Malware

Android is a very popular operating system for mobile devices. It is also being used for the IoT enabled devices in the present scenario. The popularity if the android also makes it susceptible to attacks with respect to security. The malware writers are showcasing their skills in various ways to bypass the security mechanisms utilized by the android operating system developers. Researchers are also proposing several new methods of identifying the malware app and helping remove them. The various techniques being used by the researchers are such as static analysis, dynamic analysis and hybrid analysis. The machine learning methods are most common that use these techniques to propose their methodologies. The machine learning techniques are also classified as supervised, unsupervised and reinforcement techniques. Researchers have used one, two or combination of techniques to detect intrusion. In this paper we compare various machine learning techniques and show the results achieved from the different machine learning techniques. We have compared results of algorithms such as Random Forest, J48, Logistic Regression. Furthermore, we have also executed the algorithms that work on Voting techniques and have also shown that Random Forest performs better that other algorithms.

Many researchers have built different kinds of malware in the past years. Theses malwares have helped in discovering security flaws in many systems, and they have actually contributed a lot in the security industry. This paper proposes a malware called Tmalware that aims to collect information from a user that is using either a Windows or Linux Operating System.

Malware is the main computer security threat that can cause damage to user's devices and company's infrastructure. End users who want to download executable files from the Internet are currently presented by a binary choice (OK or Cancel) but there is no viable third alternative for uncertainty (Not Sure). Reporting to any security agency or company for status inquiry regarding executable files normally lack of efficiency in terms of reporting back to the users in a timely manner. As a consequence, developing a more efficient approach that provide a prompt response to the users on reported suspicious files is important in order to encourage more end users engagement in malware reporting thus ultimately reducing the number of unknown malware in the wild. This study proposes a new automatic and scalable malware analyzer that is able to quickly scrutinize and help generate report for each malware detected. The implementation of the approach includes both the client (user's ...

Ransomware has rapidly become one of the internet's greatest threats, with occasional new iterations being deployed. It is a rising challenge to company data and new versions emerge regularly as a result of the vast sums of money to be made. Ransomware attacks have been a worldwide incidence, with the primary goal of making monetary profits by illicit means. It will result in the destruction of classified records, interruption of routine activities and damage to the credibility of a company. It encrypts the files of targets and shows alerts, demanding payment until it is possible to decrypt the data. This malware is liable for hundreds of millions of dollars in losses per year. The demand for ransom is usually in the form of virtual currencies since bitcoin is difficult to trace. This paper offers a brief analysis of the history of ransomware, best practices for seeking mitigation steps, and enduring responses to the vulnerability of ransomware that threatens the safety of machines, network protection, and records.

Rootkit is an auxiliary tool for sniffing, stealing and hiding, so it has become the key component in almost all successful attacks. Analysis of rootkits will provide system administrators and security software managers the ability to detect and prevent a computer being compromised. Ontology will provide detailed conceptualization to represent the rootkit concepts and its relationships to other security concepts in cyber-attack domain. In this paper we presented an ontology for rootkits which contains many concepts relating to security, cyber-attacks and operating systems. We divided rootkits according to four attributes, and expanded the ontology for rootkits accordingly. This ontology can be used to distinguish different types of rootkits

Background and Objective: Every second, on average, 8 (eight) new malware are created. So, our goal is to propose an antivirus, endowed with artificial intelligence, able of identifying malwares through models based on fast training and high-performance neural networks. Methods: Our NGAV (Next Generation Antivirus) is equipped with an authorial ELM (Extreme Learning Morphological) machine. Our bmELMs (Bitwise-Morphological ELMs) are inspired by the image processing theory of Mathematical Morphology. We claim that bmELMs are able to adapt in any machine learning dataset. Inspired by Mathematical Morphology, our bmELMs are capable of modeling any form present at the decisions boundaries of neural networks. Results: Our bmELMs results are compared with classical ELMs and evaluated through widely used classification metrics. Our antivirus, provided with Bitwise-Morphology, achieves an average accuracy of 97.88%, 93.07%, 93.07% and 91.74% in malware detection of PE (Portable Executable), Java, JavaScript and PHP, respectively. Conclusions: Our NGAV enables high performance, large capacity of parallelism, and simple, low-power architecture with low power consumption. We concluded that our Bitwise-Morphology assists to the main requirements for the proper operation and confection of antivirus in hardware. Introduction The term "Malware" means the combination of the words "malicious" and "software". The main objective of a malware is to allow access to any device without explicit permission and/or knowledge of its owner. Millions of new malwares are created every year in order of increasing production [1]. In the fourth quarter of 2017, more than 63,000,000 (sixty-three million) new malware were identified, meaning an increase of approximately 36% over the year 2016, in a growing production of 8 (eight) new malwares per second in the mentioned period [1]. Malwares are a cyber-pandemic with alarming levels of infections in all continents. Virtual pests are capable to promote irreversible and irrecoverable financial and reputation damages [1]. Traditional antiviruses are widely employed as a great solution in relation to cyber-protection. Antiviruses are present in almost all personal computers in a compulsory way [1]. The promised protection, however, is not always fulfilled. One of the reasons concerns to the retrograde form, based on blacklists, of the performance of conventional antiviruses. That is, the suspect executable is compared to a blacklist made from previous accusations. Therefore, if the antivirus database is not updated, then the malware is not identified and the infection happens.

