Confidentiality & Authentication Mechanism for Biometric Information Transmitted over Low Bandwidth & Unreliable channel

Low-power and lossy networks (LLNs) comprised of thousands of embedded networking devices connected to the larger Internet architecture can be used in a variety of applications, leading to the emerging concept of the Internet of Things (IoT). Access control and key management in such LLN is a big challenge since authentication, authorization, and key management process involves several handshakes of large size packets over low bandwidth and high latency links through a bottlenecked LLN border router (LBR). This may result in significant wasted bandwidth and slow authentication completion time. The goal of this work is to propose a “fast and adaptive node authentication mechanism for low-power lossy networks,” called FINALLY , that solves these problems and significantly improves the efficiency and speed of mesh authentication process. We evaluate FINALLY through simulations and show that it allows devices to authenticate quickly without repeated authentication failures, reduces unnecessarily wasted transmissions, and improves the overall completion time of the authentication process.

It is important to ensure the security of biometric authentication information, because its leakage causes serious risks, such as replay attacks using the stolen biometric data, and also because it is almost impossible to replace raw biometric information. In this paper, we propose a secure biometric authentication scheme that protects such information by employing an optical data ciphering technique based on compressed sensing. The proposed scheme is based on two-factor authentication, the biometric information being supplemented by secret information that is used as a random seed for a cipher key. In this scheme, a biometric image is optically encrypted at the time of image capture, and a pair of restored biometric images for enrollment and verification are verified in the authentication server. If any of the biometric information is exposed to risk, it can be reenrolled by changing the secret information. Through numerical experiments, we confirm that finger vein images can be restored from the compressed sensing measurement data. We also present results that verify the accuracy of the scheme.

The purpose of this paper is to present a warning that covert channels even at very low bandwidths can be a significant threat in conjuction with sufficiently sophisticated "trojan horses".According to DOD 5200,28-STD (the orange book) covert channels with a bandwidth of under 1 bit per ten seconds need not even be audited in a trusted system.While this seems reasonable it is easy to imagine scenarios where covert channels with a flow rate much lower than this may indeed compromise vital information, if the process from which the flow originates is an intelligent trojan horse.Consider the following scenario: A trusted multi-level secure strategic logistics system with a trojan horse which is an expert system capable of detecting whether there are troop and supply movements planned, which would allow offensive action within the next week. A convert channel with the rate of one bit per day, which each day transmits this information from the expert trojan horse to an insecure process would certainly be of great value in strategic planning.In summary, when considering the maximum bandwidth requirements on convert channels, it is necessay to consider this in line with the type of information available to processes running at the higher security levels, and the degree of trust that one has in these applications.

A novel biometric authentication information hiding method based on the sparse representation is proposed for enhancing the security of biometric information transmitted in the network. In order to make good use of abundant information of the cover image, the sparse representation method is adopted to exploit the correlation between the cover and biometric images. Thus, the biometric image is divided into two parts. The first part is the reconstructed image, and the other part is the residual image. The biometric authentication image cannot be restored by any one part. The residual image and sparse representation coefficients are embedded into the cover image. Then, for the sake of causing much less attention of attackers, the visual attention mechanism is employed to select embedding location and embedding sequence of secret information. Finally, the reversible watermarking algorithm based on histogram is utilized for embedding the secret information. For verifying the validity of the algorithm, the PolyU multispectral palmprint and the CASIA iris databases are used as biometric information. The experimental results show that the proposed method exhibits good security, invisibility, and high capacity.

Biometric Cryptography is the biometric tokenization used for authentication with public-key infrastructure (PKI). In particular, biometric cryptography provides the convenience of authentication via fingerprint, face, eye, voice, palm, etc. - with none of the risks posed by having the biometrics take the form of a shared secret. With comfort, biometric verification gives more security than as it were conventional cryptography-based confirmation. Since biometric highlights of each human being are distinctive from each other, that makes it difficult to get to in an unauthorized way and it jams the privacy at the time of verification since there's no plausibility of snooping. In this manner, these days the utilization of biometric-based confirmation has expanded and utilized in versatile, portable workstation, and numerous other gadgets are utilizing biometric-based verification and biometric information stored in biometric gadgets and programmers are exceptionally shrewd they can render biometric information, can take it, and not at all like username or password biometric information can not alter, due to unique feature of biometrics. It implies, compromising biometric information will be until the end of life, and programmers can take advantage of it, so the security of biometric information is a vital issue. This paper gives some idea about cryptography methods that are capable to secure biometric data and we have presented four cryptography methods which are Biometric Encryption, Blockchain, Cancelable biometrics, and Visual cryptography. This paper also provides some challenges, issues in biometric, and future direction.

