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At present, smartphones are embedded with accelerometers, gyroscopes, magnetometers and WiFi sensors. Most researchers have delved into the use of these sensors for localization. However, there are still many problems in reducing fingerprint mismatching and fusing these positioning data. The purpose of this paper is to improve positioning accuracy by reducing fingerprint mismatching and designing a weighted fusion algorithm.

For the problem of magnetic mismatching caused by singularity fingerprint, derivative Euclidean distance uses adjacent fingerprints to eliminate the influence of singularity fingerprint. To improve the positioning accuracy and robustness of the indoor navigation system, a weighted extended Kalman filter uses a weighted factor to fuse multisensor data.

The scenes of the teaching building, study room and office building are selected to collect data to test the algorithm’s performance. Experiments show that the average positioning accuracies of the teaching building, study room and office building are 1.41 m, 1.17 m, and 1.77 m, respectively.

The algorithm proposed in this paper effectively reduces fingerprint mismatching and improve positioning accuracy by adding a weighted factor. It provides a feasible solution for indoor positioning.

Biometric scans using fingerprints are widely used for security purposes. Eventually, for authentication purposes, fingerprint scans are not very reliable because they can be faked by obtaining a sample of the fingerprint of the person. There are a few spoof detection techniques available to reduce the incidence of spoofing of the biometric system. Among them, the most commonly used is the binary classification technique that detects real or fake fingerprints based on the fingerprint samples provided during training. However, this technique fails when it is provided with samples formed using other spoofing techniques that are different from the spoofing techniques covered in the training samples. This paper aims to improve the liveness detection accuracy by fusing electrocardiogram (ECG) and fingerprint.

In this paper, to avoid this limitation, an efficient liveness detection algorithm is developed using the fusion of ECG signals captured from the fingertips and fingerprint data in Internet of Things (IoT) environment. The ECG signal will ensure the detection of real fingerprint samples from fake ones.

Single model fingerprint methods have some disadvantages, such as noisy data and position of the fingerprint. To overcome this, fusion of both ECG and fingerprint is done so that the combined data improves the detection accuracy.

System security is improved in this approach, and the fingerprint recognition rate is also improved. IoT-based approach is used in this work to reduce the computation burden of data processing systems.

Fingerprints and blood samples are important for the identification of individuals and criminals. The present study aims to identify the predominant fingerprint patterns and the association between the fingerprint patterns and ABO–Rh blood groups in Omani population.

A cross-sectional study was conducted on 200 Omani individuals aged 18 years (104 males and 96 females). The imprints of all right and left-hand fingers were taken, and the types of the fingerprints were determined using a standard protocol. The blood group of all the subjects was recorded. Chi-square test was performed to identify the association between the fingerprint patterns and the ABO and Rh blood groups.

The loop fingerprint pattern was the most common in Omani subjects (49.4%), followed by whorl (44.9%) and arch (5.7%) pattern. A significant association (p < 0.001) was found between gender and fingerprint pattern. The loop was the highest occurring pattern in the females (54.6%), while the whorl was more in males (50.0%). The whorl pattern was the most common in the AB+ and O− groups. The loop was a predominant pattern in the A+, A−, B+, B− and O+ groups. The Chi-square test also revealed a significant correlation between different fingerprint patterns and blood groups of the subjects (p < 0.001).

The present study is an outcome of undergraduate student's research project thesis for the Doctor of Medicine (MD) program. The results of the present study may help in creating a data bank for biometrics, which can be useful for diagnosing associated diseases and also help in identification of individuals.

To devise a biometric‐based mechanism for enhancing security of private keys used in cryptographic applications.

To enhance security of a private key, we propose a scheme that regenerates a user's private key by taking a genuine user's password, fingerprint and a valid smart card. Our scheme uses features extracted from fingerprint along with public key cryptography, cryptographic hash functions and Shamir secret sharing scheme in a novel way to achieve our desired objectives.

Despite changes in the fingerprint pattern each time it is presented, our scheme is sufficiently robust to regenerate a constant private key. As compared to conventional methods of storing a private key merely by password‐based encryption, our scheme offers more security as it requires a genuine user's password, fingerprint and a valid smart card. Key lengths up to 1024‐bit or even higher can be regenerated making the scheme compatible with the current security requirements of public key cryptosystems.

Minutia points used for image alignment can be incorporated in the key regeneration algorithm for stronger user authentication. In this case, some alternative technique will be required for image alignment.

The robustness of our scheme depicts its use in practical systems where there are variations in fingerprint patterns because of sensor noise and alignment issues.

In this paper, we have demonstrated a novel idea of regenerating the private key of a user by using fingerprint, password and a smart card. The basic aim is to provide more security to key storage as compared to traditional methods that uses password‐based encryption for secure storage of private keys.

