Intrusion detection using machine learning-hardened domain generation algorithms

Machine learning has recently been applied in a variety of areas in information technology due to its superiority over the typical computer algorithms. The machine learning approaches are being integrated into cybersecurity detection approaches with the primary aim of supporting or providing an alternative to the first line of defense in networks. Although the automation of these detection and analysis systems is potent in today’s changing technological environment, the usefulness of machine learning in cybersecurity requires evaluation. In this research, we present an analysis and address cybersecurity concerns of machine learning techniques used in the detection of intrusion, spam, and malware. The analysis will entail the evaluation of the current maturity of the machine learning solutions when identifying their primary limitations, which has prevented the immediate adoption of machine learning in cybersecurity

Face Recognition System Based on Gabor Wavelets Transform, Principal Component Analysis and Support Vector Machine

Face Recognition is a well-known image analysis application in the branches of pattern recognition and computer vision. It utilizes the uniqueness of human facial characteristics for personnel identification and verification. For a long time, the recognition of facial expressions by using computer-based applications has been an active area of study to recognize face scheme through a face image database. It is used in a variety of essential fields of modern life such as security systems, criminal identification, video retrieval, passport and credit cards. In general, face recognition process can be summarized in three distinct steps: preprocessing, feature extraction, and classification. At first, histogram equalization and median filter are applied as preprocessing methods. Secondly, Gabor wavelets transform extracts the features of desirable facial characterized by, orientation selectivity, spatial locality, and spatial frequency to keep up the variations caused by the varying of facial expression and illumination. In addition to that, Principal Component Analysis methodology (PCA) is used in dimensionality reduction. At last, Support vector machine (SVM) is applied in classifying the feature of the image according to the classis of every mage. In order to test the approach used in this research, experiments were running on Yale database of 165 images from 15 individuals in MATLAB environment. The results obtained from the experiments confirmed the accuracy and robustness of the proposed system

Theoretical Study of the Effects Type of Host’s Crystal on the Lasing Output of High – Power Thin –Disk Laser

Ytterbium-doped (Y2O3), (Sc2O3) and (YAG) crystals are very important for high-power thindisk lasers. These lasers have shown their ability to operate quasi-three-level materials with high efficiency as well as high thermal conductivity ratio for crystalline hosts. All these reasons have required studying this type of laser. In the present work, the analytical solution was found for the equation of laser output power, pumping threshold power, and efficiency of a quasi-three-level thin disk laser. The numerical solution of these equations was also found through the Matlab program at the fundamental transverse mode, at a temperature of 299K0 and with high pumping capabilities in order to know the effect of the type of crystal host (YAG, Sc2O3,Lu2O3) on the laser production of this design and thermal effect when operating continuously. We found out that the crystal host (Lu2O3) was the best type of these hosts in obtaining the highest laser output power and efficiency at all values of pumping powe

Adaptive Emotional Personality Model based on Fuzzy Logic Interpretation of Five Factor Theory

In recent years, emotional personality has found an important application in the field of human machine interaction. Interesting examples of this domain are computer games, interface agents, human-robot interaction, etc. However, few systems in this area include a model of personality, although it plays an important role in differentiating and determining the way they experience emotions and the way they behave. Personality simulation has always been a complex issue due to the complexity of the human personality itself, and the difficulty to model human psychology on electronic basis. Current efforts for emotion simulation are rather based on predefined set or inputs and its responses or on classical models which are simple approximate and have proven flaws. In this paper an emotional simulation system was presented. It utilizes the latest psychological theories to design a complex dynamic system that reacts to any environment, without being pre-programmed on sets of input. The design was relying on fuzzy logic to simulate human emotional reaction, thus increasing the accuracy by further emulating human brain and removing the pre-defined set of input and its matched output

FuncTeller: How Well Does eFPGA Hide Functionality?

Hardware intellectual property (IP) piracy is an emerging threat to the global supply chain. Correspondingly, various countermeasures aim to protect hardware IPs, such as logic locking, camouflaging, and split manufacturing. However, these countermeasures cannot always guarantee IP security. A malicious attacker can access the layout/netlist of the hardware IP protected by these countermeasures and further retrieve the design. To eliminate/bypass these vulnerabilities, a recent approach redacts the design's IP to an embedded field-programmable gate array (eFPGA), disabling the attacker's access to the layout/netlist. eFPGAs can be programmed with arbitrary functionality. Without the bitstream, the attacker cannot recover the functionality of the protected IP. Consequently, state-of-the-art attacks are inapplicable to pirate the redacted hardware IP. In this paper, we challenge the assumed security of eFPGA-based redaction. We present an attack to retrieve the hardware IP with only black-box access to a programmed eFPGA. We observe the effect of modern electronic design automation (EDA) tools on practical hardware circuits and leverage the observation to guide our attack. Thus, our proposed method FuncTeller selects minterms to query, recovering the circuit function within a reasonable time. We demonstrate the effectiveness and efficiency of FuncTeller on multiple circuits, including academic benchmark circuits, Stanford MIPS processor, IBEX processor, Common Evaluation Platform GPS, and Cybersecurity Awareness Worldwide competition circuits. Our results show that FuncTeller achieves an average accuracy greater than 85% over these tested circuits retrieving the design's functionality.Comment: To be published in the proceedings of the 32st USENIX Security Symposium, 202