Vulnerability research plays a key role in preventing and defending against malicious computer system exploitations. Driven by a multi-billion dollar underground economy, cyber criminals today tirelessly launch malicious exploitations, threatening every aspect of daily computing. To effectively protect computer systems from devastation, it is imperative to discover and mitigate vulnerabilities before they fall into the offensive parties' hands. This dissertation is dedicated to the research and discovery of new design and deployment vulnerabilities in three very different types of computer systems. The first vulnerability is found in the automatic malicious binary (malware) detection system. Binary analysis, a central piece of technology for malware detection, are divided into two classes, static analysis and dynamic analysis. State-of-the-art detection systems employ both classes of analyses to complement each other's strengths and weaknesses for improved detection results. However, we found that the commonly seen design patterns may suffer from evasion attacks. We demonstrate attacks on the vulnerabilities by designing and implementing a novel binary obfuscation technique. The second vulnerability is located in the design of server system power management. Technological advancements have improved server system power efficiency and facilitated energy proportional computing. However, the change of power profile makes the power consumption subjected to unaudited influences of remote parties, leaving the server systems vulnerable to energy-targeted malicious exploit. We demonstrate an energy abusing attack on a standalone open Web server, measure the extent of the damage, and present a preliminary defense strategy. The third vulnerability is discovered in the application of server virtualization technologies. Server virtualization greatly benefits today's data centers and brings pervasive cloud computing a step closer to the general public. However, the practice of physical co-hosting virtual machines with different security privileges risks introducing covert channels that seriously threaten the information security in the cloud. We study the construction of high-bandwidth covert channels via the memory sub-system, and show a practical exploit of cross-virtual-machine covert channels on virtualized x86 platforms.

In the information exchange through network, the security risks always exists, that is eavesdropping, defacing, and spoofing by the attacker. Crypthography, digital signature, and authentication are techniques oppose such attacker. PKI (public key infrastructure) enables such technique. In PKI, the public key certificate is used. This public key certificate is issued and distributed by certificate authority, but we think that the updating of expired certificate etc. are very costly for the user. It seems that the management of secret key is more serious problem than that of public key certificate for the user. As above, in the system using public key cryptography, the managements of public key and secret key are very important problem. In order to solve the above problems, we propose the scheme that stores protected secret key which is made by combination of biometrics and secret key in the smartcard in the system which uses ID-based cryptography. In our proposal, TA (trusted authority) protects the secret key using biometrics information extracted from owner of that secret key and stores it as protected secret key in smartcard which has fingerprint reading function. And we must extract the same biometrics information as that is extracted at enrollment. So, we extract the helper data from biometrics information at making protected secret key and store it in smartcard. The user can restore the secret key form protected secret key by presenting his fingerprint to smart-card that has protected secret key and helper data. In our scheme, the template is not needed for authentication. So, the problem of the leaks of the template arise in traditional biometric authentication won't arise. Also we proposed the concrete operation scheme in which our scheme is used. We show that the cost of the public key and secret key management will be reduced by using this operation scheme.

