The Internet is a fantastic resource that is currently being used by a large number of people. It can alter people’s daily routines for better or worse. People can get the latest news, information, purchase products, and services, and interact with people all over the globe with only a few mouse clicks. The Internet’s power, on the other hand, makes it possible to gather massive volumes of data efficiently and cost-effectively. When people aren’t being cautious, they give up a lot of information about themselves. The internet environment differs from more conventional methods of trade and information collecting because of the popularity, convenience, and cheap cost of such information acquisition. People are utilizing the Internet in greater numbers, sometimes without realizing that data about them is being gathered. Others, on the other hand, refrain from making any online purchases due to concerns about privacy and security. Consumers are concerned about their privacy, and businesses should be aware of this. A privacy statement may help alleviate such worries.

The Internet is a global communications network that is mostly unrestrained. As a result, Internet actions originating in other countries are not subject to the laws of that nation. Because of this, we must talk about how privacy protection may be provided in a way that is uniform over the world. The Internet makes it possible to gather large amounts of data quickly and cheaply without obtaining the agreement of the people being tracked. It can follow customers in novel ways, even if they are not aware of it. Consumer preference, interest, and even credit card information are all included in this (Conti, Dehghantanha, Franke, & Watson, 2018).

Concerns about online privacy are among the most depressing for today’s internet users. Using the internet has been linked to a considerable number of privacy problems. People are worried about these threats to their privacy, such as the secret tracking of their website visits, the capture and use of their email addresses and other personal information for marketing or other purposes without consent, and the sale of their personal information to third parties without consent. Additionally, there is the issue of credit card fraud (Lee & Turban, 2001).

The advancement of Internet and database technology has resulted in concerns about data privacy. Individuals’ every touch of the mouse on the Internet, as well as data put into forms or included in existing databases, may be easily connected with transaction records and records of their every transaction on the Internet. When data mining technology and services become more widely available, the privacy concerns that arise become more prominent. Cookies are being used more and more common to identify users on websites, which some people consider to be an invasion of their personal privacy. The user’s age, gender, buying preferences, and even email address will be collected as part of the registration process. The information will be packaged into a cookie and transmitted to the user’s hard disc, where it will be saved for future user identification. When the user navigates to the same page again, the cookie will be sent to the web server by the user’s browser. The information included in the cookie may be used by the webserver to create customized web pages that are tailored to the interests and preferences of the user. In actuality, information about a user’s mobility on a website may also be stored in a cookie, as described above. The biggest source of concern is that all of this is taking place without the individual’s knowledge (Makhdoom, Abolhasan, Lipman, Liu, & Ni, 2018).

Using online tracking technologies, a web bug is a common tool that might constitute a hazard. The privacy of some individuals is violated when they go to a website. Hidden bits of code known as Web Bugs may be used to spy on people’s online activities or steal computer information. The most common kind of web bug is an image exchange format that works in conjunction with cookies to convey data about a visitor’s online activities back to the server. People’s hard discs may be infiltrated by an executable bug, which will place a file to gather information anytime they are connected to the internet. Any document from a user’s computer may be taken without their knowledge by a script-based executable bug that is placed on their machine. Server-based script-based executable bugs are yet another kind to be aware of. They can monitor the online activities of visitors and even take control of the person’s machine remotely from the company’s server. When a user attempts to leave the website, for example, numerous browser windows open (Siby, Maiti, & Tippenhauer, 2017).

Marketers may use cookies to compare their client databases with the ones they acquire from third-party sources, which raises privacy concerns. Through the use of cookies, DoubleClick has already amassed a large database of information on the internet surfing patterns of its customers. This enables cross-references to match data with real-world identities, addresses, and offline mail order purchase histories. In this way, DoubleClick knew not only where individuals went online, but also who they are, where they live, and their phone numbers. Using this database for direct marketing might be the most effective use of resources in the world (Meng, Zhang, Zhu, & Shen, 2018).

Due to a lack of regulatory norms, the Internet has the potential to be used for fraudulent enterprises. Issues about online credit card security are intertwined with privacy concerns. The theft of credit card numbers and other personal information is a common practice among hackers. Credit card fraud might result from unauthorized exposure of credit card information, which is a major issue for many consumers.

Users’ internet activity has been examined for its impact on their privacy as part of this study. Additionally, this study looked at privacy concerns of the general public and how they impact the security measures used by users. The findings of this study will be crucial in developing different tactics and approaches from the perspective of users, which will aid in lessening the long-term impacts of Internet privacy concerns.

