had deliberately misunderstood the assignment, eschewing video for still images. Called Expanded Childhood, the AI “film” was a slideshow of photos with a barely audible echo of narration.

Director Sam Lawton, a 21-year-old film student from Nebraska, later told me he used OpenAI’s DALL-E to alter the images. He assembled a series of photos from his childhood, fed them to the AI tool, and gave it various commands to expand the images: to fill in the edges with more cows, or trees; to insert people into the frame who hadn’t really been there; to reimagine what the kitchen looked like. Toss another puppy into the bathtub—why not? Lawton showed the AI-generated images to his father, recorded his befuddled reactions, and inserted the audio into the film.

“No, that’s not our house. Wow—wait a minute. That’s our house. Something’s wrong. I don’t know what that is. Do I just not rememberit?” Lawton’s father can be heard saying.

Where do real memories end and generative AI begin? It’s a question for the AI era, where our holy photos merge with holey memories, where new pixels are generated whole cloth by artificial intelligence. Over the past few weeks, tech giants Google and Adobe, whose tools collectively reach billions of fingertips, have released AI-powered editing tools that completely change the context of images, pushing the boundaries of truth, memory, and enhanced photography.

Google dipped its toes in the water with the release of Magic Eraser in 2021. Now the company is testing Magic Editor, a feature on select Android phones that repositions subjects, removes photobombers, and edits out other unseemly elements, then uses generative AI to fill in pixel gaps. Adobe, arguably the most famous maker of creative editing software, announced earlier this week that it was putting its generative AI engine Firefly into Adobe Photoshop. The aptly named Generative Fill feature will edit photos and insert new content via a text-based prompt. Type in “add some clouds” zand there they appear.

Adobe is calling it a “co-pilot” for creative workflows, which parrots the phrasing that other tech companies, such as Microsoft, are using to describe generative AI apps. It implies that you are still in total control. In this framing AI is merely offering an assist, taking over navigation when you need a bathroom break. This is something of a misportrayal when the AI is actually acting as a cartographer, redrawing the maps of your existence.

“‘Perfect your memories’ is perhaps the most haunting phrase I’ve ever read,” Signal Foundation president and former Googler Meredith Whittaker tweeted in February, in response to Google’s announcement that its Magic Eraser tool could now be used in videos, not just in photos. In its marketing of the tool, Google shows an image of a young girl facing a choppy sea. Nearer to the shoreline is a family of four, presumably not hers. Magic Eraser disappears them.

Let’s be totally clear: We could always edit photos. Whether by scissor, razor, or paint, as long as the printed photo has existed, we’ve edited. Photoshop’s provenance was timed to the rise of the personal computer, which, non-hyperbolically speaking, changed everything.

The first version of Photoshop launched in 1990. “Jennifer in Paradise” was the digital photo seen around the world: an image of Photoshop cocreator John Kroll’s wife sitting on a beach in Bora Bora. In demos, Kroll would outline his wife using the now-famous lasso tool, then clone her. He copied, pasted, and diffused an island in the distance. “A duplicate island!” Kroll said in a video posted to Adobe’s YouTube channel in 2010. An island that was not really there. A fabricated land mass.

What’s different today—what generative AI is pushing boundaries on—is the speed with which these edits can be made and who can make them. “Editing tools have existed for a long time,” says Shimrit Ben-Yair, the head of Google Photos. “And obviously we’ve been offering editing tools on Photos for a while now. As these platforms have grown their user bases, these tools become much more accessible and available to people. And edited images become more common.”

In a private demonstration of Google’s Magic Editor tool, which ships later this year, Ben-Yair pulled up yet another beach photo. This one featured two kids sporting wetsuits and boogie boards, with two adults in the distant background. The kids and adults have different skin tones, and the somewhat uncomfortable assumption in this demo—also emphasized by the distance between them—is that they are not family. Google’s Magic Editor outlined the adults in the background, then disappeared them.

In another demo, Magic Editor erased the bag strap from a woman’s shoulder as she posed in front of a waterfall, then filled in the gaps with more jacket material. Why the bag strap in a hiking photo was so bothersome, I do not know. But those aesthetic decisions are the prerogative of the photo’s creator, Google says.

Adobe’s Generative Fill is much more, well, generative. A long-haired corgi scampers down an empty road. That’s it, that’s the photo. But Generative Fill lengthens the road. It transforms barren trees into a springtime bloom. A white pickup truck appears, and whether it’s driving toward the corgi or away from it changes the tension of the photo in a notable way. But, look, now there are puddles. Surely that’s a happy photo? Generative AI is even smart enough to draft a reflection of the scampering pup in the puddles. It does this all in seconds. I’m blown away.

