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We are facing a critical aging crisis, with geriatric populations (65+) growing to unprecedented proportions and ~4 million people (a 6.5-fold increase) expected to become centenarians by 2050. This is compounded by environmental pollution, which affects individuals of all ages and contributes to age-related diseases. As we have a limited understanding of how environmental pollutants affect older populations distinctly from younger populations, these longer-lived geriatric populations present a key knowledge gap. To address this knowledge gap, we employ a "Toxic Aging Coin" approach: heads consider how age impacts chemical toxicity, and tails consider how chemicals act as gerontogens—or how they accelerate biological aging. We employed this approach to investigate hexavalent chromium (Cr[VI]) impacts on female rats exposed to 0.05 or 0.1 mg Cr(VI)/L in drinking water for 90 days; these are the maximum contaminant levels (i.e., the highest levels permitted) from the World Health Organization and U.S. Environmental Protection Agency, respectively. During exposure, rats performed a battery of behavior assays to assess grip strength, locomotor coordination, anxiety, spatial memory, sociability, and social novelty preference. We observed age differences in Cr(VI) neurotoxicity, with grip strength, locomotor function, and spatial memory in middle-aged females being particularly affected. We further compared these results in females to results in males, noting many sex differences, especially in middle-aged rats. These data emphasize the need to consider age and sex as variables in toxicology and to revisit drinking water regulations for Cr(VI). [ABSTRACT FROM AUTHOR]

With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally results in low encryption/decryption speed along with exerting a burden on the limited bandwidth of the transmission channel. To address the aforementioned issues, a new encryption scheme for colour images employing convolutional autoencoder, DNA and chaos is presented in this paper. The proposed scheme has two main modules, the dimensionality conversion module using the proposed convolutional autoencoder, and the encryption/decryption module using DNA and chaos. The dimension of the input colour image is first reduced from N ×M ×3 to P×Q gray-scale image using the encoder. Encryption and decryption are then performed in the reduced dimension space. The decrypted gray-scale image is upsampled to obtain the original colour image having dimension N × M × 3. The training and validation accuracy of the proposed autoencoder is 97% and 95%, respectively. Once the autoencoder is trained, it can be used to reduce and subsequently increase the dimension of any arbitrary input colour image. The efficacy of the designed autoencoder has been demonstrated by the successful reconstruction of the compressed image into the original colour image with negligible perceptual distortion. The second major contribution presented in this paper is an image encryption scheme using DNA along with multiple chaotic sequences and substitution boxes. The security of the proposed image encryption algorithm has been gauged using several evaluation parameters, such as histogram of the cipher image, entropy, NPCR, UACI, key sensitivity, contrast, and so on. The experimental results of the proposed scheme demonstrate its effectiveness to perform colour image encryption. [ABSTRACT FROM AUTHOR]

Traditional password authentication methods have raised many issues in the past, including insecure practices, so it comes as no surprise that the evolution of authentication should arrive in the form of password-less solutions. This research aims to explore the problems that password authentication and password policies present and aims to deploy Windows Hello for Business (WHFB) on-premises. This includes creating three virtual machines (VMs) and evaluating WHFB as a password-less solution and showing how an attacker with privileged access may retrieve the end user's domain password from the computer's memory using Mimikatz and describing the possible results. The conducted research tests are in the form of two attack methods. This was feasible by the creation of three VMs operating in the following way. The first VM will act as a domain controller (DC) and certificate authority server (CA server). The second VM will act as an Active Directory Federation Service (ADFS). The third VM will act as the end-user device. The test findings research summarized that password-less authentication is far more secure than the traditional authentication method; this is evidenced throughout the author's tests. Within the first test, it was possible to retrieve the password from an enrolled device for WHFB while it was still in the second phase of the deployment. The second test was a brute-force attack on the PIN of WHFB; since WHFB has measures to prevent such attacks, the attack was unsuccessful. However, even though the retrieval of the password was successful, there are several obstacles to achieving this outcome. It was concluded that many organizations still use password authentication as their primary authentication method for accessing devices and applications. Larger organizations such as Microsoft and Google support the adoption of password-less authentication for end-users, and the current usage of password-less authentication shared by both organizations is encouraged. This usually leads organizations to adopt this new solution for their IT infrastructure. This is because it has been used and tested by millions of people and has proven to be safe. This supports the findings of increased usage and the need for password-less authentication by today's users. [ABSTRACT FROM AUTHOR]

Making investment decisions by utilizing sentiment data from social media (SM) is starting to become a more tangible concept. There has been a broad investigation into this field of study over the last decade, and many of the findings have promising results. However, there is still an opportunity for continued research, firstly, in finding the most effective way to obtain relevant sentiment data from SM, then building a system to measure the sentiment, and finally visualizing it to help users make investment decisions. Furthermore, much of the existing work fails to factor SM metrics into the sentiment score effectively. This paper presents a novel prototype as a contribution to the field of study. In our work, a detailed overview of the topic is given in the form of a literature and technical review. Next, a prototype is designed and developed using the findings from the previous analysis. On top of that, a novel approach to factor SM metrics into the sentiment score is presented, with the goal of measuring the collective sentiment of the data effectively. To test the proposed approach, we only used popular stocks from the S&P500 to ensure large volumes of SM sentiment was available, adding further insight into findings, which we then discuss in our evaluation. [ABSTRACT FROM AUTHOR]