……………………………………

The meaning of privacy on the internet ends up being clear once you endeavor to make a mental list of individual things you’re ready to confer to complete strangers — and those you’d don’t really want to. Unmistakably, you do not ever want your clinical records, bank clarifications, or even explicit things from your shipping container to be extensively known. Any person who watched You saw how basic it was for people to get hold of someone’s own special information like road number, sidekicks’ names, tastes, or most adored spots subject to what they transparently shared. The social media accounts and other platforms that one uses on the internet can be secured and everyone needs this privacy and security.

Online security issues range from the information you wouldn’t worry sharing (say, a public electronic media record) and bothering assurance compromises like assigned ads to public embarrassment or breaks that impact your own life.

Web search engines customer following

Web search devices log not simply things you’ve been looking for. They in like manner track locales that you visit later that. Expect that your web search instrument provider fills in as a program, they keep all your search history, also. Search engines can assess your search history, Cookies and  IP address.

Taken together, this information can be used for “profiling”, or making a customer persona subject to the singular’s scrutinizing shopping, and online media tendencies. Notwithstanding different things, customer personas are comprehensively used in tweaking commercials. Profiling transforms into a veritable security issue, nonetheless, when data planning estimations complicate someone’s profile with their really unmistakable information, as this might incite data breaks.

Online media data procuring

Lately, online media security has hit the spotlight with a progression of cases, including the Cambridge Analytica story when they used data to control voters, cyberbullying, and “doxing” (sharing private information unreservedly).

In addition, huge casual networks have suffered data breaks, permitting countless customers to be revealed. Another model is Facebook’s colossal data break that uncovered the singular data of 532 million customers, including their total names, phone numbers, regions, birth dates, profiles, and email addresses.

Web tracking

For the most part, treats are harmless and shockingly obliging. These pieces of code accumulate your scrutinizing information and permit locales to review your login, tendencies, language settings, and various nuances. In any case, cookies might transform into tension concerning a big amount of data accumulated without customer consent. In December 2019, France’s data protection regulator, the Commission Nationale de l’informatique et des libertés (CNIL), concluded that Google and Amazon expected to pay 121 million dollars and 35 million euros for breaking Article 82 of the French Data Protection Act. CNIL fined the two associations for putting the cookies tracking their customer’s PCs without prior consent. Google went fundamentally further and followed customers who had deactivated advertisement personalization.

Security in mobile phone applications

In covid people are using their phones more than they did before. The new App Annie report communicates that the customers seem to spend an average 4 hours 10 minutes in 2020 which is 20% greater from 2019. Extra time spent on adaptable means more web scrutinizing, advancements clicking, and, clearly, application downloads. Accordingly, our applications have gathered huge amounts of valuable information about  us. In any case, we can not be 100% sure what unequivocally those applications know about us. Various applications request location, usernames, phone numbers, or email addresses. In any case, some go further and ask you for risky approvals — information that could make issues accepting it fall into some unsatisfactory hands. It might be access to your phone’s recorder, camera, contacts, or even messages.

A good rule is to consider whether you trust the application provider to keep this information. Accepting that there’s anything you have an abnormal point of view toward, you can deny access, either when the application asks you for approval or later in the application’s settings.

Information extortion

Information extortion that is identifying theft is not new. It has been a crime sometime before the web. However, new advanced technologies have opened up new streets for double-crossers and lawbreakers. Online extortion happens when someone gets to your personally identifiable information (PII)  to commit fraud and crimes.. This information might be your driving license, tax details, bank account details, or whatever else that can be used to mimic you on the web. In the most critical result possible, your information might be sold on the dark web.

To get this information, instigators use the going with these tacts:

Phishing. Criminals behave like dependable contacts, as financial foundations, to trick you into surrendering tricky information or opening harmful attachments.

Malware. Threatening programming or software that can get to your device’s functioning structure and license developers to take your own information

Pharming. Laying hold of information using a virus without your understanding, as often as possible through a fake site

Discarded PCs and phones. Guarantee you totally scour any phone or computer you discard before you sell it or part with it

According to the FTC report, the COVID-19 pandemic has been prepared energy for character cheats, with the amount of ID theft cases dramatically expanding in 2020 standing out from 2019.