But after the astonishment comes “What now?” Suppose that is my hiking photo, my dog, my family on the beach. How will I remember that day if in the future they are only watercolor in my brain, and I increasingly turn to my photo roll for more vivid strokes? Did I actually not carry a bag while hiking? Did the pickup truck come dangerously close to my dog that day? Did I only ever vacation on pristine, private beaches?

Executives at both Google and Adobe say the power of the tools must be considered within the context of the photo. Who is taking it, who is sharing it, where it’s being shared to. “I think in the context of a public space, there are different expectations than that of a photo being shared in a private space,” says Ben-Yair. “If someone is sharing a photo with you via Google Photos itself or a messaging app that you use, you trust that source. And you might see the editing as something that enhances the photo, because you trust that source.”

“But the more layers of abstraction there are,” she continues, “Where you don’t know the source, then yeah, you have to think through, how authentic is this photo?”

Similarly, Andy Parsons of Adobe says there’s a “continuum of use cases” for AI-edited photos. An artist (or individual who fancies themself an artist) might use generative AI to alter a photo that’s meant to be a creative interpretation, not documentation. On the other hand, “if it’s very critically important to know that what’s being presented in the photo is a reflection of reality, such as in a news organization, we expect to see more and more photographers being required to provide transparency,” Parsons says.

Parsons is something like the king of provenance at Adobe. His actual title is senior director of the Content Authenticity Initiative, a group Adobe cocreated in 2019 to establish cross-industry guidelines around content origination and media transparency. It was the doctored Nancy Pelosi video, Parsons says, in which the Speaker of the House appeared to be slurring her words, that “again, changed history.” Even though the editing wasn’t credited to AI, the sheer manipulation of the Pelosi video made Adobe reconsider how its powerful editing tools might be used. Adobe’s earliest partners in the CAI were Twitter and The New York Times.

Then, in 2021, Adobe joined forces with the BBC, chip-makers Intel and ARM, and Microsoft to create yet another consortium for standards around “digital provenance,” called Coalition for Content Provenance and Authenticity, or C2PA. The Coalition now has more than a thousand members across various industries. At Microsoft’s annual software conference this week, the company said that its Bing Image Creator will soon use C2P2-standard cryptographic methods to sign AI-generated content. (Google’s Ben-Yair also says this is an “active area of work for the company that we’re going to explain once we get closer to the launch of it.”)

“We’re all focused on the same idea,” Parsons says. “We’ve kind of lost the arms race in detecting what may be fake. The chasm has been crossed. So the protection and countermeasure we have is knowing what model was used to capture or create an image and to make that metadata trustworthy.”

In theory, these cryptographic standards ensure that if a professional photographer snaps a photo for, say, Reuters and that photo is distributed across Reuters international news channels, both the editors commissioning the photo and the consumers viewing it would have access to a full history of provenance data. They’ll know if the cows were punched up, if police cars were removed, if someone was cropped out of the frame. Elements of photos that, according to Parsons, you’d want to be cryptographically provable and verifiable.

Of course, all of this is predicated on the notion that we—the people who look at photos—will want to, or care to, or know how to, verify the authenticity of a photo. It assumes that we are able to distinguish between social and culture and news, and that those categories are clearly defined. Transparency is great, sure; I still fell for Balenciaga Pope. The image of Pope Francis wearing a stylish jacket was first posted in the subreddit r/Midjourney as a kind of meme, spread amongst Twitter users and then picked up by news outlets reporting on the virality and implications of the AI-generated image. Art, social, news—all were equally blessed by the Pope. We now know it’s fake, but Balenciaga Pope will live forever in our brains.

After seeing Magic Editor, I tried to articulate something to Shimrit Ben-Yair without assigning a moral value to it, which is to say I prefaced my statement with, “I’m trying to not assign a moral value to this.” It is remarkable, I said, how much control of our future memories is in the hands of giant tech companies right now simply because of the tools and infrastructure that exist to record so much of our lives.

Ben-Yair paused a full five seconds before responding. “Yeah, I mean … I think people trust Google with their data to safeguard. And I see that as a very, very big responsibility for us to carry.” It was a forgettable response, but thankfully, I was recording. On a Google app.

