High Accuracy Phishing Detection Based on Convolutional Neural Networks

The persistent growth in phishing and the rising volume of phishing websites has led to individuals and organizations worldwide becoming increasingly exposed to various cyber-attacks. Consequently, more effective phishing detection is required for improved cyber defence. Hence, in this paper we present a deep learning-based approach to enable high accuracy detection of phishing sites. The proposed approach utilizes convolutional neural networks (CNN) for high accuracy classification to distinguish genuine sites from phishing sites. We evaluate the models using a dataset obtained from 6,157 genuine and 4,898 phishing websites. Based on the results of extensive experiments, our CNN based models proved to be highly effective in detecting unknown phishing sites. Furthermore, the CNN based approach performed better than traditional machine learning classifiers evaluated on the same dataset, reaching 98.2% phishing detection rate with an F1-score of 0.976. The method presented in this pa-per compares favourably to the state-of-the art in deep learning based phishing website detection

DL-Droid: Deep learning based android malware detection using real devices

open access articleThe Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The sophistication of Android malware obfuscation and detection avoidance methods have significantly improved, making many traditional malware detection methods obsolete. In this paper, we propose DL-Droid, a deep learning system to detect malicious Android applications through dynamic analysis using stateful input generation. Experiments performed with over 30,000 applications (benign and malware) on real devices are presented. Furthermore, experiments were also conducted to compare the detection performance and code coverage of the stateful input generation method with the commonly used stateless approach using the deep learning system. Our study reveals that DL-Droid can achieve up to 97.8% detection rate (with dynamic features only) and 99.6% detection rate (with dynamic + static features) respectively which outperforms traditional machine learning techniques. Furthermore, the results highlight the significance of enhanced input generation for dynamic analysis as DL-Droid with the state-based input generation is shown to outperform the existing state-of-the-art approaches

A systematic approach to the formulation of anti-onychomycotic nail patches

Nail patches have a potential role as drug carriers for the topical treatment of nail diseases such as onychomycosis, a common condition. O ur aim was therefore to develop a systematic and novel appr oach to the formulat ion of a simple drug -in-adhesive ungual patch. Twelve pressure -sensitive adhesives (PSAs), four backing membranes, two release liners and three drugs were screened for pharmaceutical and mechanical properties . From this initial screeni ng, two PSAs, two drugs, one backing membrane and one release liner were selected for further investigation. Patches were prepared by solvent -casting and characterised. The patches had good uniformity of thickness and of drug content, and showed minimal drug crystallisation during six month s of storage. Meanwhile, the d rug stability in the patch upon storage and patch adhesion to the nail was influenced by the nature of the drug, the PSA and the backing membrane . The reported methodology paves the way for a systematic formulation of ungual nail patches to add to the armamentarium of nail medicines . Further , from this work, the best patch formulation has been identified

Arrays of optical vortices formed by "fork" holograms

Singular light beams with optical vortices (OV) are often generated by means of thin binary gratings with groove bifurcation ("fork holograms") that produce a set of diffracted beams with different OV charges. Usually, only single separate beams are used and investigated; here we consider the whole set of diffracted OV beams that, at certain conditions, are involved in efficient mutual interference to form a characteristic pattern where the ring-like structure of separate OV beams is replaced by series of bright and dark lines between adjacent diffraction orders. This pattern, well developed for high diffraction orders, reflects the main spatial properties of the diffracted beams as well as of the fork grating used for their generation. In particular, it confirms the theoretical model for the diffracted beams (Kummer beam model) and enables to determine the sign and the absolute value of the phase singularity embedded in the hologram.Comment: 9 pages, 8 figure

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16x16 and 32x32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.Comment: v3: Performance/complexity comparison of the proposed scheme with other large-MIMO architectures/detectors has been added (Sec. IV-D). The paper has been accepted for publication in IEEE Journal of Selected Topics in Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO Systems. v2: Section V on Channel Estimation is update