All of those privacy and security issues on the web might sound disturbing and can make you feel disturbed, but there are essential advances you can take right now to cut the risk of online coercion.

.

Literature Review

Concerns about Internet privacy are nothing new to some individuals, while others are just overreacting now that they realize how rapidly the Internet is expanding. Online purchasing is no different than going to a physical store. They’re both concerned about privacy, too. To track a person’s internet navigation is like installing a camera in a shop and watching them walk around.

Cyber security threats have risen as a result of people not changing their passwords, not updating their devices, and not encrypting their IoT systems’ critical data. These weak security measures increase the likelihood of a data breach, as well as the possibility of other hazards. Because of insufficient security standards and regulations, the Internet of Things is considered a vulnerable target for cyber-attacks by the majority of security professionals. A plethora of security methods have been implemented to protect Internet of Things devices from cyber-attacks. Security regulations, on the other hand, have not been clearly defined. As a result, end-users were unable to take preventative actions against data breaches and hacks. The malware was created by hackers to infiltrate Internet of Things devices. To get workers or people to divulge private information, they devised several phishing strategies. As a result, high-profile hacks on corporate workstations and personal gadgets often violate users’ privacy (Kelley, Delhagen, & Yuen, 2003). To avoid or neutralize cyber threats, device makers and security specialists need to have a clear understanding of the cyber hazards (Leloglu, 2016).

Increasing cyber security concerns and the availability of crucial IoT system data to hostile applications have been attributed to unintentional password use, a failure to reset passwords, and a lack of device upgrades, among other factors. Data breaches and other risks are more likely with such lax security measures. Weak security standards and rules make IoT a target for cyber assaults, according to most security experts. To safeguard IoT devices from cyber threats, numerous security procedures have been established; nevertheless, security rules have not been well specified. Thus, end-users were unable to use defensive measures to resist cyber-attacks on their data. To hijack IoT devices, hackers created a variety of viruses. Using different phishing methods, they enticed workers and other people to provide personal information. Therefore, high-profile attacks on corporate computers and individual users’ mobile devices typically endanger the privacy of such computers and gadgets. It is possible for device manufacturers and security specialists to collaborate to develop a cyber-attack defense system that is successful in preventing or neutralizing cyber-attacks (Alsmadi & Easttom, 2020).

Even though cookies may be used to identify site visitors, no personal information other than names, addresses, and email addresses can be extracted from them unless the user freely provides it (Hulme, 2004). As a result, the usage of cookies does not pose a significant privacy risk. In reality, some consumers are eager to part over their private information in exchange for special discounts or other advantages (Goodwin, 1991). When personal information is submitted willingly, using cookies for online transactions is no different from ordering from a catalog by mail. Concerns about data abuse are raised by both of them when it reaches the hands of corporations (Alaba, Othman, Hashem, & Alotaibi, 2017).

There’s also an argument that privacy issues on the internet are insignificant. Customers don’t want their data to be used for marketing reasons on the internet. Telephone directories and other sources of consumer information are good places to look for this information. Marketers may generally make use of this data for promotional purposes. These statistics allow marketers to distribute fliers to actual mailboxes. Some people believe that deleting junk email is simpler than deleting junk mail in the actual world. As a result, junk email’s privacy implications are dismissed as irrelevant (Culnan & Armstrong, 1999).

Tamara Dinev et al. focuses on the trade-offs between personal advantages and privacy costs connected with Internet usage. The data imply that trust increases e-commerce. When personal desire and capacity to manage information overcome privacy concerns and perceptions of vulnerability, people are encouraged to utilize the Internet for e-commerce objectives (Dinev & Hart, 2003).

Internet users may improve their privacy by using a variety of measures. The usage of many online services is hampered by privacy worries over their security, according to research. Thus, the importance of information retrieved by online services may be better understood, and an internet user’s permission for information sharing can be granted more easily. The study’s goal is to find out how personality factors affect privacy issues on the internet. Hacking or fraud operations that compromise personal information put users at risk of identity theft or fraud (Pearson, 2013).  Cranor et al. classified the privacy-enabling technologies into two categories: architecture-based privacy and policy-based privacy. Higher-level privacy can be protected via privacy-by-architecture techniques, but they are seldom used due to a lack of legal enforcement and a contradiction between commercial objectives that enable data reduction and local processing. As an alternative, privacy-by-policy methods guarantee just the bare minimum of privacy by using technologies that adhere to the notice and choice concepts. Because privacy-by-architecture ensures strict minimization, privacy-by-policy becomes less necessary, the authors reasoned the authors (Spiekermann & Cranor, 2008) .

