Biblio

A biometric system is a developing innovation which is utilized in different fields like forensics and security system. Finger recognition is the innovation that confirms the personality of an individual which relies upon the way that everybody has unique fingerprints. Fingerprint biometric systems are smaller in size, simple to utilize and have low power. This proposed study focuses on fingerprint biometric systems and how such a system would be implemented. If implemented, this system would have multifactor authentication strategies and improvised features based on encryption algorithms. The scanner that will be used is Biometric Fingerprint Sensor that is connected to system which determines the authorization and access control rights. All user access information is gathered by the system where the administrators can retrieve and analyse the information. This system has function of being up to date with the data changes like displaying the name of the individual for controlling security of the system.

The bioinformatics features are collected by pattern recognition technology, and the digital coding and format conversion of the feature data are realized by using the theory of topological group transformation. Authentication and Signature based on Zero Knowledge Proof Technology can be used as the trusted credentials of cloud platform and cannot be forged, thus realizing trusted and secure access.

In this paper, a novel DNA based computing method is proposed for encryption of biometric color(face)and gray fingerprint images. In many applications of present scenario, gray and color images are exhibited major role for authenticating identity of an individual. The values of aforementioned images have considered as two separate matrices. The key generation process two level mathematical operations have applied on fingerprint image for generating encryption key. For enhancing security to biometric image, DNA computing has done on the above matrices generating DNA sequence. Further, DNA sequences have scrambled to add complexity to biometric image. Results of blending images, image of DNA computing has shown in experimental section. It is observed that the proposed substitution DNA computing algorithm has shown good resistant against statistical and differential attacks.

Instant messaging is an application that is widely used to communicate. Based on the wearesocial.com report, three of the five most used social media platforms are chat or instant messaging. Instant messaging was chosen for communication because it has security features in log in using a One Time Password (OTP) code, end-to-end encryption, and even two-factor authentication. However, instant messaging applications still have a vulnerability to account theft. This account theft occurs when the user loses his cellphone. Account theft can happen when a cellphone is locked or not. As a result of this account theft, thieves can read confidential messages and send fake news on behalf of the victim. In this research, instant messaging application security will be applied using hybrid encryption and two-factor authentication, which are made interrelated. Both methods will be implemented in 2 implementation designs. The implementation design is securing login and securing sending and receiving messages. For login security, QR Code implementation is sent via email. In sending and receiving messages, the message decryption process will be carried out when the user is authenticated using a fingerprint. Hybrid encryption as message security uses RSA 2048 and AES 128. Of the ten attempts to steal accounts that have been conducted, it is shown that the implementation design is proven to reduce the impact of account theft.

Mechanical faults of Gas Insulated Switchgear (GIS) often occurred, which may cause serious losses. Detecting vibration signal was effective for condition monitoring and fault diagnosis of GIS. The vibration characteristic of GIS in service was detected and researched based on a developed testing system in this paper, and feature fingerprint extraction method was proposed to evaluate vibration characteristics and diagnose mechanical defects. Through analyzing the spectrum of the vibration signal, we could see that vibration frequency of operating GIS was about 100Hz under normal condition. By means of the wavelet transformation, the vibration fingerprint was extracted for the diagnosis of mechanical vibration. The mechanical vibration characteristic of GIS including circuit breaker and arrester in service was detected, we could see that the frequency distribution of abnormal vibration signal was wider, it contained a lot of high harmonic components besides the 100Hz component, and the vibration acoustic fingerprint was totally different from the normal ones, that is, by comparing the frequency spectra and vibration fingerprint, the mechanical faults of GIS could be found effectively.

Most anti-collusion audio fingerprinting schemes are aiming at finding colluders from the illegal redistributed audio copies. However, the loss caused by the redistributed versions is inevitable. In this letter, a novel fingerprinting scheme is proposed to eliminate the motivation of collusion attack. The audio signal is transformed to the frequency domain by the Fourier transform, and the coefficients in frequency domain are reversed in different degrees according to the fingerprint sequence. Different from other fingerprinting schemes, the coefficients of the host media are excessively modified by the proposed method in order to reduce the quality of the colluded version significantly, but the imperceptibility is well preserved. Experiments show that the colluded audio cannot be reused because of the poor quality. In addition, the proposed method can also resist other common attacks. Various kinds of copyright risks and losses caused by the illegal redistribution are effectively avoided, which is significant for protecting the copyright of audio.

