A software agent enabled biometric security algorithm for secure file access in consumer storage devices

In order to resist unauthorized access, consumer storage devices are typically protected using a low entropy password. However, storage devices are not fully protected against an adversary because the adversary can utilize an off-line dictionary attack to find the correct password and/or run an existing algorithm for resetting the existing password. In addition, a password protected device may also be stolen or misplaced allowing an adversary to easily retrieve all the stored confidential information from a removable storage device. In order to protect the consumer’s confidential information that has been stored, this paper proposes a mutual authentication and key negotiation protocol that can be used to protect the confidential information in the device. The functionality of the protocol enables the storage device to be secure against relevant security attacks. A formal security analysis using Burrows-Abadi-Needham (BAN) logic is presented to verify the presented algorithm. In addition, a performance analysis of the proposed protocol reveals a significantly reduced communication overhead compared to the relevant literature

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Computer scienc

Mutual query data sharing protocol for public key encryption through chosen-ciphertext attack in cloud environment

In this paper, we are proposing a mutual query data sharing protocol (MQDS) to overcome the encryption or decryption time limitations of exiting protocols like Boneh, rivest shamir adleman (RSA), Multi-bit transposed ring learning parity with noise (TRLPN), ring learning parity with noise (Ring-LPN) cryptosystem, key-Ordered decisional learning parity with noise (kO-DLPN), and KD_CS protocol’s. Titled scheme is to provide the security for the authenticated user data among the distributed physical users and devices. The proposed data sharing protocol is designed to resist the chosen-ciphertext attack (CCA) under the hardness solution for the query shared-strong diffie-hellman (SDH) problem. The evaluation of proposed work with the existing data sharing protocols in computational and communication overhead through their response time is evaluated

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Computer scienc

Securing Cloud Storage by Transparent Biometric Cryptography

With the capability of storing huge volumes of data over the Internet, cloud storage has become a popular and desirable service for individuals and enterprises. The security issues, nevertheless, have been the intense debate within the cloud community. Significant attacks can be taken place, the most common being guessing the (poor) passwords. Given weaknesses with verification credentials, malicious attacks have happened across a variety of well-known storage services (i.e. Dropbox and Google Drive) – resulting in loss the privacy and confidentiality of files. Whilst today's use of third-party cryptographic applications can independently encrypt data, it arguably places a significant burden upon the user in terms of manually ciphering/deciphering each file and administering numerous keys in addition to the login password. The field of biometric cryptography applies biometric modalities within cryptography to produce robust bio-crypto keys without having to remember them. There are, nonetheless, still specific flaws associated with the security of the established bio-crypto key and its usability. Users currently should present their biometric modalities intrusively each time a file needs to be encrypted/decrypted – thus leading to cumbersomeness and inconvenience while throughout usage. Transparent biometrics seeks to eliminate the explicit interaction for verification and thereby remove the user inconvenience. However, the application of transparent biometric within bio-cryptography can increase the variability of the biometric sample leading to further challenges on reproducing the bio-crypto key. An innovative bio-cryptographic approach is developed to non-intrusively encrypt/decrypt data by a bio-crypto key established from transparent biometrics on the fly without storing it somewhere using a backpropagation neural network. This approach seeks to handle the shortcomings of the password login, and concurrently removes the usability issues of the third-party cryptographic applications – thus enabling a more secure and usable user-oriented level of encryption to reinforce the security controls within cloud-based storage. The challenge represents the ability of the innovative bio-cryptographic approach to generate a reproducible bio-crypto key by selective transparent biometric modalities including fingerprint, face and keystrokes which are inherently noisier than their traditional counterparts. Accordingly, sets of experiments using functional and practical datasets reflecting a transparent and unconstrained sample collection are conducted to determine the reliability of creating a non-intrusive and repeatable bio-crypto key of a 256-bit length. With numerous samples being acquired in a non-intrusive fashion, the system would be spontaneously able to capture 6 samples within minute window of time. There is a possibility then to trade-off the false rejection against the false acceptance to tackle the high error, as long as the correct key can be generated via at least one successful sample. As such, the experiments demonstrate that a correct key can be generated to the genuine user once a minute and the average FAR was 0.9%, 0.06%, and 0.06% for fingerprint, face, and keystrokes respectively. For further reinforcing the effectiveness of the key generation approach, other sets of experiments are also implemented to determine what impact the multibiometric approach would have upon the performance at the feature phase versus the matching phase. Holistically, the multibiometric key generation approach demonstrates the superiority in generating the bio-crypto key of a 256-bit in comparison with the single biometric approach. In particular, the feature-level fusion outperforms the matching-level fusion at producing the valid correct key with limited illegitimacy attempts in compromising it – 0.02% FAR rate overall. Accordingly, the thesis proposes an innovative bio-cryptosystem architecture by which cloud-independent encryption is provided to protect the users' personal data in a more reliable and usable fashion using non-intrusive multimodal biometrics.Higher Committee of Education Development in Iraq (HCED