With the increasing volume of smartphones, computers, and sensors in the Internet of Things (IoT) model, enhancing security and preventing ransom attacks have become a major concern. Traditional security mechanisms are no longer applicable due to the involvement of devices with limited resources, which require more computing power and resources. Ransomware is comparatively a new and cruel malware in cyberspace with higher rates of attacks around the world. Ransomware could encrypt entire data to make users unable to access their files and important information. In some cases, the system has been hostage completely by the hackers, and the user may receive a demand for ransom money using different resources o access of his/her own data/system. One of the problems associated with the Internet of Things is how to keep your smartphones secure and keep your data safe as most of the antivirus solutions are not useful in this case. This research concludes the impact of ransomware on the IoT, malware processes, and work on detecting and monitoring smartphone infections. The paper also discusses ransomware awareness to end-user with strategy to defeat it.

1. Malware Malware murapakan singkatan dari Malicious Sofware, yang artinya sebuah program jahat, seperti namanya, malware dibuat dengan tujuan untuk merusak atau mengambil alih control sebuah computer, bisa juga untuk mengambil informasi yang ada didalamnya Sebuah malware melekatkan dirinya padanya sebuah halaman website, pop up iklan pada website, toolbar, atau aplikasi gratis yang biasa didownload user pada website, malware tersebut akan masuk secara sembunyi-sembunyi melalui komponen yang sudah terinfeksi tesrsebut ke dalam computer korban. ktika malware sudah berada didalam siste, dia akan mencuri informasi yang tersimpan pada computer tersbut seperti password atau detail akun penting lainnya. (Awan, 2020). Efek dari malicious software biasa jauh lebih berbahaya bagi corporates dibanding untuk personal user. Jika malware menyerang jaringan sistem Anda, mereka bisa menyebabkan kerusakan dan gangguan yang meluas, yang memerlukan upaya pemulihan ekstensif di dalam organisasi. Malware juga memiliki beberapa nama lain seperti badware dan di dokumen legal, malware lebih sering disebut sebagai computer contamination (kontaminasi sistem komputer). Sehingga apabila Anda melihat kata itu, itu hanyalah cara lain untuk menyebut malware. Sasaran utama malware menarget banyak sekali korban, malware dapat digunakan untuk mematai-matai seseorang, mencuri berbagai data pribadi yang dimiliki orang lain, merusak program keamanan, dan masih banyak lagi. Apapun target dari malware intinya program ini dapat merugikan berbagai pihak yang disusupi oleh Malware. Namun secara umum, malware biasanya diciptakan dengan tujuan merusak suatu software dan sistem operasi lewat kode/script yang tidak diketahui. Jadi pihak yang menciptakan malware menyisipkan malware secara tersembunyi oleh pihak yang menciptakannya.(https:// www.klikmania.net/) Tipe Malware Malware berkembang dengan pesat seiring perkembangan jaman, Berikut adalah contoh malware yang sering kita jumpai: • Virus Sebuah virus computer bekerja seperti virus pada manusia. Mereka menyebar dengan cepat, penyebaran virus dipercepat atau dikarenakan karena ulah manusia. Virus tersebut akan sangat mengganggu kinerja perngakat yang aterjangkit. Virus kmputer menyebar ke computer lainnya