The Global Positioning System (GPS) can determine the position of any person or object on earth based on satellite signals. But when inside the building, the GPS cannot receive signals, the indoor positioning system will determine the precise position. How to achieve more precise positioning is the difficulty of an indoor positioning system now. In this paper, we proposed an ultra-wideband fingerprinting positioning method based on a convolutional neural network (CNN), and we collect the dataset in a room to test the model, then compare our method with the existing method. In the experiment, our method can reach an accuracy of 98.36%. Compared with other fingerprint positioning methods our method has a great improvement in robustness. That results show that our method has good practicality while achieves higher accuracy.

The fingerprint sensor based on pMUTs was reported [1]. Spatial resolution of the image depends on the size of the acoustic source when a plane wave is used. If the size of the acoustic source is smaller, piezoelectric films with high dielectric constant are required. In this study, in order to obtain small acoustic source, we proposed Pb(Zrx Th-x)O3 (PZT) epitaxial transducers with high dielectric constant. PbTiO3 (PTO) epitaxial films were grown on conductive La-SrTiO3 (STO) substrate by RF magnetron sputtering. Longitudinal wave conversion loss of PTO transducers was measured by a network analyzer. The thermoplastic elastomer was used instead of real fingerprint. We confirmed that conversion loss of piezoelectric film/substrate structure was increased by contacting the elastomer due the change of reflection coefficient of the substrate bottom/elastomer interface. Minimum conversion loss images were obtained by mechanically scanning the soft probe on the transducer surface. We achieved the detection of the fingerprint phantom based on the elastomer in the GHz.

Bloom filters (BFs) are fast and space-efficient data structures used for set membership queries in many applications. BFs are required to satisfy three key requirements: low space cost, high-speed lookups, and fast updates. Prior works do not satisfy these requirements at the same time. The standard BF does not support deletions of items and the variants that support deletions need additional space or performance overhead. The state-of-the-art cuckoo filters (CF) has high performance with seemingly low space cost. However, the CF suffers a critical issue of varying space cost per item. This is because the exclusive-OR (XOR) operation used by the CF requires the total number of buckets to be a power of two, leading to the space inflation. To address the issue, in this paper we propose a scalable variant of the cuckoo filter called additive and subtractive cuckoo filter (ASCF). We aim to improve the space efficiency while sustaining comparably high performance. The ASCF uses the addition and subtraction (ADD/SUB) operations instead of the XOR operation to compute an item's two candidate bucket indexes based on its fingerprint. Experimental results show that the ASCF achieves both low space cost and high performance. Compared to the CF, the ASCF reduces up to 1.9x space cost per item while maintaining the same lookup and update throughput. In addition, the ASCF outperforms other filters in both space cost and performance.

In VANETs, pseudonyms are often used to replace the identity of vehicles in communication. When vehicles drive out of the network or misbehave, their pseudonym certificates need to be revoked by the certificate authority (CA). The certificate revocation lists (CRLs) are usually used to store the revoked certificates before their expiration. However, using CRLs would incur additional storage, communication and computation overhead. Some existing schemes have proposed to use Bloom Filter to compress the original CRLs, but they are unable to delete the expired certificates and introduce the false positive problem. In this paper, we propose an improved pseudonym certificates revocation scheme, using Cuckoo Filter for compression to reduce the impact of these problems. In order to optimize deletion efficiency, we propose the concept of Certificate Expiration List (CEL) which can be implemented with priority queue. The experimental results show that our scheme can effectively reduce the storage and communication overhead of pseudonym certificates revocation, while retaining moderately low false positive rates. In addition, our scheme can also greatly improve the lookup performance on CRLs, and reduce the revocation operation costs by allowing deletion.

