PkM Peningkatan Kemampuan Masyarakat Desa Terhadap Teknologi Informasi melalui Jaringan Internet Sebagai Penerapan IoT Desa Cerdas

Bucor Wetan Village is one of the villages in Pakuniran District, Probolinggo Regency, a village with a strong cultural culture and a religious community that makes villagers have a very high level of awareness of education. Such conditions are not matched by balanced infrastructure development, including uneven and unstable internet services. From these problems, the service team will provide training and assistance to improve the ability of the community to be able to build an internet network so that all residents will enjoy a stable internet network, the output of this activity will make the village smart with the ability to use information technology. he The method used with assistance starts planning, implementation, and evaluation. The results of community service have made the residents of Bucor Wetan Village have the ability to build an internet network and enjoy a stable internet.

Mitigation of Attacks via Improved Network Security in IoT Network using Machine Learning

In this paper, we develop a support vector machine (SVM) based attack mitigation technique from the IoT network. The SVM aims to classify the features related to the attacks based on pre-processed and feature extracted information. The simulation is conducted in terms of accuracy, precision, recall and f-measure over KDD datasets. The results show that the proposed SVM classifier obtains high grade of classification accuracy in both training and testing datasets

Analysis of Mobile Malware: A Systematic Review of Evolution and Infection Strategies

The open-source and popularity of Android attracts hackers and has multiplied security concerns targeting devices. As such, malware attacks on Android are one of the security challenges facing society. This paper presents an analysis of mobile malware evolution between 2000-2020. The paper presents mobile malware types and in-depth infection strategies malware deploys to infect mobile devices. Accordingly, factors that restricted the fast spread of early malware and those that enhance the fast propagation of recent malware are identified. Moreover, the paper discusses and classifies mobile malware based on privilege escalation and attack goals. Based on the reviewed survey papers, our research presents recommendations in the form of measures to cope with emerging security threats posed by malware and thus decrease threats and malware infection rates. Finally, we identify the need for a critical analysis of mobile malware frameworks to identify their weaknesses and strengths to develop a more robust, accurate, and scalable tool from an Android detection standpoint. The survey results facilitate the understanding of mobile malware evolution and the infection trend. They also help mobile malware analysts to understand the current evasion techniques mobile malware deploys

IoMT Malware Detection Approaches: Analysis and Research Challenges

The advancement in Information and Communications Technology (ICT) has changed the entire paradigm of computing. Because of such advancement, we have new types of computing and communication environments, for example, Internet of Things (IoT) that is a collection of smart IoT devices. The Internet of Medical Things (IoMT) is a specific type of IoT communication environment which deals with communication through the smart healthcare (medical) devices. Though IoT communication environment facilitates and supports our day-to-day activities, but at the same time it has also certain drawbacks as it suffers from several security and privacy issues, such as replay, man-in-the-middle, impersonation, privileged-insider, remote hijacking, password guessing and denial of service (DoS) attacks, and malware attacks. Among these attacks, the attacks which are performed through the malware botnet (i.e., Mirai) are the malignant attacks. The existence of malware botnets leads to attacks on confidentiality, integrity, authenticity and availability of the data and other resources of the system. In presence of such attacks, the sensitive data of IoT communication may be disclosed, altered or even may not be available to the authorized users. Therefore, it becomes essential to protect the IoT/IoMT environment from malware attacks. In this review paper, we first perform the study of various types of malware attacks, and their symptoms. We also discuss some architectures of IoT environment along with their applications. Next, a taxonomy of security protocols in IoT environment is provided. Moreover, we conduct a comparative study on various existing schemes for malware detection and prevention in IoT environment. Finally, some future research challenges and directions of malware detection in IoT/IoMT environment are highlighted

Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review

One of today's fastest-growing technologies is the Internet of Things (IoT). It is a technology that lets billions of smart devices or objects known as "Things" collect different kinds of data about themselves and their surroundings utilizing different sensors. For example, it could be used to keep an eye on and regulate industrial services, or it could be used to improve corporate operations. But the IoT currently faces more security threats than ever before. This review paper discusses the many sorts of cybersecurity attacks that may be used against IoT devices. Also, K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Naive Bayes (NB), and Artificial Neural Network (ANN) are examples of Machine Learning (ML) approaches that can be employed in IDS. The goal of this study is to show the results of analyzing various classification algorithms in terms of confusion matrix, accuracy, precision, specificity, sensitivity, and f-score to Develop an Intrusion Detection System (IDS) model

Integrated information gain with extra tree algorithm for feature permission analysis in android malware classification