After Adobe unveiled Generative Fill this week, I wrote to Sam Lawton, the student filmmaker behind Expanded Childhood, to ask if he planned to use it. He’s still partial to AI image generators like Midjourney and DALL-E 2, he wrote, but sees the usefulness of Adobe integrating generative AI directly into its most popular editing software.

“There’s been discourse on Twitter for a while now about how AI is going to take all graphic designer jobs, usually referencing smaller Gen AI companies that can generate logos and what not,” Lawton says. “In reality, it should be pretty obvious that a big player like Adobe would come in and give these tools straight to the designers to keep them within their ecosystem.”

As for his short film, he says the reception to it has been “interesting,” in that it has resonated with people much more than he thought it would. He’d thought the AI-distorted faces, the obvious fakeness of a few of the stills, compounded with the fact that it was rooted in his own childhood, would create a barrier to people connecting with the film. “From what I’ve been told repeatedly, though, the feeling of nostalgia, combined with the uncanny valley, has leaked through into the viewer’s own experience,” he says.

Lawton tells me he has found the process of being able to see more context around his foundational memories to be therapeutic, even when the AI-generated memory wasn’t entirely true.

There are many current problems in cybersecurity and IoT, some of which include:

1. Device vulnerabilities: IoT devices are often designed with weak security, making them an easy target for hackers.

2. Distributed Denial-of-service (DDoS) attacks: These attacks are increasing in frequency and are becoming more sophisticated, making them difficult to prevent.

3. Lack of standards: There is currently a lack of industry-wide standards for IoT security, making it difficult for manufacturers to ensure that their devices are secure.

4. Data privacy: IoT devices often collect and store large amounts of data, putting personal and sensitive information at risk.

5. Insider threats: Employees, contractors, and other insiders can pose significant security risks to IoT systems, as they can intentionally or inadvertently cause data breaches.

6. Cloud security: Many IoT devices rely on cloud services to operate, making them vulnerable to cloud-based attacks.

To address these problems, it is important for businesses and individuals to implement strong cybersecurity measures, such as strong passwords, encryption, and regular updates. Additionally, industry-wide standards and regulations can help ensure that IoT devices are designed and manufactured with security in mind.@

This is certainly not grounded theory because you have not alternated data collection and data analysis in the systematic fashion required by that method. To be mixed methods research you would need to integrate the results from qualitative and quantitative methods, but it sounds like your N would be too small to produce meaningful quantitative results.

That leaves exploratory research, would be a good match to a thematic analysis.

* Big corporations driving the research to suit their market needs and revenue

* Academics funded by big corporations skewing the research directions and outcomes

* Research only focussed on publishing papers without an iota of concern for quality and ethics

In a nutshell, the issues with AI are primarily due to the declining quality of academic research at elite institutions.

viAct is GDPR absolute complaint.

Peter Broadhurst Thank you peter, sent you a message. Please check. Have a great day!

The external influences on the work - profession, familiar life and so on.

The social conditions and relations with other people, also, I think influence the ethical issues of Neuromarketing.

The General Data Protection Regulation (GDPR) is a robust privacy law that was created by the European Union (EU) in 2016 and became effective in 2018. ... The purpose of the GDPR is to update digital security for the citizens of the EU by giving them a higher level of control on the personal information they share online.

Great question - given the attitude afforded by the Investigatory Powers Act in the UK, there is a huge privacy concern posed by CAVs. These are essentially mobile surveillance systems and the concern is how footage from the onboard interior and exterior facing cameras is used and whether state bodies can request access to these. Lots of really questions surrounding CAV use and development in the UK.

Very best wishes, James.

Hi.,

xAPI works by producing simple statements, consisting of a noun, verb and object. For example, Jack has completed Basic Business Math. The statement that's produced lets you know what e-learning Jack has accessed and exactly when it was completed. This information is stored in the Learning Record Store (LRS).

The main data structure used by xAPI to describe tracked experiences is called a statement.The XAPI service enables you to call any of the application XAPIs and return results which can then be used by a later step in the business process.

Dear Ekhlas A. Hussein,

I would like to add a few words to this discussion on this important topic. The issue of privacy protection in Big Data analysis for unstructured data is an important and developmental topic. Due to the fact that more and more companies, enterprises, corporations, public and financial institutions use the analytics of large sets of internal data (generated in a specific economic entity or institution) and external (obtained from the Internet), use Big Data Analytics platforms, so the importance of information security and data obtained from various sources, archived and processed will increase. As part of improving the security systems of computerized Big Data Analytics platforms and the data stored on these platforms, intelligent gateway and firewall solutions are created when these platforms download data from the intranet and the Internet. In addition, the systems of institutional email applications are being improved in order to reduce the scale of successful cybercriminal attacks by cybercriminals using malware and ransomware viruses hidden in spamming.