Information security and privacy issues are most seriously addressed by internet users. Digital security and privacy is an important aspect of preserving the confidentiality internet user. It has been established that securing the privacy of an individual includes safeguarding the information as well as personal papers inside the system. Data privacy should be regarded by most of the business and the internet service provider in order to protect the secrecy and exploitation of the user’s data. Borka Jerman-Blažič identified potential dangers to safeguard privacy on today’s broad networks, and the technology that may be utilized to combat such attacks. For that the author highlighted some privacy-enhancing technologies (Seničar, Jerman-Blažič, & Klobučar, 2003).

Lukas Malina et al. first categorize several existing technologies for privacy-enhancing and assess their suitability for use in privacy-required services inside the Internet of Things. Also included are classifications of possible privacy concerns, threats, and leakages associated with specific Internet of Things use cases. A simple and creative privacy-preserving framework based on a collection of suitable privacy-enhancing technologies is also proposed in order to secure security and privacy inside Internet of Things services (Malina, Srivastava, Dzurenda, Hajny, & Ricci, 2019).

There were eight privacy design techniques offered by Hoepman: four were data-oriented and four were process-oriented. As early as the idea phase of software development, these methodologies assist IT architects in incorporating privacy by design considerations into their work. Design patterns for privacy-enhancing devices are classified by the tactics, as well. The methodologies described here are useful for both creating privacy-friendly systems and analyzing the privacy effect of already-existing information technology systems (Hoepman, 2014).

Alfred Kobsa argued that Privacy regulations and user concerns have an impact on the implementation of customized systems. It demonstrates that the negative effects are severe, and that present systems will need to be significantly improved. Existing technology can meet the most basic needs. Nevertheless, the majority of privacy regulations set obligations that call for the development of new technologies that have yet to be fully explored. Because user preferences and legal requirements vary so widely, there is no one-size-fits-all answer to privacy concerns, according to the research. As a result, privacy must be dynamically adjusted to meet the demands of each particular user and the jurisdictions in which both the personalized system and the user are located at any one time (Kobsa, 2001).

Online services face the difficulty of maintaining data security while still providing perfect privacy. Authentication and data security are the most difficult issues that internet users must deal with. When it comes to altering people’s perceptions, using the risk control approaches aim to change internet users’ behaviors by educating them about the privacy issue’s consequences. Internet scams, victimization, privacy protection, and online conduct are all topics that will be discussed in depth in this piece of writing. Finally, data encryption for devices should be adopted to improve data security and user privacy on the web. The theatre retention minimization and classification must also be focused on in order to evaluate the data and categorize them in order to minimize data loss as much as feasible. Internet users that utilize two-factor authentication must also adopt strict remote access regulations that demand two-factor authentication as well. Re-authentication of the user’s information for the inactivity of online services is also part of the robust remote access (Huang, Xiang, Chonka, Zhou, & Deng, 2010).

Technologies for exchanging information compromise the privacy of individuals whose data they access. This research employed a broad examination of all Internet security problems. Internet privacy may be preserved thanks to cyber security. Cyber security is our last chance now that the internet is no longer safe from security breaches. The study’s goal is to examine the threats to cyber security posed by cutting-edge Internet technology. There’s also a lot of emphasis on new cyber security technology, ethics, and trends. Cyber security is a means of keeping tabs on criminals who commit crimes online, such as identity theft and data breaches. As a result, cyber security approaches may be used to keep the internet secure while still protecting users’ privacy.

Research Questions

1. To explore the interest of people in providing their information to online websites
2. To see the general behavior of public to prefer privacy over convenience.
3. To see the trust level of public on internet sites.
4. To find the extent of people willing to provide their information online.
5. To take suggestion for securing internet.

Methodology

A survey was used to gather data for empirical testing of the study hypotheses, using the instrument developed by Dinev and Hart to measure privacy concerns about information misuse and intention to trade.

Variables

Usage of internet

To understand the meaning of data security, it is expected to measure the overall web use of people. This covers all the various web based activities like social media activities, online shopping, web banking  and working on the internet of the internet user. This huge number of web-based activities incorporate high security, data assurance and understanding their use reliably will be helpful in choosing the prioritization of the customer to the extent of security.