A. Pendahuluan Di era modern ini penggunaan perangkat lunak sangatlah penting dalam kehidupan sehari-hari, baik itu untuk bekerja, sekolah maupun kegiatan rumah tangga semuanya membutuhkan bantuan dari perangkat digital. Banyak data-data penting baik yang bersifat umum maupun pribadi tersimpan dalam perangkat digital yang sewaktu-waktu bisa sangat di butuhkan. Data-data tersebut adalah sasaran empuk bagi para penjahat di dunia digital untuk bisa melakukan kejahatan. Mereka biasanya akan melakukan sabotase ke dalam perangkat digital kita dan menjadikan data-data tersebut sebagai sandera lalu meminta imbalan tertentu atas sandera tersebut atau juga langsung mencuri data tersebut untuk selanjutnya dijual atau dijadikan sebagai bahan melakukan kejahatan lainnya. Cara yang dilakukan oleh para penjahat digital agar bisa menerobos perangkat digital kita adalah dengan menggunakan Malware. "Malware yang merupakan singkatan dari Malicious Software, yang artinya sebuah program jahat. Seperti namanya, malware dibuat dengan tujuan untuk merusakatau mengambil alih kontrol sebuah komputer, bisa juga untuk mengambil informasi yang ada di dalamnya (Setiawan dan Yulianto, 2020). Sebagai pengguna perangkat digital yang cerdas kita tentunya harus bisa mengantisipasi agar perangkat kita tidak terkena malware. Dan cara yang terbaik adalah dengan mencegah malware tersebut mauk ke dalam perangkat digital kita.

Internet users use the web every day for Browsing, Email, Banking, Social Media, and Web File & Video downloads. This research paper aims to help world internet users how not to get victimized to EMOTET malware-A Banking Credentials Stealer. Emotet is a very advanced modular trojan malware that primarily targets financial systems and internet users to steal financial and personal information by sending phishing emails to the people in question and self-spreading. Emotet also drops and downloads other banking trojans such as Trickbot, Ursnif, and IceDiD to exploit systems further and encrypts the large chunk of victim sensitive data with Ryuk ransomware payloads to benefit cyber attackers. United States Computer Emergency Readiness Team (US-CERT) issued an alert already concerning malicious Emotet campaign attackers. US-CERT also concluded that Emotet malware is the most destructive and costly malware affecting federal, state, local, tribal, governments, private businesses, non-profit organizations, and individuals. A research conducted by top cybersecurity company CrowdStrike revealed that dealing with Emotet infections costs $1 million per incident to remediate. In general, Emotet spread through emails when a user opens phishing attachments and clicking on phishing links such as malicious URL links, fake PDFs, and macro-enabled Microsoft Word documents. Therefore, this paper aims to address a complete understanding of what Emotet malware is, how dangerous the operation of Emotet is, its countermeasures, and will present robust Security Situational Awareness (SSA) to all internet users about Emotet malware. This paper will use a survey questionnaire as a qualitative research methodology instrument to collect data and know-how internet users are familiar with Emotet Malware. The survey results are shocked to see how internet users lack situational awareness about Emotet. In conclusion, the paper provides precautions, mitigation actions, and recommendations to prevent user computers from Emotet infections with Security Situational Awareness (SSA).

This study has been undertaken to provide an understanding on the level of the general public's knowledge about ransomware and its potential damage or financial loss. Questions have been asked including if payment would be made if the users files were encrypted. By identifying what the general public's understanding level is, this will assist in assessing if ransomware is still a financially lucrative method for hackers. The data collection tool being used within this study is a survey, it has been distributed to the general public to help the results of this study remain fair and unbiased. The survey has provided anonymity to its participants by only collecting the answers of the survey and no personal details such as age, gender or occupation. The results of this study clearly indicate that overall the general public is lacking an understating of the devastating effects that ransomware can have on systems or the financial loss it can cause. Visualised through graphs and charts, this provides a clear visual representation of the general public's lack of knowledge around ransomware. Participants of this study have been diverse in terms of age, gender and occupation in order to reduce participant bias. A limitation of this study is the small participant group of 40 persons, larger scale data collection could provide healthier outcomes and further back up the research results. Overall, clear evidence has been obtained and demonstrated in this article verifying that the general public's understanding is very limited when it comes to the threats of ransomware.