Regards,

Dariusz Prokopowicz

Hi Arijit Nandi ,

Thanks for your input. I have their codes. They have followed the same. I have attached their code below.

Dear Agnes Koschmider,

Have you got any datasets? Can you share it with me?

Thanks for this interested question. Agree with

Dear Sisay Chala,

A very good substantive question. During the SARS-CoV-2 (Covid-19) coronavirus pandemic, the scale of digitization and internationalization of remote communication processes, remote work, e-learning, online shopping and payments, etc., and many other aspects of communication processes, economic processes, increased, financial, social etc. The scale of using ICT, Internet and Industry 4.0 information technologies in these processes has increased. On the other hand, there are doubts whether the pace of improvement of cybercrime risk management systems, the risk of data transfer in the Internet, the risk of viruses and viruses and malware in smartphones used by users of the mobile internet banking application, etc. is keeping pace with the current progress determined by the increase in the digitization and Internetisation of communication processes. , economic, financial, social and other processes.

Best regards, Have a nice day, Stay healthy!

Dariusz Prokopowicz

Intresting topic

Given that the main routes to breach privacy are

- identity tracing,

- attribute disclosure attacks using DNA (ADAD)

- and completion of sensitive DNA information*,

the main questions would emerge from each of these distinct yet overlapping issues.

Genomic privacy though, I would argue, isn't necessarily about the academic exercise (fascinating as one might find it), but rather a more and more pressing issue, given the development of AI, as well as the various regulatory frameworks concerning data and individual privacy...

I do hope this may have been of some use, though I'm sure a lot has happened in the field since the question was posted. Best of luck with your research!

*https://www.nature.com/articles/nrg3723?cacheBust=1508217951179

Dear Ridha Dhawan,

In my opinion, people who use various information services available on the Internet have very different knowledge about the security of personal data posted on various social media portals and / or transferred via various instant messaging and other Internet media. High variation in this knowledge results from different experiences, and above all from possible negative experiences of loss of sensitive data on the Internet or other effects of cyber criminals' activities. People who have less knowledge in this matter are willing to post more personal data about themselves on social media portals. In a situation of greater awareness of the emerging threats in this matter, Internet users use specific actions, practices (e.g. not opening e-mails of unknown origin) and instruments (e.g. anti-virus applications, frequent updating of operating systems). Therefore, Internet users who are individual clients of social media portals and other new Internet media have varied awareness of various aspects of the risk of potential loss of personal data in the Internet, etc., however, they do not examine these risks instrumentally. On the other hand, enterprises, mainly large corporations, financial institutions, including internet banks, build and improve risk management systems for IT systems connected to the Internet, etc. I have described this issue in more detail in some of my publications available on the Research Gate portal. I invite you to cooperation.

Best regards,

Dariusz Prokopowicz

Privacy and social media are in a paradoxical relationship.

Agree with Ralf's views on this. Universities can look at industry linked programs in Risk and Compliance space and privacy can be covered under that.

I think using normalization techniques it possible to add.

I agree with Manjula.

This is a great question, and inspired to me to look for some quantification of the risk and probability of data breaches and harm. Found the following reports which may be of interest. They are largely from security companies and insurance companies, which would have access to this kind of data and might need data like that to set insurance policies.

done wish you the best

I think as you have mentioned there’s a lack of skilled employees and general lack of knowledge on the subject because in my opinion it’s still relatlively in its infancy. Also it’s trying to understand how to utilise it for the benefit of the company and how it affects things GDPR.

The link below may clarify this thing:

https://en.wikipedia.org/wiki/Differential_privacy

The Electronic Frontier Foundation "The leading nonprofit defending digital privacy, free speech, and innovation."

The Electronic Privacy Information Center

You would probably find more information related to this vector of research if you looked at things associated with "risk tolerance". A highly paranoid person might be thought of as having very low tolerance for risk, while a person with a high tolerance for risk might be thought of as not being paranoid. I am over-simplifying, of course, from a psychological perspective, but since you are looking at behaviors associated with information, this terminology might be more useful to your ability to find related publications/research.