로그인 과정에서는 사용자의 ID와 Password를 기반으로 시스템에 대한 사용권한을 확인하고 접근 권한을 부여한다. 하지만 로그인 과정에서 입력된 ID와 Password 정보는 패킷 스니핑 또는 키 로그(Key log) 프로그램 등을 이용하여 악의적인 공격자에 의해 노출될 수 있다는 취약점이 있다. 웹서버 또는 웹메일 시스템 등에 등록된 ID와 Password가 노출된다면 이는 개인 프라이버시 문제와도 연결되어 매우 심각한 문제를 야기한다. 본 연구에서는 기존의 ID/Password 기반 로그인 기법과 더불어 소프트웨어 형태의 보안카드를 핸드폰에 설치하여 유무선망을 통한 다중 인증(Multi-factor authentication) 기법을 제시한다. 제안한 소프트웨어 형태의 보안카드 기반 로그인 기법은 ID/Password와 함께 부가적으로 바이오 정보를 이용할 수 있으며 사용자의 핸드폰에 소프트 형태의 보안카드를 생성/전송/저장하게 된다. 따라서 제안한 시스템을 사용할 경우 기존의 ID 및 Password 정보에 대해 각 개인별 바이오 정보 기반 일회용 패스워드(Biometric One-Time Password) 방식으로 소프트 보안카드를 생성할 수 있으며 이를 이용하여 웹 및 인터넷 로그인 과정을 수행하기 때문에 보다 안전한 다중 인증 시스템을 구축할 수 있다. Login process uses both ID and password information to authenticate someone and to permit its access privilege on system. However, an attacker can get those ID and password information by using existing packet sniffing or key logger programs. It cause privacy problem as those information can be used as a hacking and network attack on web server and web e-mail system. Therefore, a more secure and advanced authentication mechanism should be required to enhance the authentication process on existing system. In this paper, we propose a multi-factor authentication process by using software form of secure card system combined with existing ID/Password based login system. Proposed mechanism uses a random number generated from the his/her own handset with biometric information. Therefore, we can provide a one-time password function on web login system to authenticate the user using multi-factor form. Proposed scheme provide enhanced authentication function and security because it is a 'multi-factor authentication mechanism' combined with handset and biometric information on web login system.

Bathymetric simultaneous localisation and mapping (SLAM) methods yield accurate navigation results for autonomous underwater vehicles (AUVs) and can construct consistent seabed terrain maps. Multiple independently working vehicles can complete tasks like surveying and mapping efficiently, which means cooperative bathymetric SLAM using multiple AUVs is suitable for large-scale seabed mapping. However, the transmission of bathymetric measurements collected using a multi-beam echo sounder over a low bandwidth, noisy, and unreliable acoustic channel is difficult, making cooperative bathymetric SLAM very challenging. This paper develops a graph-based cooperative bathymetric SLAM system that can compress many bathymetric measurements into small-scale acoustic packets and yield accurate navigation results with a 10% loss of acoustic packets caused by unreliable acoustic communication. According to the simulation conducted using the field data, the new algorithm is shown to be robust and capable of providing accurate location and mapping results over a low bandwidth, noisy, and unreliable acoustic channel.

Maintaining the privacy and security of people information are two most important principles of electronic health plan. One of the methods of creating privacy and securing of information is using Public key cryptography system. In this paper, we compare two algorithms, Common And Fast Exponentiation algorithms, for enhancing the efficiency of public key cryptography. We express that a designed system by Fast Exponentiation Algorithm has high speed and performance but low power consumption and space occupied compared with Common Exponentiation algorithm. Although designed systems by Common Exponentiation algorithm have slower speed and lower performance, designing by this algorithm has less complexity, and easier designing compared with Fast Exponentiation algorithm. In this paper, we will try to examine and compare two different methods of exponentiation, also observe performance Impact of these two approaches in the form of hardware with VHDL language on FPGA.

Privacy and information security in general are major concerns that impede enterprise adaptation of shared or public cloud computing. Specifically, the concern of virtual machine (VM) physical co-residency stems from the threat that hostile tenants can leverage various forms of side channels (such as cache covert channels) to exfiltrate sensitive information of victims on the same physical system. However, on virtualized x86 systems, covert channel attacks have not yet proven to be practical, and thus the threat is widely considered a potential risk. In this paper, we present a novel covert channel attack that is capable of high-bandwidth and reliable data transmission in the cloud. We first study the application of existing cache channel techniques in a virtualized environment and uncover their major insufficiency and difficulties. We then overcome these obstacles by: 1) redesigning a pure timing-based data transmission scheme, and 2) exploiting the memory bus as a high-bandwidth covert channel medium. We further design and implement a robust communication protocol and demonstrate realistic covert channel attacks on various virtualized x86 systems. Our experimental results show that covert channels do pose serious threats to information security in the cloud. Finally, we discuss our insights on covert channel mitigation in virtualized environments.

