Malicious attacks, malware, and ransomware families pose critical security issues to cybersecurity, it may cause catastrophic damages computer systems, data centers, web, mobile applications across various industries businesses. Traditional anti-ransomware systems struggle fight against newly created sophisticated attacks. Therefore, state-of-the-art techniques like traditional neural network-based architectures can be immensely utilized in the development of innovative solutions. In this...

Internet of Things (IoT) is rapidly emerging as the next generation communication infrastructure, where myriad multi-scale sensors and devices are seamlessly blended for ubiquitous computing communication. The rapid growth IoT applications has increased demand experienced professionals in area. Since few, if any, dedicated courses currently offered, most Science, Technology, Engineering, Mathematics (STEM) students will have limited or no exposure to development until after graduation...

With the rapid technological advancement, security has become a major issue due to increase in malware activity that poses serious threat and safety of both computer systems stakeholders. To maintain stakeholders, particularly, end users security, protecting data from fraudulent efforts is one most pressing concerns. A set malicious programming code, scripts, active content, or intrusive software designed destroy intended programs mobile web applications referred as malware. According study,...

Along with the rapid growth of new science andtechnology, functions smartphones become more and morepowerful. Nevertheless, everything has two aspects. Smartphonesbring so much convenience for people also bring securityrisks at same time. Malicious application a bigthreat to mobile security. Thus, an efficiency security analysisand detection method is important necessary. Due toattacking malicious application, user could not use smartphonenormally personal information be stolen. What...

Malware classification is a critical part in the cyber-security. Traditional methodologies for malware typically use static analysis and dynamic to identify malware. In this paper, methodology based on its binary image extracting local pattern (LBP) features proposed. First, images are reorganized into 3 by grids which mainly used extract LBP feature. Second, implemented that it useful or texture classification. Finally, Tensorflow, library machine learning, applied classify with Performance...

This paper presents a detection system for theDistributed Denial of Service (DDoS) attack based on neuralnetwork, which is implemented in the Apache Hadoop clusterand HBase system. While there are already manyapproaches DDoS detection, two mainchallenges: learning capability systemand ability to process huge unstructured dataset. Themain contribution this develop detectionsystem with adapt new types DDoSattacks and store analyze unstructureddataset collected from network logs. Particularly,...

Fake news detection research has appeared for a couple of years and is relatively new difficult field. The difficulties come from the semantics natural languages manual identification via human beings, let along machines. In this project, we propose to analyze performance several machine learning algorithms integrating tools such as FakeNewsTracker[1], doc2vec, Support Vector Machine (SVM), decision trees. Our preliminary results indicate that SVM trees are suitable identify fake with an...

Quantum-based Machine Learning (QML) combines quantum computing (QC) with machine learning (ML), which can be applied in various sectors, and there is a high demand for QML professionals. However, not yet many schools' curricula. We design labware the basic concepts of QC, ML, their applications science engineering fields Google Colab, applying three-stage strategy efficient effective student learning.

Background/Objectives: Smart technologies have the potential to be rapid, sensitive, and cost-effective tools for real-life monitoring of cognitive function among older adults. Identifying barriers using remote testing in adults’ daily lives is essential. However, obstacles utilizing digital tests community-dwelling adults with probable Alzheimer’s Disease (AD) remain unclear. The purpose this study was investigate AD toward mobile app-based assessment. Methods: This a qualitative study....

The work described in this paper consists of a temperature tracking system that follows Client-Server architecture. A Raspberry Pi, System-on-a-Chip (SoC) device, is responsible for sensing the and streaming it to server, readings then are displayed mobile android application. For system, python application was developed sense stream temperature, servlet read store SQLite database, Android display from server. initial versions project used SoC device as server (storing into local database),...

The primary goal of the authentic learning provides students with an engaging and motivating environment for hands-on experiences in solving real-world security problems. Each topic consists pre-lab, lab, post-lab (Pre/Lab/Post) activities. With approach, we design develop portable labware on Google CoLab ML ransomware detection prevention so that can access practice these labs anywhere anytime without time tedious installation configuration which will help more focus concepts getting...

The security threats to mobile applications are growing explosively. Mobile apps flaws and defects open doors for hackers break in access sensitive information. Defensive requirements analysis should be an integral part of secure SDLC. Developers need consider the information confidentiality data integrity, verify early development lifecycle rather than fixing holes after attacking leaks take place. Early eliminating known vulnerabilities will help developers increase reduce likelihood...

Nowadays, big data contains infinite business opportunities. Companies begin to analyze their predict potential customers and decisions using Naïve Bayes Classifier, Association Rule Mining, Decision Tree other famous algorithms. An accurate classification result may help companies leading in its industry. seek find feasible intelligences obtain reliable prediction results. In this paper we propose an association rule mining improve Classifier. Classifier is one of the algorithm but based on...

The number one threat to the digital world is exponential increase in ransomware attacks. Ransomware malware that prevents victims from accessing their resources by locking or encrypting data until a ransom paid. With individuals and businesses growing dependencies on technology Internet, researchers cyber security field are looking for different measures prevent malicious attackers having successful campaign. A new variant being introduced daily, thus behavior-based analysis of detecting...

As mobile computing is now becoming more and popular, the security threats to applications are also growing explosively. Mobile app flaws defects could open doors for hackers break into them access sensitive information. Most vulnerabilities should be addressed in early stage of software development. However, many development professionals lack awareness importance vulnerability necessary knowledge skills at stage. The combination prevalence devices rapid growth has resulted a shortage...

E-mail service is one of the most popular Internet communication services. Thousands companies, organizations and individuals use e-mail every day get benefit from it. However, an amount spam emails always hang around us bring down our productivity. We urgently need a filtering to clean up network environment. A using Association Rule Naïve Bayes Classifier recommended here. Instead focusing on increasing precision rate, we try preserve all non-spam as first priority. In real world...

Electronic mail has nowadays become a convenient and inexpensive way for communication regardless of the distance. However, an increasing volume unsolicited emails is bringing down productivity dramatically. There need reliable anti-spam filters to separate such messages from legitimate ones. The Naïve Bayesian classifier suggested as effective engine pick out spam emails. We have developed filter that employs this content-based classifier. This statistic-based was trained on Enron Spam...

This paper presents principles of Defensive Programming and examines the growing concern that these are not effectively incorporated into Computer Science related computing degree programs' curricula. To support this concern, applied to a case study - Cross-site Scripting cybersecurity attacks. concludes plays an important role in preventing attacks should thus be more aggressively integrated CS courses such as Programming, Algorithms, Databases, Architecture Organization, Networks.

As mobile computing is becoming more and popular, the security threats to applications are simultaneously increasing explosively. Most malicious activities hack user's private information, such as contact location hijack transactions communications, exploit confidential enterprise data stored in databases or cache on devices. Database one of most important areas be addressed. Many schools integrating database topics into cybersecurity education. This paper addresses needs for pedagogical...

Denial of Service (DoS) is one the common attempts in security hacking for making computation resources unavailable or to impair geographical networks. In this paper, we detect attack from publicly available datasets using Logistic regression, Naive Bayes algorithm and artificial neural The results our experiments indicate that accuracy, ROC curve balanced accuracy network were higher than logistic regression slightly imbalanced distribution dataset.