Journal Article•
User Profiling: A Privacy Issue in Online Public Network
TL;DR: A relationship hiding technique is proposed to protect the user from profiling and the proposed and the state of the art sharing techniques are taking almost same processing time.
Abstract: The internet users, especially those who are using the Online Public Network (OPN) have concern about their private data. The OPNs are collecting user information from their profiles which are provided during the account creation and linking these attributes (for example age, gender and location) to the user explicitly posted data. In this way the OPNs collect and analyze the user’s psychological and behavioral characteristics to create user profiles. These user profiles are used for advertisement purposes and can be provided to third party for financial profit, but these profiles have private information about users which could be used for malicious purposes. In this paper, a relationship hiding technique is proposed to protect the user from profiling. The relationship between the user account profile data and the user explicit posted data has been hidden using the data encryption to protect user privacy, but the encryption hides the information even from the legitimate users. In order to allow the legitimate users to see the shared contents, a collaborative sharing technique is proposed. The collaborative sharing technique is implemented and tested as a proof of concept which gives satisfactory results. The proposed and the state of the art sharing techniques are taking almost same processing time.
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TL;DR: In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.
Abstract: The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.
53 citations
01 Jan 2021
TL;DR: Various data mining algorithms and machine learning algorithms are revealed, which can be help to create some specific schema of different cyberattacks to train expert system to alert and decision-making process.
Abstract: Cybersecurity deals with various types of cybercrimes, but it is essential to identify the similarities in existing cybercrimes using data mining and machine learning technologies This review paper reveals various data mining algorithms and machine learning algorithms, which can be help to create some specific schema of different cyberattacks Machine learning algorithms can be helpful to train system to identify anomaly, specific patterns to predict the cyberattacks Data mining plays a critical role to provide a predictive solution to rectify possible cybercrime and modus operandi and explore defense system against them This is the era of big data, so it is very difficult to analyze and investigate the irregular activity on cyberspace Data mining methods, while allowing the system to analyze hidden knowledge and to train expert system to alert and decision-making process This review paper explores various data mining method like classification, association, and Clustering, while machine learning includes different methods like supervised, semi-supervised, and unsupervised learning methods
11 citations
TL;DR: The history of online social networking is presented and classifies their types; it also discusses cyber threats on social networking websites and puts forward a policy and action plan to counter threats to social networks in the future.
Abstract: Social networks are websites that enable people to communicate with others, express their opinions, and share their thoughts, experiences, and interests. It also contributes to job creation and facilitates the marketing of various products and services. A cyber threat is the malicious attempt to access a computer network through a data communications pathway by illegal means; they can be intended or unintended, direct or indirect, and are usually carried out by hackers, virus code writers, industrial spies, organized crime unions, vengeful employees and spiteful intruders. This paper presents the history of online social networking and classifies their types; it also discusses cyber threats on social networking websites and puts forward a policy and action plan to counter threats to social networks in the future.
10 citations
Cites background from "User Profiling: A Privacy Issue in ..."
...Online service providers perform user profiling for commercial purposes; however, it can open up the way for privacy leakage [23]....
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TL;DR: A scalable group key management protocol (SGKMP) is proposed, which requires only two rounds to complete the group key generation process, irrespective of group size and it is secure from the eavesdropper in the middle.
7 citations
TL;DR: This article presents a system for retrieving personal information from the Internet on the basis of several input criteria that is capable of differentiating the information of different people with the same name by using artificial intelligence techniques.
Abstract: The advances in data computing and analysis methodologies have contributed to the added value of data. Several years ago it was difficult to imagine that we would ever be able to extract such a large amount of information from the Internet. All this thanks to the ability of current techniques to process large volumes of data in a short period of time. The Internet provides access to a large amount of unstructured or unlabelled data, which are hard to retrieve for any human due to the lack of knowledge of the available sources of information. Moreover, in many cases people are unaware of the online availability of their personal data. This article presents a system for retrieving personal information from the Internet on the basis of several input criteria. The system is capable of differentiating the information of different people with the same name by using artificial intelligence techniques. In the conducted case study, the information has been gathered from sources containing information about people living in Spain, but it could be adapted to the specific sources of information of other countries. The system has been validated in a case study which included several participants and the obtained results have been quite satisfactory.
6 citations