Behaviour Profiling for Mobile Devices

With more than 5 billion users globally, mobile devices have become ubiquitous in our daily life. The modern mobile handheld device is capable of providing many multimedia services through a wide range of applications over multiple networks as well as on the handheld device itself. These services are predominantly driven by data, which is increasingly associated with sensitive information. Such a trend raises the security requirement for reliable and robust verification techniques of users.This thesis explores the end-user verification requirements of mobile devices and proposes a novel Behaviour Profiling security framework for mobile devices. The research starts with a critical review of existing mobile technologies, security threats and mechanisms, and highlights a broad range of weaknesses. Therefore, attention is given to biometric verification techniques which have the ability to offer better security. Despite a large number of biometric works carried out in the area of transparent authentication systems (TAS) and Intrusion Detection Systems (IDS), each have a set of weaknesses that fail to provide a comprehensive solution. They are either reliant upon a specific behaviour to enable the system to function or only capable of providing security for network based services. To this end, the behaviour profiling technique is identified as a potential candidate to provide high level security from both authentication and IDS aspects, operating in a continuous and transparent manner within the mobile host environment.This research examines the feasibility of a behaviour profiling technique through mobile users general applications usage, telephone, text message and multi-instance application usage with the best experimental results Equal Error Rates (EER) of 13.5%, 5.4%, 2.2% and 10% respectively. Based upon this information, a novel architecture of Behaviour Profiling on mobile devices is proposed. The framework is able to provide a robust, continuous and non-intrusive verification mechanism in standalone, TAS or IDS modes, regardless of device hardware configuration. The framework is able to utilise user behaviour to continuously evaluate the system security status of the device. With a high system security level, users are granted with instant access to sensitive services and data, while with lower system security levels, users are required to reassure their identity before accessing sensitive services.The core functions of the novel framework are validated through the implementation of a simulation system. A series of security scenarios are designed to demonstrate the effectiveness of the novel framework to verify legitimate and imposter activities. By employing the smoothing function of three applications, verification time of 3 minutes and a time period of 60 minutes of the degradation function, the Behaviour Profiling framework achieved the best performance with False Rejection Rate (FRR) rates of 7.57%, 77% and 11.24% for the normal, protected and overall applications respectively and with False Acceptance Rate (FAR) rates of 3.42%, 15.29% and 4.09% for their counterparts

Developing a comprehensive information security framework for mHealth: a detailed analysis

It has been clearly shown that mHealth solutions, which is the use of mobile devices and other wireless technology to provide healthcare services, deliver more patient-focused healthcare, and improve the overall efficiency of healthcare systems. In addition, these solutions can potentially reduce the cost of providing healthcare in the context of the increasing demands of the aging populations in advanced economies. These solutions can also play an important part in intelligent environments, facilitating real-time data collection and input to enable various functionalities. However, there are several challenges regarding the development of mHealth solutions: the most important of these being privacy and data security. Furthermore, the use of cloud computing is becoming an option for the healthcare sector to store healthcare data; but storing data in the cloud raises serious concerns. This paper investigates how data are managed both on mHealth devices as well as in the cloud. Firstly, a detailed analysis of the entire mHealth domain is undertaken to determine domain-specific features and a taxonomy for mHealth, from which a set of security requirements are identified in order to develop a new information security framework. It then examines individual information security frameworks for mHealth devices and the cloud, noting similarities and differences. Furthermore, key mechanisms to implement the new framework are discussed and the new framework is then presented. Finally, the paper presents how the new framework could be implemented in order to develop an Advanced Digital Medical Platform