This paper aims to extend the technology acceptance model (TAM) to explore the factors influencing a hotel customer’s intention to use a fingerprint system instead of a traditional keycard system and the moderating factors (i.e. gender and age) on the relationships between the proposed factors and the customer’s intention to use fingerprint technology. When hotels add new technologies, the potential vulnerability of their systems also increases. Underestimating such risks can possibly result in massive losses from identity theft and related fraud for hoteliers. Customers who are aware of these risks may become more open to innovative methods of identification or verification, such as biometrics.

The online survey instrument was developed based on TAMs. The authors collected complete 526 responses from hotel customers and tested the hypotheses using structural equation modeling.

This study found seven factors (i.e. perceived usefulness, perceived ease of use, subjective norm, perceived convenience, perceived data security, perceived property security and personal concerns) which significantly influence a hotel customer’s intention to use fingerprint technology. Gender and age played important moderating roles in the relationships between some of these factors and the intention to use.

Recommendations are made as to how hotels can benefit from the implementation of biometrics, particularly fingerprint systems. For example, a hotel’s marketing campaign can be more effective by emphasizing the advantages of fingerprint technology related to “data security and convenience” for younger consumers (i.e. Gen X and Gen Y).

Both educators and practitioners will benefit from the findings of this empirical study, as there are very few published studies on a customer’s fingerprint technology acceptance in the hotel context.

The purpose of this project was to determine if there was a difference in the longevity of the latent fingerprints of children vs adults. It is generally believed that a subject’s age does not affect the evaporation rates of fingerprints. However, based upon a recent criminal investigation of child abduction, it was hypothesized that children’s latent fingerprints do not last as long as those of adults. Participation in this study was voluntary and informed consent obtained. A total of 97 subjects pressed their fingers on glass slides and their latent fingerprints were lifted one, three, five and seven days later. A comparison was then made between the longevity of the prints of children vs adults. Almost all of the adult prints were still present on day seven. Of the children’s prints, 20 percent were unclear on day three; 54 percent were unclear on day five; and 76 percent were unclear on day seven. This has implications for law enforcement and forensic science in that time may become a critical variable in criminal investigations requiring the lifting of latent fingerprints of children.

Browser fingerprinting is increasingly being used for online tracking of users, and, unlike the use of cookies, is almost impossible for users to control. This has a major negative impact on online privacy. Despite the availability of a range of fingerprinting countermeasures as well as some limited attempts by browser vendors to curb its effectiveness, it remains largely uncontrolled. The paper aims to discuss this issue.

This paper provides the first comprehensive and structured discussion of measures to limit or control browser fingerprinting, covering both user-based and browser-based techniques.

This study discusses the limitations of counter browser fingerprinting measures and the need for browser vendor support in controlling fingerprinting. Further, a somewhat counterintuitive possible new browser identifier is proposed which could make cookies and fingerprint-based tracking redundant; the need for, and possible effect of, this feature is discussed.

This study provides the first comprehensive and structured discussion of measures to limit or control browser fingerprinting. Also, it proposes a new browser identifier that could make cookies and fingerprint-based tracking redundant.

The purpose of this paper is to show that a fingerprinting code is a set of code words that are embedded in each copy of a digital object, with the purpose of making each copy unique. If the fingerprinting code is c‐secure, then the decoding of a pirate word created by a coalition of at most c dishonest users, will expose at least one of the guilty parties.

The paper presents a systematic strategy for collusions attacking a fingerprinting scheme. As a particular case, this strategy shows that linear codes are not good fingerprinting codes. Based on binary linear equidistant codes, the paper constructs a family of fingerprinting codes in which the identification of guilty users can be efficiently done using minimum distance decoding. Moreover, in order to obtain codes with a better rate a 2‐secure fingerprinting code is also constructed by concatenating a code from the previous family with an outer IPP code.

The particular choice of the codes is such that it allows the use of efficient decoding algorithms that correct errors beyond the error correction bound of the code, namely a simplified version of the Chase algorithms for the inner code and the Koetter‐Vardy soft‐decision list decoding algorithm for the outer code.

The paper presents a fingerprinting code together with an efficient chasing algorithm.

It is increasingly difficult to ignore the importance of anonymity on the internet. Tor has been proposed as a reliable way to keep our identity secret from governments and organizations. This research evaluates its ability to protect our activity on the Web.

Using traffic analysis over ACK packets among others, fingerprints of websites can be created and later on used to recognise Tor traffic.

Tor does not add enough entropy to HTTP traffic, which allows us to recognise the access to static websites without breaking Tor's cryptography.

This work shows that the method presented behaves well with a limited set of fingerprints. Further research should be performed on its reliability with larger sets.

Tor has been used by political dissidents and citizens in countries without freedom of speech to access banned websites such as Twitter or Facebook. This paper shows that it might be possible for their countries to know what they have done.

This paper shows that while Tor does a good work keeping the content of our communication, it is weak protecting the identity of the website being accessed.