With the popularity of the Internet and mobile intelligent terminals, the number of mobile applications is exploding. Mobile intelligent terminals trend to be the mainstream way of people's work and daily life online in place of PC terminals. Mobile application system brings some security problems inevitably while it provides convenience for people, and becomes a main target of hackers. Therefore, it is imminent to strengthen the security detection of mobile applications. This paper divides mobile application security detection into client security detection and server security detection. We propose a combining static and dynamic security detection method to detect client-side. We provide a method to get network information of server by capturing and analyzing mobile application traffic, and propose a fuzzy testing method based on HTTP protocol to detect server-side security vulnerabilities. Finally, on the basis of this, an automated platform for security detection of mobile application system is developed. Experiments show that the platform can detect the vulnerabilities of mobile application client and server effectively, and realize the automation of mobile application security detection. It can also reduce the cost of mobile security detection and enhance the security of mobile applications.

With the popularity of smart devices and the widespread use of the Wi-Fi-based indoor localization, edge computing is becoming the mainstream paradigm of processing massive sensing data to acquire indoor localization service. However, these data which were conveyed to train the localization model unintentionally contain some sensitive information of users/devices, and were released without any protection may cause serious privacy leakage. To solve this issue, we propose a lightweight differential privacy-preserving mechanism for the edge computing environment. We extend ε-differential privacy theory to a mature machine learning localization technology to achieve privacy protection while training the localization model. Experimental results on multiple real-world datasets show that, compared with the original localization technology without privacy-preserving, our proposed scheme can achieve high accuracy of indoor localization while providing differential privacy guarantee. Through regulating the value of ε, the data quality loss of our method can be controlled up to 8.9% and the time consumption can be almost negligible. Therefore, our scheme can be efficiently applied in the edge networks and provides some guidance on indoor localization privacy protection in the edge computing.

Biometrics manages the computerized acknowledgment of people dependent on natural and social attributes. The example acknowledgment framework perceives an individual by deciding the credibility of a particular conduct normal for person. The primary rule of biometric framework is recognizable proof and check. A biometric confirmation framework use fingerprints, face, hand geometry, iris, and voice, mark, and keystroke elements of a person to recognize an individual or to check a guaranteed character. Biometrics authentication is a form of identification and access control process which identify individuals in packs that are under reconnaissance. Biometric security system increase in the overall security and individuals no longer have to deal with lost ID Cards or forgotten passwords. It helps much organization to see everyone is at a certain time when something might have happened that needs reviewed. The current issues in biometric system with individuals and many organization facing are personal privacy, expensive, data's may be stolen.

Remote authentication via biometric features has received much attention recently, hence the security of biometric data is of great importance. Here a crypto-steganography method applied for the protection of biometric data is implemented. It include semantic segmentation, chaotic encryption, data hiding and fingerprint recognition to avoid the risk of spoofing attacks. Semantically segmented image of the person to be authenticated is used as the cover image and chaotic encrypted fingerprint image is used as secret image here. Chaotic encrypted fingerprint image is embedded into the cover image using Integer Wavelet Transform (IWT). Extracted fingerprint image is then compared with the fingerprints in database to authenticate the person. Qualified Significant Wavelet Trees (QSWT`s) of the cover image act as the target coefficients to insert the secret image. IWT provide both invisibility and resistance against the lossy transmissions. Experimental result shows that the semantic segmentation reduces the bandwidth efficiently. In addition, chaotic encryption and IWT based data hiding increases the security of the transmitted biometric data.

Source camera attribution of digital images has been a hot research topic in digital forensics literature. However, the thermal cameras and the radiometric data they generate stood as a nascent topic, as such devices are expensive and tailored for specific use-cases - not adapted by the masses. This has changed dramatically, with the low-cost, pluggable thermal-camera add-ons to smartphones and similar low-cost pocket-size thermal cameras introduced to consumers recently, which enabled the use of thermal imaging devices for the masses. In this paper, we are going to investigate the use of an established source device attribution method on radiometric data produced with a consumer-level, low-cost handheld thermal camera. The results we represent in this paper are promising and show that it is quite possible to attribute thermal images with their source camera.

