Substitution boxes are essential nonlinear components responsible to impart strong confusion and security in most of modern symmetric ciphers. Constructing efficient S-boxes has been a prominent ...topic of interest for security experts. With an aim to construct cryptographically efficient S-box, a novel scheme based on firefly (FA) optimization and chaotic map is proposed in this paper. The anticipated approach generates initial S-box using chaotic map. The meta-heuristic FA is applied to find notable configuration of S-box that satisfies the criterions by guided search for near-optimal features by minimizing fitness function. The performance of proposed approach is assessed through well-established criterions such as bijectivity, nonlinearity, strict avalanche criteria, bit independence criteria, differential uniformity, and linear approximation probability. The obtained experimental results are compared with some recently investigated S-boxes to demonstrate that the proposed scheme has better proficiency of constructing efficient S-boxes.
•A model to detect distraction of drivers.•Utilizes Convolutional Neural Networks to detect the activity being performed by the driver.•The model is able to differentiate between the types of ...distractions as well.•High detection accuracy of 99% achieved over a large dataset.•The model proposed, takes significantly less training time and delivers high test accuracy.
With the intervention of social media and internet technology, people are getting more and more careless and distracted while driving which is having a severe detrimental effect on the safety of the driver and his fellow passengers. To provide an effective solution, this paper puts forward a Machine Learning model using Convolutional Neural Networks to not only detect the distracted driver but also identify the cause of his distraction by analyzing the images obtained using the camera module installed inside the vehicle. Convolutional Neural Networks are known to learn spatial features from images, which can be further examined by fully connected neural networks. The experimental results show a 99% average accuracy in distraction recognition and hence strongly support that our Convolutional Neural Networks model can be used to identify distraction among the drivers.
Highly crystalline ZnO nanoparticles (NPs) were synthesized with zinc acetate as precursor and oxalic acid at 80°C through the simple solution phase approach. The synthesized ZnO NPs possessed ...monodispersity with the average size 20–30nm. The crystalline properties revealed the typical hexagonal wurtzite phase with orientation along c-axis. The photocatalytic activity investigation was carried out by performing the decomposition of rhodamine-B dye under UV illumination over as-synthesized ZnO NPs. The rhodamine B dye considerably degraded by ∼95% within 70min in the presence of as-synthesized ZnO NPs. An excellent rate constant (k=0.0343min−1) was obtained for the degradation of rhodamine B dye.
► Highly crystalline ZnO NPs were synthesized by solution phase approach at 80°C. ► Synthesized ZnO NPs exhibited good monodispersity. ► Rhodamine B dye considerably degraded by ∼95% within 70min over ZnO NPs under UV-light illumination. ► Photocatalytic reaction showed the rate k=0.0343min−1 and followed the 1st order kinetic mechanism.
An innovative Cu(Hadp)
(Bimb)
(KA@CP-S3) coordination polymer expands its dimensionality from a 1D chain to a 2D network. The topological analysis reveals that KA@CP-S3 has 2-connected uninodal 2D
...topology. KA@CP-S3 has capable luminescent sensing for volatile organic compounds (VOCs), nitroaromatics, heavy metal ions, anions, disposed antibiotics (nitrofurantoin and tetracycline) and biomarkers. Intriguingly, KA@CP-S3 exhibits outstanding selective quenching of about 90.7% and 90.5% for the 125 mg dl
and 150 mg dl
strengths of sucrose, respectively, in aqueous solution along with other ranges in between. The photocatalytic degradation efficiency of KA@CP-S3 for the potentially harmful organic dye Bromophenol Blue displays 95.4%, which is the highest among the 13 dyes that were evaluated.
The increasing role of Telecare Medicine Information Systems (TMIS) makes its accessibility for patients to explore medical treatment, accumulate and approach medical data through internet ...connectivity. Security and privacy preservation is necessary for medical data of the patient in TMIS because of the very perceptive purpose. Recently, Mohit et al.’s proposed a mutual authentication protocol for TMIS in the cloud computing environment. In this work, we reviewed their protocol and found that it is not secure against stolen verifier attack, many logged in patient attack, patient anonymity, impersonation attack, and fails to protect session key. For enhancement of security level, we proposed a new mutual authentication protocol for the similar environment. The presented framework is also more capable in terms of computation cost. In addition, the security evaluation of the protocol protects resilience of all possible security attributes, and we also explored formal security evaluation based on random oracle model. The performance of the proposed protocol is much better in comparison to the existing protocol.
A symmetric block cipher employing a substitution-permutation duo is an effective technique for the provision of information security. For substitution, modern block ciphers use one or more ...substitution boxes (S-Boxes). Certain criteria and design principles are fulfilled and followed for the construction of a good S-Box. In this paper, an innovative technique to construct substitution-boxes using our cubic fractional transformation (CFT) is presented. The cryptographic strength of the proposed S-box is critically evaluated against the state of the art performance criteria of strong S-boxes, including bijection, nonlinearity, bit independence criterion, strict avalanche effect, and linear and differential approximation probabilities. The performance results of the proposed S-Box are compared with recently investigated S-Boxes to prove its cryptographic strength. The simulation and comparison analyses validate that the proposed S-Box construction method has adequate efficacy to generate efficient candidate S-Boxes for usage in block ciphers.