Toward Efficient Low Cost Highly Accurate Emotion Speech Synthesizer,

Abstract: A Text to Speech (TTS) system with the ability to express emotions is an interesting technology that is still under development. There have been multiple proposals to simulate emotion so far, and there are multiple dimensions for assessment. No system guarantees high score in all of these dimensions, this means that no system works in a direction to get low computation load, small database along with high accuracy and excellent voice quality. After all of these qualities are relative and fuzzy and there is no rigid grading system. In this paper we will propose a new path for research that will work toward improving all of the quality factors together, so that future work can come up with a more optimum solution for the emotional TTS systems

A Fuzzy Case-Based Reasoning Model for Software Requirements Specifications Quality Assessment

Different software Quality Assurance (SQA) audit techniques are applied in the literature to determine whether the required standards and procedures within the Software Requirements Specification (SRS) phase are adhered to. The inspection of the Software Requirements Specification (iSRS) system is an analytical assurance tool which is proposed to strengthen the ability to scrutinize how to optimally create high-quality SRSs. The iSRS utilizes a Case-Based Reasoning (CBR) model in carrying out the SRS quality analysis based on the experience of the previously analyzed cases. This paper presents the contribution of integrating fuzzy Logic technique in the CBR steps to form a Fuzzy Case-Based Reasoning (FCBR) model for improving the reasoning and accuracy of the iSRS system. Additionally, for efficient cases retrieval in the CBR, relevant cases selection and nearest cases selection heuristic search algorithms are used in the system. Basically, the input to the relevant cases algorithm is the available cases in the system case base and the output is the relevant cases. The input to the nearest cases algorithm is the relevant cases and the output is the nearest cases. The fuzzy Logic technique works on the selected nearest cases and it utilizes similarity measurement methods to classify the cases into no-match, partial-match and complete-match cases. The features matching results assist the revised step of the CBR to generate a new solution. The implementation of the new FCBR model shows that converting numerical representation to qualitative terms simplifies the matching process and improves the decision-making of the system

PANC Study (Pancreatitis: A National Cohort Study): national cohort study examining the first 30 days from presentation of acute pancreatitis in the UK

Abstract Background Acute pancreatitis is a common, yet complex, emergency surgical presentation. Multiple guidelines exist and management can vary significantly. The aim of this first UK, multicentre, prospective cohort study was to assess the variation in management of acute pancreatitis to guide resource planning and optimize treatment. Methods All patients aged greater than or equal to 18 years presenting with acute pancreatitis, as per the Atlanta criteria, from March to April 2021 were eligible for inclusion and followed up for 30 days. Anonymized data were uploaded to a secure electronic database in line with local governance approvals. Results A total of 113 hospitals contributed data on 2580 patients, with an equal sex distribution and a mean age of 57 years. The aetiology was gallstones in 50.6 per cent, with idiopathic the next most common (22.4 per cent). In addition to the 7.6 per cent with a diagnosis of chronic pancreatitis, 20.1 per cent of patients had a previous episode of acute pancreatitis. One in 20 patients were classed as having severe pancreatitis, as per the Atlanta criteria. The overall mortality rate was 2.3 per cent at 30 days, but rose to one in three in the severe group. Predictors of death included male sex, increased age, and frailty; previous acute pancreatitis and gallstones as aetiologies were protective. Smoking status and body mass index did not affect death. Conclusion Most patients presenting with acute pancreatitis have a mild, self-limiting disease. Rates of patients with idiopathic pancreatitis are high. Recurrent attacks of pancreatitis are common, but are likely to have reduced risk of death on subsequent admissions. </jats:sec

On Differential Subordination and Superordination for Univalent Function Involving New Operator

The goal of this paper is to investigate some of the features of differential subordination of analytic univalent functions in an open unit disc. In addition, it has shed light on geometric features such as coefficient inequality, Hadamard product qualities, and the Komatu integral operator. Some intriguing results for third-order differential subordination and superordination of analytic univalent functions have been installed. Then, using the convolution of two linear operators, certain results of third order differential subordination involving linear operators were reported. As a result, we use features of the Komatu integral operator to analyze and study third-order subordinations and superordinations in relation to the convolution. Finally, several results for third order differential subordination in the open unit disk using generalized hypergeometric function have been addressed using the convolution operator