There are two main contributions in this paper: Firstly, by analyzing the frequency domain features and Mel domain features, we can identify footstep events and non-footstep events. Secondly, we compared the two footstep sound signals of the same person in frequency domain under different experimental conditions, finding that almost all of their peak frequencies and trough frequencies in the main frequency band are respectively corresponding one-to-one. However for the two different people, even under the same experimental conditions, it is difficult to have the same peak frequencies and trough frequencies in the main frequency band of their footstep sound signals. Therefore, this feature of footstep sound signals can be used to identify different people.

iOS is one of the most secure operating systems based on policies created and enforced by Apple. Though not impervious or free from vulnerabilities, iOS has remained resilient to many attacks partially based on lower market share of devices, but primarily because of tight controls placed on iOS development and application deployment. Locked iOS devices pose a specific hard problem for both law enforcement and corporate IT dealing with malicious insiders or intrusion scenarios. The need to recover forensic data from locked iOS devices has been of public interest for some time. In this paper, we describe a case study analysis of the iPhone 5c model and our attempts to use electromagnetic (EM) fault-injection as a side channel means to unlock the device. Based on our study, we report on our unsuccessful attempts in unlocking a locked iPhone 5c using this side channel-based approach. As a contribution, we provide initial analysis of the iPhone 5c processor's spectral mapping under different states, a brief survey of published techniques related to iPhone unlock scenarios, and a set of lessons learned and recommended best practices for other researchers who are interested in future EM-based iOS studies.

This paper presents a methodology for IP core protection of CE devices from both buyer's and seller's perspective. In the presented methodology, buyer fingerprint is embedded along seller watermark during architectural synthesis phase of IP core design. The buyer fingerprint is inserted during scheduling phase while seller watermark is implanted during register allocation phase of architectural synthesis process. The presented approach provides a robust mechanisms of IP core protection for both buyer and seller at zero area overhead, 1.1 % latency overhead and 0.95 % design cost overhead compared to a similar approach (that provides only protection to IP seller).

In the current society, people pay more and more attention to identity security, especially in the case of some highly confidential or personal privacy, one-to-one identification is particularly important. The iris recognition just has the characteristics of high efficiency, not easy to be counterfeited, etc., which has been promoted as an identity technology. This paper has carried out research on daugman algorithm and iris edge detection.

Security plays an important role in many authentication applications. Modern era information sharing is boundless and becoming much easier to access with the introduction of the Internet and the World Wide Web. Although this can be considered as a good point, issues such as privacy and data integrity arise due to the lack of control and authority. For this reason, the concept of data security was introduced. Data security can be categorized into two which are secrecy and authentication. In particular, this research was focused on the authentication of data security. There have been substantial research which discusses on multi-factor authentication scheme but most of those research do not entirely protect data against all types of attacks. Most current research only focuses on improving the security part of authentication while neglecting other important parts such as the accuracy and efficiency of the system. Current multifactor authentication schemes were simply not designed to have security, accuracy, and efficiency as their main focus. To overcome the above issue, this research will propose a new multi-factor authentication scheme which is capable to withstand external attacks which are known security vulnerabilities and attacks which are based on user behavior. On the other hand, the proposed scheme still needs to maintain an optimum level of accuracy and efficiency. From the result of the experiments, the proposed scheme was proven to be able to withstand the attacks. This is due to the implementation of the attack recognition and key generator technique together with the use of multi-factor in the proposed scheme.