•A custom deep learning framework for detecting fire in real-world images.•Attention mechanism and transfer learning is used with EfficientNetB0 trained.•Framework uses Grad-CAM method for ...visualization and localization of fire.•High recall of 97.61 supports the reliability of model for fire detection task.
Fire is a severe natural calamity that causes significant harm to human lives and the environment. Recent works have proposed the use of computer vision for developing a cost-effective automated fire detection system. This paper presents a custom framework for detecting fire using transfer learning with state-of-the-art CNNs trained over real-world fire breakout images. The framework also uses the Grad-CAM method for the visualization and localization of fire in the images. The model also uses an attention mechanism that has significantly assisted the network in achieving better performances. It was observed through Grad-CAM results that the proposed use of attention led the model towards better localization of fire in the images. Among the plethora of models explored, the EfficientNetB0 emerged as the best-suited network choice for the problem. For the selected real-world fire image dataset, a test accuracy of 95.40% strongly supports the model's efficiency in detecting fire from the presented image samples. Also, a very high recall of 97.61 highlights that the model has negligible false negatives, suggesting the network to be reliable for fire detection.
Substitution-boxes (S-boxes) are unique nonlinear elements, which are used to achieve the property of confusion in modern symmetric ciphers and offer resistance to cryptanalysis. The construction of ...strong S-boxes has gained considerable attention in the area of cryptography. In fact, the security of transmitted data is highly dependent on the strength of the S-boxes for the prevention of unauthorised access. Therefore, the creation of strong S-box with high nonlinearity score has been considered a significant challenge. This study presented a novel method for the designing of 8 × 8 S-boxes with selected cryptographic characteristics based on a cuckoo search (CS) algorithm and discrete-space chaotic map. Notably, the advantage of the proposed approach is indicated through the efficient randomisation and lower adjustable parameters in CS compared to GA and PSO. Also, this approach utilised a 1D discrete-space chaotic map with virtually unlimited key space to design initial S-boxes, which is another advantage over the methods based on continuous-space chaotic maps, which consist of the limited key space. Moreover, chaotic maps have a potential to overcome the trapping problem of a standard CS in the local optima, and they were used to generate initial S-boxes to achieve the desired quality and facilitate the metaheuristic search. Accordingly, the metaheuristic CS was used to find a notable S-box configuration which fulfilled the established criteria. This objective was achieved by searching for the optimal or near-optimal features which maximised the given fitness function. The performance of the proposed method was evaluated based on the established performance evaluation criteria, including bijectivity, nonlinearity, strict avalanche criteria, bit independence criteria, differential uniformity, and linear probability. Based on the results of proposed method performance was benchmarked against the results of the recently developed S-boxes, it was indicated that the S-boxes exhibited good cryptographic features and could resist various cryptanalysis attacks.
Static substitution-boxes in fixed structured block ciphers may make the system vulnerable to cryptanalysis. However, key-dependent dynamic substitution-boxes (S-boxes) assume to improve the security ...and robustness of the whole cryptosystem. This paper proposes to present the construction of key-dependent dynamic S-boxes having high nonlinearity. The proposed scheme involves the evolution of initially generated S-box for improved nonlinearity based on the fractional-order time-delayed Hopfield neural network. The cryptographic performance of the evolved S-box is assessed by using standard security parameters, including nonlinearity, strict avalanche criterion, bits independence criterion, differential uniformity, linear approximation probability, etc. The proposed scheme is able to evolve an S-box having mean nonlinearity of 111.25, strict avalanche criteria value of 0.5007, and differential uniformity of 10. The performance assessments demonstrate that the proposed scheme and S-box have excellent features, and are thus capable of offering high nonlinearity in the cryptosystem. The comparison analysis further confirms the improved security features of anticipated scheme and S-box, as compared to many existing chaos-based and other S-boxes.
In modern-day block ciphers, the role of substitution-boxes is to transform the plaintext data nonlinearly to generate ciphertext data with sufficient confusion. It has been well-confirmed that the ...robustness and security of such block ciphers heavily based on the cryptographic strength of the underlying substitution-boxes. Reason being, they are the only components that are held responsible to bring required nonlinearity and complexity into the security system which can frustrate the attackers. Accordingly, a number of different concepts have been explored to construct strong S-boxes. To move forward with the same aim, a novel simple modular approach, the very first time, is investigated to construct nonlinear S-box in this paper. The proposed new modular approach consists of three operations such as new transformation, modular inverses, and permutation. A number of highly nonlinear S-boxes can be easily constructed with slight changes in the novel transformation parameters. An example S-box is presented whose critical performance assessment against some benchmarking criterions such as high nonlinearity, absence of fixed points, fulfillment of SAC and BIC properties, low differential uniformity and linear approximation probability and comparison with recent S-boxes demonstrate its upright cryptographic potentiality. In addition, an image encryption algorithm is also proposed wherein the generated S-box is applied to perform the pixels shuffling and substitution for strong statistical and differential encryption performance.
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