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1

Joshi, Ankit, Komesh Borkar, Rohit Dhote, et al. "A Machine Learning Technique to Detect Malware." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 188–93. http://dx.doi.org/10.22214/ijraset.2022.47841.

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Анотація:
Abstract: Organizations have been threatened by malware for a long time, but timely detection of the virus remains a challenge. Malware may quickly damage the system by doing pointless tasks that burden it and prevent it from operating efficiently. There are two ways to detect malware: the traditional method that relies on the malware's signature and the behavior-based approach. The malware's behavior is characterized by the action it conducts when active in the machine, such as executing the operating system functions and downloading infected files from the internet. Based on how it behaves,
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2

Miraglia, Armando, and Matteo Casenove. "Fight fire with fire: the ultimate active defence." Information & Computer Security 24, no. 3 (2016): 288–96. http://dx.doi.org/10.1108/ics-01-2015-0004.

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Анотація:
Purpose This paper proposes an approach to deal with malware and botnets, which in recent years have become one of the major threats in the cyber world. These malicious pieces of software can cause harm not only to the infected victims but also to actors at a much larger scale. For this reason, defenders, namely, security researchers and analysts, and law enforcement have fought back and contained the spreading infections. However, the fight is fundamentally asymmetric. Design/methodology/approach In this paper, the authors argue the need to equip defenders with more powerful active defence to
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3

Zhang, Hong, Shumin Yang, Guowen Wu, Shigen Shen, and Qiying Cao. "Steady-State Availability Evaluation for Heterogeneous Edge Computing-Enabled WSNs with Malware Infections." Mobile Information Systems 2022 (April 11, 2022): 1–16. http://dx.doi.org/10.1155/2022/4743605.

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Анотація:
To evaluate the steady-state availability of heterogeneous edge computing-enabled wireless sensor networks (HECWSNs) with malware infections, we first propose a Stackelberg attack-defence game to predict the optimal strategies of malware and intrusion detection systems (IDSs) deployed in heterogeneous sensor nodes (HSNs). Next, we present a new malware infection model—heterogeneous susceptible-threatened-active-recovered-dead (HSTARD) based on epidemic theory. Then, considering the heterogeneity of sink sensor nodes and common sensor nodes and the malware attack correlation, we derive the stat
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4

Shatnawi, Ahmed S., Aya Jaradat, Tuqa Bani Yaseen, Eyad Taqieddin, Mahmoud Al-Ayyoub, and Dheya Mustafa. "An Android Malware Detection Leveraging Machine Learning." Wireless Communications and Mobile Computing 2022 (May 6, 2022): 1–12. http://dx.doi.org/10.1155/2022/1830201.

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Анотація:
Android applications have recently witnessed a pronounced progress, making them among the fastest growing technological fields to thrive and advance. However, such level of growth does not evolve without some cost. This particularly involves increased security threats that the underlying applications and their users usually fall prey to. As malware becomes increasingly more capable of penetrating these applications and exploiting them in suspicious actions, the need for active research endeavors to counter these malicious programs becomes imminent. Some of the studies are based on dynamic anal
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5

Londoño, Sebastián, Christian Urcuqui, Manuel Fuentes Amaya, Johan Gómez, and Andrés Navarro Cadavid. "SafeCandy: System for security, analysis and validation in Android." Sistemas y Telemática 13, no. 35 (2015): 89–102. http://dx.doi.org/10.18046/syt.v13i35.2154.

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Анотація:
Android is an operating system which currently has over one billion active users for all their mobile devices, a market impact that is influencing an increase in the amount of information that can be obtained from different users, facts that have motivated the development of malicious software by cybercriminals. To solve the problems caused by malware, Android implements a different architecture and security controls, such as a unique user ID (UID) for each application, while an API permits its distribution platform, Google Play applications. It has been shown that there are ways to violate th
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6

Sartea, Riccardo, Alessandro Farinelli, and Matteo Murari. "SECUR-AMA: Active Malware Analysis Based on Monte Carlo Tree Search for Android Systems." Engineering Applications of Artificial Intelligence 87 (January 2020): 103303. http://dx.doi.org/10.1016/j.engappai.2019.103303.

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7

O'Callaghan, Derek, Martin Harrigan, Joe Carthy, and Pádraig Cunningham. "Network Analysis of Recurring YouTube Spam Campaigns." Proceedings of the International AAAI Conference on Web and Social Media 6, no. 1 (2021): 531–34. http://dx.doi.org/10.1609/icwsm.v6i1.14288.

