Face Shape-Based Physiognomy in LinkedIn Profiles with Cascade Classifier and K-Means Clustering

The progress of a company is influenced by the excellent performance of its employee. The recruitment process should be done in a correct procedure so that it would not have the potential to harm the company. The improved use of social media can be an aspect to be applied in a recruitment process. LinkedIn is a social media platform that has many users which focuses on the career development aspect. Profile photos are commonly used in social media. In physiognomy, a personality analysis can be carried out based on his/her outward appearance. The profile photo can be an aspect of personality analysis with this knowledge. This research aimed to predict the face shape based on LinkedIn profile photos. A Cascade classifier algorithm with a haar-like feature was used to detect the face area. Dlib library was used to detect face landmarks. K-Means algorithm was used to differentiate the border of hair and facial skin. Indicators of the face shape calculation are the value of face angle, which is the arctangent of the face landmarks matrix; similarity value from the standard deviation calculation between horizontal line 1, 2, and 3; and diameter value which resulted from the standard deviation calculation between horizontal line 2 and vertical line 4. We provide output as face shape from the LinkedIn profile photos. Based on ten profile photo samples, only two predictions were incorrect

Cyber Security

This open access book constitutes the refereed proceedings of the 18th China Annual Conference on Cyber Security, CNCERT 2022, held in Beijing, China, in August 2022. The 17 papers presented were carefully reviewed and selected from 64 submissions. The papers are organized according to the following topical sections: ​​data security; anomaly detection; cryptocurrency; information security; vulnerabilities; mobile internet; threat intelligence; text recognition

Identification and recognition of animals from biometric markers using computer vision approaches: a review

Although classic methods (such as ear tagging, marking, etc.) are generally used for animal identification and recognition, biometric methods have gained popularity in recent years due to the advantages they offer. Systems utilizing biometric markers have been developed for various purposes in animal management, including more effective and accurate tracking of animals, vaccination, disease management, and prevention of theft and fraud. Animals" irises, retinas, faces, muzzle, and body patterns contain unique biometric markers. The use of these markers in computer vision approaches for animal identification and tracking systems has become a highly effective and promising research area in recent years. This review aims to provide a general overview of the latest developments in image processing approaches for animal identification and recognition applications. In this review, we examined in detail all relevant studies we could access from different electronic databases for each biometric method. Afterward, the opportunities and challenges of classical and biometric methods were compared. We anticipate that this study, which conducts a literature review on animal identification and recognition based on computer vision approaches, will shed light on future research towards developing automated systems with biometric methods

Aspects of internet security: identity management and online child protection

This thesis examines four main subjects; consumer federated Internet Identity Management (IdM), text analysis to detect grooming in Internet chat, a system for using steganographed emoticons as ‘digital fingerprints’ in instant messaging and a systems analysis of online child protection. The Internet was never designed to support an identity framework. The current username / password model does not scale well and with an ever increasing number of sites and services users are suffering from password fatigue and using insecure practises such as using the same password across websites. In addition users are supplying personal information to vast number of sites and services with little, if any control over how that information is used. A new identity metasystem promises to bring federated identity, which has found success in the enterprise to the consumer, placing the user in control and limiting the disclosure of personal information. This thesis argues though technical feasible no business model exists to support consumer IdM and without a major change in Internet culture such as a breakdown in trust and security a new identity metasystem will not be realised. Is it possible to detect grooming or potential grooming from a statistical examination of Internet chat messages? Using techniques from speaker verification can grooming relationships be detected? Can this approach improve on the leading text analysis technique – Bayesian trigram analysis? Using a novel feature extraction technique and Gaussian Mixture Models (GMM) to detect potential grooming proved to be unreliable. Even with the benefit of extensive tuning the author doubts the technique would match or improve upon Bayesian analysis. Around 80% of child grooming is blatant with the groomer disguising neither their age nor sexual intent. Experiments conducted with Bayesian trigram analysis suggest this could be reliably detected, detecting the subtle, devious remaining 20% is considerably harder and reliable detection is questionable especially in systems using teenagers (the most at risk group). Observations of the MSN Messenger service and protocol lead the author to discover a method by which to leave digitally verifiable files on the computer of anyone who chats with a child by exploiting the custom emoticon feature. By employing techniques from steganography these custom emoticons can be made to appear innocuous. Finding and removing custom emoticons is a non-trivial matter and they cannot be easily spoofed. Identification is performed by examining the emoticon (file) hashes. If an emoticon is recovered e.g. in the course of an investigation it can be hashed and the hashed compared against a database of registered users and used to support non-repudiation and confirm if an individual has indeed been chatting with a child. Online child protection has been described as a classic systems problem. It covers a broad range of complex, and sometimes difficult to research issues including technology, sociology, psychology and law, and affects directly or indirectly the majority of the UK population. Yet despite this the problem and the challenges are poorly understood, thanks in no small part to mawkish attitudes and alarmist media coverage. Here the problem is examined holistically; how children use technology, what the risks are, and how they can best be protected – based not on idealism, but on the known behaviours of children. The overall protection message is often confused and unrealistic, leaving parents and children ill prepared to protect themselves. Technology does have a place in protecting children, but this is secondary to a strong and understanding parent/child relationship and education, both of the child and parent

Open-Source Face Recognition Frameworks: A Review of the Landscape

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Comprehensive Survey: Biometric User Authentication Application, Evaluation, and Discussion

This paper conducts an extensive review of biometric user authentication literature, addressing three primary research questions: (1) commonly used biometric traits and their suitability for specific applications, (2) performance factors such as security, convenience, and robustness, and potential countermeasures against cyberattacks, and (3) factors affecting biometric system accuracy and po-tential improvements. Our analysis delves into physiological and behavioral traits, exploring their pros and cons. We discuss factors influencing biometric system effectiveness and highlight areas for enhancement. Our study differs from previous surveys by extensively examining biometric traits, exploring various application domains, and analyzing measures to mitigate cyberattacks. This paper aims to inform researchers and practitioners about the biometric authentication landscape and guide future advancements

Cyber Security

This open access book constitutes the refereed proceedings of the 18th China Annual Conference on Cyber Security, CNCERT 2022, held in Beijing, China, in August 2022. The 17 papers presented were carefully reviewed and selected from 64 submissions. The papers are organized according to the following topical sections: ​​data security; anomaly detection; cryptocurrency; information security; vulnerabilities; mobile internet; threat intelligence; text recognition