Also maybe this paper helps you: https://www.researchgate.net/publication/323837643_A_model_for_users'_profile_recognition_based_on_their_behavior_in_online_applications?_sg=NUMFtFov-uuLhy4A8nzxo0kfndJVOTmI97d0BAwb_LJ4eumZWtCGjRT134qB7Lb6nKi00rrBIIPsTRzkmqIfW-w4gx11PnRoJLCP-KHk.GYvObA3FwTf-m99GeCQ9rqmf21H-PZb1mOlHacBweQp_DHd9fXgdZCS_ZtxxfDDEH90NVX3qEEeEkFmaA5a7Tw

Unfortunately, contrary to the assurances of companies that run social media portals, the information contained on these websites is not always fully secured by the activities of cybercriminals. In addition, the issue of downloading data from social media portals by large companies to Big Data database systems should be added in order to process them for marketing purposes. The issue of privacy in social media is very important and is related to the security of personal information. Privacy is at risk in terms of information posted on social media portals.

The problems of the analysis of information contained on social media portals for marketing purposes are described in the publication:

I invite you to discussion and cooperation. Greetings

Interesting

a lot of work has been done in this respect, see for example

colleagues in the European Union Agency for Fundamental Rights have done a lot see http://fra.europa.eu/en/publication/2018/biometrics-rights-protection

Thank all colleagues and friends

I Agree with Barbara Sawicka definitely!

GPDR can be considered in many aspects.

For small organizations, this will involve many new responsibilities. It will also affect honest and high standards - as there will be a need to document compliance with these standards, while it has been sufficient to comply with them so far.

Larger organizations are likely to feel less because they are more formalized and bureaucratic anyway.

There will be fear of penalties, which may limit some activities. While most probably agree that abuses and uncontrolled trade in personal data should be limited, the problem of borderline events, taken in good faith, will also appear, which, however, can also be interpreted as abuse and transgression.

Will this improve the protection of the right to privacy? It really depends on people and their awareness. The last affair with Facebook showed how easy private data can be used, but on the other hand people should be able to count on such a situation by sharing their data on the Internet. No regulation can replace reason and caution.

Will it affect learning and information flow? I do not think so much. If these regulations were in force many years ago, today we would probably know that the AIDS patient traveled a lot and was homosexual - because they influenced the way the disease spread and that it affected homosexuals in the first place, but we would not know the name this patient, which does not matter to understand the mechanism of disease spread.

I work in data recovery. This is a very sensitive area when it comes to confidentiality and data security. If someone entrusts me with his medium, he expects that the data I will recover will not be disclosed to anyone else or to a jealous wife or police - if I suspect that they may be evidence of a crime. On the other hand, if the client is, for example, the Police, it is not my role to protect someone's intimate secrets that concern legal but very personal matters.

Usually I do not analyze the contents of the media, unless I am explicitly asked for it, so I do not even know about many ethically doubtful situations. However, over the years I have seen something like this several times that I had serious doubts as to how to proceed. Always prevailed loyalty to the client. He is the owner of the data and he is responsible for their use.

Thank you @roger Hallman

Hi Scott,

it was pleasure meeting you at ICIS and indeed your paper is interesting.

in my view, most privacy researchers adopt/adapt some form of the privacy calculus, even if the calculus is not mentioned, what is missing however is the boundary conditions to this calculus (e.g., cognitive, motivational, situational factors, to name a few). Identifying these boundary conditions could be our way as privacy researchers to understand the complexity of privacy-related decision making.

good luck!

Thank you @Maleh Yassine, @Martin Henze, @Dibakar Pal, @Venkatesh Gauri Shankar

See details in good Wikipedia articles (see the links below):

We conducted a study on acoustical methods for leak detection.  We have a conference paper published. A more comprehensive report should be out later this year.

I think that a simple read lock should fulfill your requirement of giving merely one process access to a certificate repository. I caught a glimpse of the existing literature and found a patent about a read and write lock management at https://www.google.com/patents/US6029190. I hope it helps you.

Hi Jalpesh

When dealing with Big Data Privacy and Security, you need to consider the fact that you must have security first, in order to ensure that you can then have privacy. If you have data which has privacy, but there is no security, then anyone can help themselves to the data, and it is simply a matter of time before the privacy element is cracked and the data is available to the attacker. Whereas, if the data is secure in the first place, then privacy simply adds another level of comfort to your already secure data.

So the first goal must always be to aim for a high level of security. This is then followed by ensuring a high level of privacy can be achieved. Next, we need to ensure we retain the means to ensure we can certify the provenance of the data. Data is useless if it has been accessed and corrupted, modified or had important elements deleted. Thus, we must achieve three goals in order to have a useful outcome.