The rapid growth of free applications in the android market has led to the fast spread of malware apps since users store their sensitive personal information on their mobile devices when using those apps. The permission mechanism is designed as a security layer to protect the android operating system by restricting access to local resources of the system at installation time and run time for updated versions of the android operating system. Even though permissions provide a secure layer to users, they can be exploited by attackers to threaten user privacy. Consequently, exploring the patterns of those permissions becomes necessary to find the relevant permission features that contribute to classifying android apps. However, with the era of big data and the rapid explosion of malware along with many unnecessary requested permissions, it has become a challenge to recognize the patterns of permissions from these data due to the irrelevant and redundant features that affect the classification performance and increase the complexity cost overhead. Ensemble-based Extra Tree - Feature Selection (FS-EX) algorithm was proposed in this study to explore the permission patterns by selecting a minimal-sized subset of highly discriminant permission features capable of discriminating against malware samples from nonmalware samples. The integrated Information Gain with Ensemble-based Extra Tree - Feature Selection (FS-IGEX) algorithm is proposed to assign weight values to permission features instead of binary values to determine the impact of weighted attribute variables on the classification performance. The two proposed methods based on Ensemble Extra Tree Feature Selection were evaluated on five datasets with various sample sizes and feature space using nine machine learning classifiers. Comparison studies were carried out between FS-EX subsets and the dataset of Full Permission features (FP) and the two approaches of the FS-IGEX method - the Permission-Binary (PB) approach and the Permission-Weighted (PW) approach. The permissions with PB were represented with binary values, whereas permissions with PW were represented with weighted values. The results demonstrated that the approach with the FS-EX was promising in obtaining the most prominent permission features related to the class target and attaining the same or close classification results in terms of accuracy with the highest accuracy mean of 96%, as compared to the FP. In addition, the PW approach of the FS-IGEX method had highly influential weighted permission features that could classify apps as malware and non-malware with the highest accuracy mean of 93%, compared to the PB approach of the FS-IGEX method and the FP

Security in 5G-Enabled Internet of Things Communication: Issues: Challenges, and Future Research Roadmap

5G mobile communication systems promote the mobile network to not only interconnect people, but also interconnect and control the machine and other devices. 5G-enabled Internet of Things (IoT) communication environment supports a wide-variety of applications, such as remote surgery, self-driving car, virtual reality, flying IoT drones, security and surveillance and many more. These applications help and assist the routine works of the community. In such communication environment, all the devices and users communicate through the Internet. Therefore, this communication agonizes from different types of security and privacy issues. It is also vulnerable to different types of possible attacks (for example, replay, impersonation, password reckoning, physical device stealing, session key computation, privileged-insider, malware, man-in-the-middle, malicious routing, and so on). It is then very crucial to protect the infrastructure of 5G-enabled IoT communication environment against these attacks. This necessitates the researchers working in this domain to propose various types of security protocols under different types of categories, like key management, user authentication/device authentication, access control/user access control and intrusion detection. In this survey paper, the details of various system models (i.e., network model and threat model) required for 5G-enabled IoT communication environment are provided. The details of security requirements and attacks possible in this communication environment are further added. The different types of security protocols are also provided. The analysis and comparison of the existing security protocols in 5G-enabled IoT communication environment are conducted. Some of the future research challenges and directions in the security of 5G-enabled IoT environment are displayed. The motivation of this work is to bring the details of different types of security protocols in 5G-enabled IoT under one roof so that the future researchers will be benefited with the conducted work

5G και IoT και σύγχρονες εφαρμογές

Η παρούσα εργασία ασχολείται με το ΙοΤ με δυνατότητα 5G. Αρχικά στην εργασία γίνεται αναφορά στην ιστορική εξέλιξη του 5G. Ακολουθεί αναφορά στην τεχνολογία 5G, όπου αναφέρονται τα χαρακτηριστικά του 5G, τα οφέλη της τεχνολογίας 5G και παρουσιάζονται αναλυτικά οι τεχνολογίες για αλληλεπίδραση με ΙοΤ. Επίσης, γίνεται περιγραφή της τεχνολογίας ΙοΤ, όπου αποτυπώνονται οι προκλήσεις και τα χαρακτηριστικά του ΙοΤ, οι τεχνολογίες IoT και οι τεχνολογίες για αλληλεπίδραση με 5G. Ακολουθεί εκτενής αναφορά στην αρχιτεκτονική του συστήματος 5G - IoT, καθώς και στις απαιτήσεις ασφαλείας και τις πιθανές επιθέσεις σε επικοινωνία IoT με δυνατότητα. Στη συνέχεια, αναφέρονται τα υπάρχοντα πρωτόκολλα ασφαλείας σε περιβάλλον επικοινωνιών IoT με δυνατότητα 5G. Η εργασία ολοκληρώνεται με αναφορά στο υφιστάμενο εμπορικό πλαίσιο του 5G στην παγκόσμια βιομηχανία, αλλά και με ιδιαίτερη αναφορά στις μελλοντικές προκλήσεις της τεχνολογίας που μελετήθηκε.The present work deals with IoT with 5G capability. Initially, the work refers to the historical development of 5G. The following is a reference to 5G technology, which mentions the features of 5G, the benefits of 5G technology and presents in detail the technologies for interaction with IoT. It also describes IoT technology, which captures the challenges and features of IoT, IoT technologies and technologies for 5G interaction. The following is an extensive reference to the 5G - IoT system architecture, as well as security requirements and possible attacks on IoT communication capabilities. The following is a list of existing security protocols in a 5G IoT communication environment. The work concludes with a reference to the current commercial context of 5G in the global industry, but also with a special reference to the future challenges of the technology studied