Ransomware is a malicious class of software that utilises encryption to implement an attack on system availability. The target's data remains encrypted and is held captive by the attacker until a ransom demand is met. A common approach used by many crypto-ransomware detection techniques is to monitor file system activity and attempt to identify encrypted files being written to disk, often using a file's entropy as an indicator of encryption. However, often in the description of these techniques, little or no discussion is made as to why a particular entropy calculation technique is selected or any justification given as to why one technique is selected over the alternatives. The Shannon method of entropy calculation is the most commonly-used technique when it comes to file encryption identification in crypto-ransomware detection techniques. Overall, correctly encrypted data should be indistinguishable from random data, so apart from the standard mathematical entropy calculations such as Chi-Square ( χ 2 ), Shannon Entropy and Serial Correlation, the test suites used to validate the output from pseudo-random number generators would also be suited to perform this analysis. The hypothesis being that there is a fundamental difference between different entropy methods and that the best methods may be used to better detect ransomware encrypted files. The paper compares the accuracy of 53 distinct tests in being able to differentiate between encrypted data and other file types. The testing is broken down into two phases, the first phase is used to identify potential candidate tests, and a second phase where these candidates are thoroughly evaluated. To ensure that the tests were sufficiently robust, the NapierOne dataset is used. This dataset contains thousands of examples of the most commonly used file types, as well as examples of files that have been encrypted by crypto-ransomware. During the second phase of testing, 11 candidate entropy calculation techniques were tested against more than 270,000 individual files—resulting in nearly three million separate calculations. The overall accuracy of each of the individual test's ability to differentiate between files encrypted using crypto-ransomware and other file types is then evaluated and each test is compared using this metric in an attempt to identify the entropy method most suited for encrypted file identification. An investigation was also undertaken to determine if a hybrid approach, where the results of multiple tests are combined, to discover if an improvement in accuracy could be achieved. [ABSTRACT FROM AUTHOR]

Historically, threat information sharing has relied on manual modelling and centralised network systems, which can be inefficient, insecure, and prone to errors. Alternatively, private blockchains are now widely used to address these issues and improve overall organisational security. An organisation's vulnerabilities to attacks might change over time. It is utterly important to find a balance among a current threat, the potential countermeasures, their consequences and costs, and the estimation of the overall risk that this provides to the organisation. For enhancing organisational security and automation, applying threat intelligence technology is critical for detecting, classifying, analysing, and sharing new cyberattack tactics. Trusted partner organisations can then share newly identified threats to improve their defensive capabilities against unknown attacks. On this basis, organisations can help reduce the risk of a cyberattack by providing access to past and current cybersecurity events through blockchain smart contracts and the Interplanetary File System (IPFS). The suggested combination of technologies can make organisational systems more reliable and secure, improving system automation and data quality. This paper outlines a privacy-preserving mechanism for threat information sharing in a trusted way. It proposes a reliable and secure architecture for data automation, quality, and traceability based on the Hyperledger Fabric private-permissioned distributed ledger technology and the MITRE ATT&CK threat intelligence framework. This methodology can also be applied to combat intellectual property theft and industrial espionage. [ABSTRACT FROM AUTHOR]

E-governance is a process that aims to enhance a government's ability to simplify all the processes that may involve government, citizens, businesses, and so on. The rapid evolution of digital technologies has often created the necessity for the establishment of an e-Governance model. There is often a need for an inclusive e-governance model with integrated multiactor governance services and where a single market approach can be adopted. e-Governance often aims to minimise bureaucratic processes, while at the same time including a digital-by-default approach to public services. This aims at administrative efficiency and the reduction of bureaucratic processes. It can also improve government capabilities, and enhances trust and security, which brings confidence in governmental transactions. However, solid implementations of a distributed data sharing model within an e-governance architecture is far from a reality; hence, citizens of European countries often go through the tedious process of having their confidential information verified. This paper focuses on the sinGLe sign-on e-GovernAnce Paradigm based on a distributed file-exchange network for security, transparency, cost-effectiveness and trust (GLASS) model, which aims to ensure that a citizen can control their relationship with governmental agencies. The paper thus proposes an approach that integrates a permissioned blockchain with the InterPlanetary File System (IPFS). This method demonstrates how we may encrypt and store verifiable credentials of the GLASS ecosystem, such as academic awards, ID documents and so on, within IPFS in a secure manner and thus only allow trusted users to read a blockchain record, and obtain the encryption key. This allows for the decryption of a given verifiable credential that stored on IPFS. This paper outlines the creation of a demonstrator that proves the principles of the GLASS approach. [ABSTRACT FROM AUTHOR]

Cryptographic algorithms and functions should possess some of the important functional requirements such as: non-linearity, resiliency, propagation and immunity. Several previous studies were executed to analyze these characteristics of the cryptographic functions specifically for Boolean and symmetric functions. Randomness is a requirement in present cryptographic algorithms and therefore, Symmetric Random Function Generator (SRFG) has been developed. In this paper, we have analysed SRFG based on propagation feature and immunity. Moreover, NIST recommended statistical suite has been tested on SRFG outputs. The test values show that SRFG possess some of the useful randomness properties for cryptographic applications such as individual frequency in a sequence and block-based frequency, long run of sequences, oscillations from 0 to 1 or vice-versa, patterns of bits, gap bits between two patterns, and overlapping block bits. We also analyze the comparison of SRFG and some existing random number generators. We observe that SRFG is efficient for cryptographic operations in terms of propagation and immunity features. [ABSTRACT FROM AUTHOR]