Outsourcing services to cloud server (CS) becomes popular in these years. However, the outsourced services often involve with sensitive activity and CS naturally becomes a target of varieties of attacks. Even worse, CS itself can misuse the outsourced services for illegal profit. Traditional online banking system also can make use of a cloud framework to provide economical and high-speed online services to the consumers, which makes the financial dealing easy and convenient. Most of the banking organizations provide services through passbook, ATM, mobile banking, electronic banking (e-banking) etc. Among these, the e-banking and mobile banking are more convenient and becomes essential. Therefore, it is critical to provide an efficient, reliable and more importantly, secure e-banking services to the consumers. The cloud environment is suitable paradigm to a new, small and medium scale banking organization as it eliminates the requirement for them to start with small resources and increase gradually as the service demand rises. However, security is one of the main concerns since it deals with many sensitive data of the valuable customers. In addition to this, the access of various data needs to be restricted to prevent any unauthorized transaction. Nagaraju et al. presented a framework to achieve reliability and security in public cloud based online banking using multi-factor authentication concept. Unfortunately, the login and authentication protocol of this framework is prone to impersonation attack. In this paper, we have revised the framework to avoid this attack.

BYOD (Bring Your Own Device) trends allows employees to use the smartphone as a tool in everyday work and also as an attendance device. The security of employee attendance system is important to ensure that employees do not commit fraud in recording attendance and when monitoring activities at working hours. In this paper, we propose a combination of fingerprint, secure android ID, and GPS as authentication factors, also addition of anti emulator and anti fake location module turn Mobile Attendance System into Mobile Secure Attendance System. Testing based on scenarios that have been adapted to various possible frauds is done to prove whether the system can minimize the occurrence of fraud in attendance recording and monitoring of employee activities.

The quantitative security effectiveness analysis is a difficult problem for the research of network address randomization techniques. In this paper, a system model and an attack model are proposed based on general attacks' attack processes and network address randomization's technical principle. Based on the models, the network address randomization's security effectiveness is quantitatively analyzed from the perspective of the attacker's attack time and attack cost in both static network address and network address randomization cases. The results of the analysis show that the security effectiveness of network address randomization is determined by the randomization frequency, the randomization space, the states of hosts in the target network, and the capabilities of the attacker.

To manage and handle the issues of physical security in the modern world, there is a dire need for a multilevel security system to ensure the safety of precious belongings that could be money, military equipment or medical life-saving drugs. Security locker solution is proposed which is a multiple layer security system consisting of various levels of authentication. In most cases, only relevant persons should have access to their precious belongings. The unlocking of the box is only possible when all of the security levels are successfully cleared. The five levels of security include entering of password on interactive GUI, thumbprint, facial recognition, speech pattern recognition, and vein pattern recognition. This project is unique and effective in a sense that it incorporates five levels of security in a single prototype with the use of cost-effective equipment. Assessing our security system, it is seen that security is increased many a fold as it is near to impossible to breach all these five levels of security. The Raspberry Pi microcomputers, handling all the traits efficiently and smartly makes it easy for performing all the verification tasks. The traits used involves checking, training and verifying processes with application of machine learning operations.

Cryptographically cloud computing may be an innovative safe cloud computing design. Cloud computing may be a huge size dispersed computing model that ambitious by the economy of the level. It integrates a group of inattentive virtualized animatedly scalable and managed possessions like computing control storage space platform and services. External end users will approach to resources over the net victimization fatal particularly mobile terminals, Cloud's architecture structures are advances in on-demand new trends. That are the belongings are animatedly assigned to a user per his request and hand over when the task is finished. So, this paper projected biometric coding to boost the confidentiality in Cloud computing for biometric knowledge. Also, this paper mentioned virtualization for Cloud computing also as statistics coding. Indeed, this paper overviewed the safety weaknesses of Cloud computing and the way biometric coding will improve the confidentiality in Cloud computing atmosphere. Excluding this confidentiality is increased in Cloud computing by victimization biometric coding for biometric knowledge. The novel approach of biometric coding is to reinforce the biometric knowledge confidentiality in Cloud computing. Implementation of identification mechanism can take the security of information and access management in the cloud to a higher level. This section discusses, however, a projected statistics system with relation to alternative recognition systems to date is a lot of advantageous and result oriented as a result of it does not work on presumptions: it's distinctive and provides quick and contact less authentication. Thus, this paper reviews the new discipline techniques accustomed to defend methodology encrypted info in passing remote cloud storage.