The purpose/ intention of the internet user.

The purpose of the user to use the internet makes it easy to understand the impacts of internet security breach on him. This is an immediate aftereffect of the break in the web based organizations is significantly fruitful on the customer’s objective in including the web as found in the composing review. This will be assessed by coordinating a survey among our participants  which will be established on questions associated with assurance and data security.

Security frameworks

The distinctive security frameworks that are executed by various relationship to

update the security and assurance of data will be considered as to design the best procedure

of updating security.

Data Collection

The tool that is to be used in a study is very important. The nature of the tool and its coherence with the nature of the study is very important so the tool that is to be used by the researcher in the study should be appropriate and according to the study. The tool makes the result standardised so they can be verified and followed. In our research we were to be linked with the participants that are already very busy with their work, so we were not able to conduct in-depth interviews with them because of lack of time. For conducting research with this kind of participants we need a tool that takes very less time and provides a  huge amount of information to us. For this purpose we choose the questionnaire as a tool of our research. The questionnaires are very interesting to be used and tobe filled. The participants are easily available for filling up the questionnaires and be a part of our study. The questionnaire takes only a few minutes to be filled and is easy to analyse. The questionnaire we used in our study was in the English language. It consisted of 10 questions. The responses were based on Likert scale. The respondents were given in a list mentioning the responses that are, strongly agree, agree, neutral, disagree and strongly disagree. At the top of the questionnaires the section of demographic details was given that consist of two items. One was of age, and the other was of gender. The questions in the questionnaire were direct and short. The questionnaire was especially designed for this research. Questions were kept easy to understand and there was no double barreled question in our questionnaire. The language was kept in English language because of the international nature of the language as the participants we took were diverse and had many differences so the language was to be easy to understand for all of the participants. Our proposed research model will be tested using an online survey created using a Google form. The purpose of our study is to go through the views of the general public to see their concerns related to internet security and their suggestions for the improvements.

Participants

Choosing the participants for a study is an important part of investigation. The participants one in choosing should be related to the field and scope of the study. The participants are chosen on the basis that the change in the variable should cause any difference in their lives. The participants are the main source of information in a study and it is to be confirmed that the information to be gathered should come in a pure condition that will further help us in our analysis. Choosing wrong participants will directly affect the analysis and results eventually. The participants in our study are selected in a very clear and productive way. As our topic of research is totally related to the internet , we selected the participants that use the internet on a daily basis and have a clear idea about the security and privacy issues using the different internet platforms.

Sample Size

The sample of the study will be calculated by using G*power analysis, which is highly suggested for structural equation modeling. However, sample size will be increased to gain maximum reliability and validate data.

Sampling Technique

A network sample also termed a chain referral will be utilised to reach a significantly distributed community of internet users. To gather data, the survey link will be disseminated and publicised on numerous social media channels. The responders will be encouraged to submit the online survey and spread the link to other people located in their network. This procedure will stay ongoing till we acquire the required number of samples for analysis.

Results

In this chapter all the results collected from the participants shall be discussed along with their illustration. All the following results are recorded by the responses of the a[participants that became a part of our study.

Age of the participants

            Analysis

            The participants are taken into the study from a variety of age groups. It includes participants of age 18 to 20, 21 to 24, 25 to 28, 29 to 30 and 30 to 40 years.

Education of the participants

Q 1. Can you live without the internet?

response rate of question No 1

Analysis

About 77.8 % participants marked yes for the first question while 22.2% participants marked No. It means that most of the participants can not live without the internet so the internet is an important part of the lives of most of the people.

1. 2 .How often do you use the internet on a daily basis?

response rate of question No 2

Analysis

77.8% of the participants said that they use the internet for more than 4 hours a day while 14. 8% reported 2-4 hours spent on the internet. only 7.4 % participants reported that they use the internet only for less than 1 hour.

Q.3.Do you think using the Internet for shopping and banking would make your life easier?

response rate of question No 3

Analysis

96.2% participants think that using the internet for baking and shopping online will make Life is easy . while 4.8 participants think inversely.

Q.4.In general, which is more important to you: CONVENIENCE or PRIVACY?

response rate of question No 4

Analys

88.9% participants think that privacy is most important rather than convence. Only 11.1 %       participants think that prvancy is most important.