Cyberstalking is a special form of stalking and involves the use of information and communication technologies as the means and the medium of harassment or intimidation. Cyberstalking can lead to significant and long lasting psychological, economic or even physical effects, and can be a platform for the commission of violent crimes. In the last decade, cyberstalking has received significant attention from researchers, lawmakers, policy officials, and law enforcement agencies. Yet, although there is a significant body of literature on the topic, which recognizes cyberstalking as a very serious and growing problem and discusses various aspects of it, we believe that the phenomenon is not sufficiently examined, particularly considering the rapidly evolving technologies, which give perpetrators unprecedented capabilities. In this paper, in an interdisciplinary approach, we review relevant research and look into the criminalization of cyberstalking. Our paper extends existing knowledge of the phenomenon by analyzing a number of recent real cases, obtained mainly through an online legal research service, to reveal the nature of cyberstalking. We outline the most important aspects and issues raised by this phenomenon and make a number of recommendations as possible solutions to mitigating the risk, from education and awareness to adequate technology and legal response.

Credit card fraud presents an impressive array of forms and methods, often involving sophisticated means, organized crime aspects, and very significant criminal proceeds. Based on an extensive inquiry that involved the study of a large number of credit card fraud cases brought to the United States federal courts in violation of 18 U.S.C. § 1029(a)(1)-(5), press releases from law enforcement organizations, and information security reports, this article discusses the legal elements, the essential perpetration aspects, and the most relevant sentencing enhancements for these crimes, and proposes a number of improvements. The contributions of this article can be used for a more effective legal and judicial response in the process of risk identification and mitigation, and for developing awareness and training programs. Although the article focuses on one jurisdiction, the findings, particularly those in the perpetration aspects section, and the conclusion would be useful to a global audience.

This article is an extensive inquiry into computer damage cases based on the comprehensive study of over three hundred cases brought to courts in violation of 18 U.S.C. § 1030(a)(5). Based on an empirical categorization of the essential aspects of computer damage cases, the article analyzes the most relevant issues, interpretations, and arguments available for each computer damage category. These categories include fundamental facets, such as legal elements; motive and intent; results; profile of perpetrators; and means of perpetration, including, if applicable, the software involved.

Part I concerns theoretical aspects and discusses the legal elements of computer damage offenses under the CFAA. Part II considers the practical aspects and discusses the essential features involved in the perpetration of these offenses and the profile of attackers. Finally, Part III provides a summary of findings and the implications of this study for stakeholders.

This article makes two important contributions: a comprehensive analysis and a conceptual approach for this area. The findings will improve the investigation, prosecution and litigation of such cases in courts, help organizations in their process of identification and mitigation of risks, and stimulate more research in this area. Finally, although this article focused exclusively on one jurisdiction, the findings can be of interest to a wider, global context.

Internet of Things (IoT) is being considered as the growth engine for industrial revolution 4.0. The combination of IoT, cloud computing and healthcare can contribute in ensuring well-being of people. One important challenge of IoT network is maintaining privacy and to overcome security threats. This paper provides a systematic review of the security aspects of IoT. Firstly, the application of IoT in industrial and medical service scenarios are described, and the security threats are discussed for the different layers of IoT healthcare architecture. Secondly, different types of existing malware including spyware, viruses, worms, keyloggers, and trojan horses are described in the context of IoT. Thirdly, some of the recent malware attacks such as Mirai, echobot and reaper are discussed. Next, a comparative discussion is presented on the effectiveness of different machine learning algorithms in mitigating the security threats. It is found that the k-nearest neighbor (kNN) machine learning algorithm exhibits excellent accuracy in detecting malware. This paper also reviews different tools for ransomware detection, classification and analysis. Finally, a discussion is presented on the existing security issues, open challenges and possible future scopes in ensuring IoT security.

Malware is today one of the biggest security threat to internet. People today use terms such as malware, spyware, or ransomware much more than the term "virus" where Malware can steal your information, make your device send SMS messages to premium rate text services, or install adware that forces you to view web pages or Download apps. We need a robust malware detection solution to counter this serious malware project that can effectively and efficiently recognis e malware apps. We will present SIGPID in our proposed system to perform data extraction and as SIGPID design is effective in malware detection. Our method defines the substantial work permission needed by an application and differentiate between essential and non-essential permissions and detect and remove the malware on such a basis.