I have attached a number of useful papers from my own research collection which cover each of these three areas to get you started. As you can see, there is little work on Big Data Provenance, and the work of Thomas Pasquier is something you should explore further.

If you consider the source of data, data which comes from corporate sources, where the corporate is ISO 27002 compliant, it is likely to be a reasonable source of data. For cloud sourced data, while there are some standards now coming out, there is currently no complete cloud security standard, thus this data is likely to be of a lesser standard. Once we move to Internet of Things data, we are moving into 'Wild West' territory. Anybody and their dog can easily hack in to IoT systems, meaning the level of trust in this data has to be considerably discounted.

If you want to find a big data area that can provide you with an exptreme challenge, IoT is the pace to go. Of course, this means that until cloud big data security and privacy are solved, your big data IoT challenge will be an impossible goal to achieve.

Ultimately, the choice is yours, but we need to focus on resolving problems in a logical way, so you may want to address the cloud big data challenge first, before moving on to IoT big data. You could, of course, focus on non-cloud big data, but given the ease with which cloud enables the creation of big data, the cloud route may be the better choice.

I hope this helps.

Regards

Bob

enc

The customers have unique personally identifiable information (PII) represented in biometric datasets. The PII entails privacy, trust, and security at all times. Cybercriminals seek PII for ransomware and illegal financial gains. To secure-biometric information is to employ secure server for effective authentications of transactions. Stolen biometric datasets could be used for impersonation to evade safeguards. Therefore, measures such as use of datasets for intended purposes only, destruction upon completion, access by trusted personnel only, closely supervised settings, extended access control, safeguarding the private key, and strong passwords (ePassports contents),

Ayodeji,

I am not sure if this will really be much of an assist, but this is probably the best you will be able to do when dealing with anything child related as it is very challenging to procure hash sets for anything child related unless you are law enforcement or LE sponsored to perform forensics etc.  You may want to consider speaking with someone at your local ICAC or NCMEC.

You can use the NSRL datasets found at the included link for non-child related hash sets for research projects.

You can use Autopsy to perform some of that research.

Good Luck.

Thanks.

The concept of privacy and security is such a vast and could be applied in several fields.

I agree to explanations provided by Henrique Santos and Jean Damascene Twizeyimana. Info system encompasses users so, models developed for Info System Security applicable to humans also. and yes, if as a human being I will not take the responsibility of safe keeping of my gadgets (s.a, my cards, smart phones, physical keys, laptop etc) or will not  keep certain things private to myself  (e.g., my PINs, Password, OTPs etc) then I doubt anything can provide me security.

Here is an article discussing the privacy laws between the EU and the US: 

As for the determination of the best country, it will depend on your preset determining factors.

Human factor is considered as the weakest link in defending systems' security and privacy. The bulk of known attacks lay in the area of social engineering attacks. Phishing attacks are wide spread in on- and off-line communications (for instance, emailing and postal services).

These bold/italic marked terms above can be used to see their exact meaning in the Wikipedia, and applied with any search engine to collect enormous amount of information relating to the actual analyses of vulnerabilities, threats and their impact on privacy and security. 

You have other variation such as t-closeness

l-diversity guarantees that for a group there is at least l different sensitive attribute values (or combination), in addition to the basic k-anonymity algorithm.

p-sensitivity relates to location query, but could probably be generalised to a larger set of problem.

What do you want to do?

Jeff, it was indeed a valuable response and the suggested tool will be great help towards implementation of one of the ideas I have in mind. Thank you so much. Thanks kskyani for asking the question as well :-)

Have a look at the Ofcom studies at http://stakeholders.ofcom.org.uk/market-data-research/other/research-publications/childrens/childrens-media-lives-year1/

They have been working with families with children, researching their media usage and behavior.

I have quickly scanned this recent study about privacy perception among teenagers. 

@shuaibu , any references ? 

Thanks Tobias and Gottfried. I do mean concrete harms such as medical identity theft, work or insurance prejudices, significant embarrassment or personal disruption.

By data blocking I mean: information blocking, “where persons or entities knowingly and unreasonably interfere with the exchange or use of electronic health information.”

The ONC report Below mostly refers to vendor and financial reasons for promulgating data silos, but I am also interested in other more local reasons such as control and rivalry and misapplication or over-application of privacy protecting legislation particularly at the health service level.

Yes, paper records are also susceptible to breach and blocking