Q.5. In general, how concerned are you about security on the Internet? (e.g people reading your email, finding out what websites you visit, etc.) Keep in mind that “security” can mean privacy, confidentiality, and/or proof of identity for you or for someone else.

response rate of question No 5

Analysis

About 33.3 % are somewhat concerned about their privacy being breached while only 22.2 % are very concerned and 7.4% of the participants are totally unconcerned about all of this.

Q.6.How concerned are you about security in relation to making purchases or banking over the Internet? Keep in mind that “security” can mean privacy, confidentiality, and/or proof of identity for you or for someone else.

response rate of question No 6

Analysis

42.% participants are somewhat concerned about the security issues while they do online shopping. 23.1% participants are very much concerned about it while 15.4%  are a little concerned about it.

Q.7 One thing that makes it difficult to study Internet security is people’s and business’ reluctance to report security problems for fear of causing more problems for themselves. In addition, it is not always clear where they should be reported. One idea is to have a “clearinghouse” where security problems can be studied and tracked.

Would you report a security break-in of your personal machine or network to a clearinghouse that maintains your anonymity?

response rate of question No 7

Analysis

85.2% participants reported that they will report a security break when they have to maintain their anonymity while 14.8% participants responded that they shall not report any security break.

Q.8 Privacy practice disclosure indicates that a site willingly discloses to the user what it plans to do with information collected from the user. Can you easily accept it?

response rate of question No 8

Analysis

The 66.7% participants will accept it when a privacy practice disclosure indicates that a site willingly discloses to the user what it plans to do with information collected from the user. while 33.3% participants will accept it.

Q.9 Have you ever had your credit card number stolen (either online or offline)?

response rate of question No 9

Analysis

65.4 % participants indicated that they had not got their credit card number stolen while 34.6% participants indicated that they had got their credit card number stolen.

Q.10 Are you willing to use your credit card on the web?

response rate of question No 10

Analysis

About 66.7% participants are willing to use credit cards on the internet while 33.3%participants are not willing to use their credit card online.

Data Analysis

SPSS will be used for descriptive statistical analysis, i.e. frequency, mean and standard deviation. Inferential data analysis will be done through PLS-SEM and Smart PLS3 (measurement model and structural model).

Discussion and conclusion

The aftereffects of the review showed numerous significant data and connections between the review factors, the most noticeable of which was the Approximately, 93.7% among them don’t uncover their private data on the web. In this way, we present some significant discoveries and

ideas. The pace of consummation has been 100% for this review. Out of 200 respondents, every one of them have addressed the posed sixteen inquiries out of their assets. Roughly 56 members are male in sexual orientation, and 144 are female. It implies that the greater part rates of members are female, where they address 72% to 28% of male. Among them, 36 are from the age-bunch between 18 and 25. 48 members are from the age-bunch somewhere in the range of 26 and 30. 26 individuals are from the age group somewhere in the range of 31 and 35. Somewhere in the range of 36 and 40, 35 members have been there. Over the 41 age range, 55 members. The outcomes demonstrated the high instructive level of the example, which gives the consequences of the review test extraordinary significance because of the attention to online security and security.32 Protection concerns are a hindrance to improvement. Also, numerous clients confronted extreme challenges with respect to web and information security while utilizing the Internet. An issue can’t be disregarded in light of the fact that protection concerns decrease web use. The key is that organizations on the web need to oversee and meet their customers ‘assumptions where protection is concerned. They ought to know that shoppers are searching for security assurance and a protection articulation can serve to ease purchasers ‘concerns. As a large number of the examples are not completely persuaded of the cutting edge information security framework. This implies that there are significant issues with respect to ongoing regulation and guidelines connected with penetrating network safety .Encryption of information can help clients from getting shielded from information spillage and protection issues. it implies stricter security can channel the negative goals from various web clients. We suggest that since the example results showed that the Internet is utilized in excess of multiple times each day (53%), current issues and difficulties ought to be considered as promising circumstances for improvement that should be accomplished inside a thorough cycle that incorporates security destinations configuration stages and the viable and utilization of normalized security arrangements in the creation stages, end clients additionally need to comprehend the principal motivation behind the gadget and how to meet their prerequisites under severe oversight and investigation to consistently deal with the dangers.Circling back to the following of data might include some sort of “security loss of motion” at the individual level. Individuals may consistently feel that their own data might be undermined. Since disarray seems, by all accounts, to be related with sensations of dread and high danger, endeavors ought to be made to teach the general population with believability about Internet protection.