As an advanced information recognition and data capture techniques,RFID are widely used in many areas. However, due to the RFID tag works and cost constraints, information security through wireless channel is threatened. Through analyzing the security risks and existing defect of the RFID authentication protocol,this paper proposes a new RFID authentication scheme combined public key encryption algorithm and hash function. Analysis result shows that it has higher security and the smaller resources consumption in achieving.

In the technological era, it is essential to identify personal details of a person for various reasons. One of the most trustable commonly used methods for identifying a person is physical traits called biometrics of the person. This biometric information may be a person’s iris, finger print, voice of face. Among these factors finger print is most commonly used one. Nowadays even mobile phone uses fingerprint identification. In forensic and law & order department consider finger print matching as an important factor to identify a person. But recognizing fingerprint from poor quality images is still a very complex problem.To overcome this problem it is essential to enhance the details of contactless fingerprint.This can be done by a proper image enhancement algorithm like thresholding and binarization. Fingerprint recognition can be done by using feature extraction method.

Gender detection using fingerprint biometrics has emerged as a promising area of research due to its non-intrusive nature and potential applications in biometric identification systems. The procedure can involve multiple steps are the size of finger print and their ridge pattern, minutiae point, machine learning and image processing and accuracy and limitations. This review explores the effectiveness of machine learning techniques for gender classification based on fingerprint patterns, emphasizing the role of advanced classification algorithms and feature extraction methods. Machine learning is crucial for gender detection since it classifies fingerprint patterns and biometric information using models like Convolutional Neural Networks (CNN) and Support Vector Machines (SVM). To identify traits unique to a gender, such as ridge density and minutiae points, these algorithms are trained using labelled datasets. Compared to manual procedures, these models are more effective at handling high-dimensional data and identifying subtle gender-related patterns. Although hybrid models like CNN-DNN and AlexNet further increase classification precision, Convolutional Neural Networks (CNNs) are especially effective due to their automatic feature extraction capabilities. Despite their effectiveness, factors like as picture resolution, demographic balance, and dataset heterogeneity might affect performance, highlighting the need for carefully selected datasets and improved model designs. A structured comparative analysis of multiple studies reveals the impact of various datasets, feature types, and model architectures on classification accuracy and reliability. The findings suggest that deep learning models often outperform traditional classifiers, while dimensionality reduction and hybrid approaches can further enhance performance. However, challenges such as dataset imbalances, limited diversity, and susceptibility to low-quality fingerprint data remain prominent barriers to achieving consistent results. This review also outlines key limitations observed across the studies and provides recommendations for future research, including the need for more diverse datasets and optimized classification frameworks. This study aims to improve fingerprint feature extraction for gender detection, reduce processing costs, fix dataset imbalances, and increase classification accuracy. By stating the objective, the scope and objectives of each investigation are made clear. The generalizability of machine learning models is significantly impacted by the amount, variety, and quality of the dataset. The analysis aims to support the development of more accurate, inclusive, and scalable fingerprint-based gender detection systems.

The Civil Air Patrol (CAP) performs aerial reconnaissance of roadways and bridges. To enhance the analysis of aerial observations, CAP has proposed broadcasting amateur television from aircraft cockpits to ground receiving stations, However, because of the large bandwidth required for video transmission and the low transmitter power available the range of video transmission is very limited. As an alternative to amateur television transmission, the paper develops a software based, continuous-tone, still image transmission system. A digitized color image at television resolution contains nearly one million bytes. Digital imaging is, therefore, not often implemented due to high storage or transmission costs. However, by employing a high quality image compression technique, images may be compressed from 1/10 to greater than 1/50 their uncompressed size without visibly affecting image quality. These compressed images can then be transmitted over a low bandwidth channel in a reasonable time. The major issues in developing the prototype system were the image compression and data transmission techniques. The selected image compression technique is based on the JPEG Still Image Data Compression Standard, known officially as ISO DIS 10918-1 or CCITT Recommendation T.81. The system's data link will use high speed (9600 bits per second) packet radio (CCITT X25). This system shows the JPEG image compression method is suitable for transmitting high quality compressed images over a low bandwidth channel in a reasonable time. Additional data compression is achieved through the use of V.42 bis data compression.