Taking everything into account, we suggest require the improvement of new trust expanding viewpoints on information insurance, both from the lawmaker, site and from the engineers of protection upgrade technologie

References

Alaba, F. A., Othman, M., Hashem, I. A. T., & Alotaibi, F. (2017). Internet of Things security: A survey. Journal of Network and Computer Applications, 88, 10–28.

Alsmadi, I., & Easttom, C. (2020). The NICE Cyber Security Framework. Springer.

Conti, M., Dehghantanha, A., Franke, K., & Watson, S. (2018). Internet of Things security and forensics: Challenges and opportunities. Elsevier.

Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness, and impersonal trust: An empirical investigation. Organization Science, 10(1), 104–115.

Dinev, T., & Hart, P. (2003). PRIVACY CONCERNS AND INTERNET USE–A MODEL OF TRADE-OFF FACTORS. In Academy of Management Proceedings (Vol. 2003, pp. D1–D6). Academy of Management Briarcliff Manor, NY 10510.

Goodwin, C. (1991). Privacy: Recognition of a consumer right. Journal of Public Policy & Marketing, 10(1), 149–166.

Hoepman, J.-H. (2014). Privacy design strategies. In IFIP International Information Security Conference (pp. 446–459). Springer.

Huang, X., Xiang, Y., Chonka, A., Zhou, J., & Deng, R. H. (2010). A generic framework for three-factor authentication: Preserving security and privacy in distributed systems. IEEE Transactions on Parallel and Distributed Systems, 22(8), 1390–1397.

Hulme, G. V. (2004). Microsoft releases of security updates. Information Week, 19, 34–36.

Kelley, C., Delhagen, K., & Yuen, E. H. (2003). Online Credit Card Security Confidence Erodes, Forrester Research, July 25, 2003.

Kobsa, A. (2001). Tailoring privacy to users’ needs. In International Conference on User Modeling (pp. 301–313). Springer.

Lee, M. K. O., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75–91.

Leloglu, E. (2016). A review of security concerns in Internet of Things. Journal of Computer and Communications, 5(1), 121–136.

Makhdoom, I., Abolhasan, M., Lipman, J., Liu, R. P., & Ni, W. (2018). Anatomy of threats to the internet of things. IEEE Communications Surveys & Tutorials, 21(2), 1636–1675.

Malina, L., Srivastava, G., Dzurenda, P., Hajny, J., & Ricci, S. (2019). A privacy-enhancing framework for Internet of Things services. In International Conference on Network and System Security (pp. 77–97). Springer.

Meng, Y., Zhang, W., Zhu, H., & Shen, X. S. (2018). Securing consumer IoT in the smart home: Architecture, challenges, and countermeasures. IEEE Wireless Communications, 25(6), 53–59.

Pearson, S. (2013). Privacy, security and trust in cloud computing. In Privacy and security for cloud computing (pp. 3–42). Springer.

Seničar, V., Jerman-Blažič, B., & Klobučar, T. (2003). Privacy-enhancing technologies—approaches and development. Computer Standards & Interfaces, 25(2), 147–158.

Siby, S., Maiti, R. R., & Tippenhauer, N. O. (2017). IoTScanner: Detecting privacy threats in IoT neighborhoods. In Proceedings of the 3rd ACM International Workshop on IoT Privacy, Trust, and Security (pp. 23–30).

Spiekermann, S., & Cranor, L. F. (2008). Engineering privacy. IEEE Transactions on Software Engineering, 35(1), 67–82.

Abstract

The proposed survey would look at internet privacy problems and concerns of general public related to these issues and also their suggestions. Data will be collected online individuals picked randomly online. The questionnaire has 12 close-ended and open-ended questions. The result is measured through SPSS analysis of the data. General trend of the trust of people on internet security is seen. Also suggestions were taken in the form of qualitative data. The finding would therefore help to know the concerns of people related to internet security.

Contents

Abstract                                                                                                                                                                                            2

Introduction                                                                                                                                                                                    4

Literature Review                                                                                                                                                                         7

Research Questions                                                                                                                                                                   12

Methodology                                                                                                                                                                               12

Data Collection                                                                                                                                                                        13

Participants                                                                                                                                                                              13

Sample Size                                                                                                                                                                              13

Sampling Technique                                                                                                                                                             13

Data Analysis                                                                                                                                                                           13

References                                                                                                                                                                                    14

Appendix                                                                                                                                                                                       16