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Анотація:
As the popularity of content sharing websites has increased, they have become targets for spam, phishing and the distribution of malware. On YouTube, the facility for users to post comments can be used by spam campaigns to direct unsuspecting users to malicious third-party websites. In this paper, we demonstrate how such campaigns can be tracked over time using network motif profiling, i.e. by tracking counts of indicative network motifs. By considering all motifs of up to five nodes, we identify discriminating motifs that reveal two distinctly different spam campaign strategies, and present a
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8

Duraisamy Soundrapandian, Pradeepkumar, and Geetha Subbiah. "MULBER: Effective Android Malware Clustering Using Evolutionary Feature Selection and Mahalanobis Distance Metric." Symmetry 14, no. 10 (2022): 2221. http://dx.doi.org/10.3390/sym14102221.

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Анотація:
Symmetric and asymmetric patterns are fascinating phenomena that show a level of co-existence in mobile application behavior analyses. For example, static phenomena, such as information sharing through collaboration with known apps, is a good example of a symmetric model of communication, and app collusion, where apps collaborate dynamically with unknown malware apps, is an example of a serious threat with an asymmetric pattern. The symmetric nature of app collaboration can become vulnerable when a vulnerability called PendingIntent is exchanged during Inter-Component Communication (ICC). The
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9

Nawaz, Umair, Muhammad Aleem, and Jerry Chun-Wei Lin. "On the evaluation of android malware detectors against code-obfuscation techniques." PeerJ Computer Science 8 (June 21, 2022): e1002. http://dx.doi.org/10.7717/peerj-cs.1002.

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Анотація:
The Android mobile platform is the most popular and dominates the cell phone market. With the increasing use of Android, malware developers have become active in circumventing security measures by using various obfuscation techniques. The obfuscation techniques are used to hide the malicious code in the Android applications to evade detection by anti-malware tools. Some attackers use the obfuscation techniques in isolation, while some attackers use a mixed approach (i.e., employing multiple obfuscation techniques simultaneously). Therefore, it is crucial to analyze the impact of the different
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10

Wu, Xiaojun, Qiying Cao, Juan Jin, Yuanjie Li, and Hong Zhang. "Nodes Availability Analysis of NB-IoT Based Heterogeneous Wireless Sensor Networks under Malware Infection." Wireless Communications and Mobile Computing 2019 (January 3, 2019): 1–9. http://dx.doi.org/10.1155/2019/4392839.

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Анотація:
The Narrowband Internet of Things (NB-IoT) is a main stream technology based on mobile communication system. The combination of NB-IoT and WSNs can active the application of WSNs. In order to evaluate the influence of node heterogeneity on malware propagation in NB-IoT based Heterogeneous Wireless Sensor Networks, we propose a node heterogeneity model based on node distribution and vulnerability differences, which can be used to analyze the availability of nodes. We then establish the node state transition model by epidemic theory and Markov chain. Further, we obtain the dynamic equations of t
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11

McDonald, Grant, Pavlos Papadopoulos, Nikolaos Pitropakis, Jawad Ahmad, and William J. Buchanan. "Ransomware: Analysing the Impact on Windows Active Directory Domain Services." Sensors 22, no. 3 (2022): 953. http://dx.doi.org/10.3390/s22030953.

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Анотація:
Ransomware has become an increasingly popular type of malware across the past decade and continues to rise in popularity due to its high profitability. Organisations and enterprises have become prime targets for ransomware as they are more likely to succumb to ransom demands as part of operating expenses to counter the cost incurred from downtime. Despite the prevalence of ransomware as a threat towards organisations, there is very little information outlining how ransomware affects Windows Server environments, and particularly its proprietary domain services such as Active Directory. Hence, w
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12

Oksiiuk, Oleksandr, Andriy Zerko, and Andriy Fesenko. "ANALYSIS OF THE PRIMARY TRENDS IN CYBERSECURITY." Information systems and technologies security, no. 1 (2) (2020): 3–8. http://dx.doi.org/10.17721/ists.2020.1.3-8.

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Анотація:
Open and free cyberspace increases the freedom of people and social communications, in such conditions it becomes especially important to search for new possibilities of ensuring the state security in view of the formation of a new confrontation field - cyberspace. It is important to analyze the actual problems of information security, actions of the world governments and world organizations for identifying the current state of modern trends in the cybersecurity field. Cybersecurity incidents affect the lives of consumers of informational and many other services, and cyberattacks targeting var
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13

Bux, Khuda, Muhammad Yousaf, Akhtar Hussain Jalbani, and Komal Batool. "Detection of Malicious Servers for Preventing Client-Side Attacks." January 2021 40, no. 1 (2021): 230–40. http://dx.doi.org/10.22581/muet1982.2101.20.

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Анотація:
The number of client-side attacks is increasing day-by-day. These attacks are launched by using various methods like phishing, drive-by downloads, click-frauds, social engineering, scareware, and ransomware. To get more advantage with less exertion and time, the attackers are focus on the clients, rather than servers which are more secured as compared to the clients. This makes clients as an easy target for the attackers on the Internet. A number of systems/tools have been created by the security community with various functions for detection of client-side attacks. The discovery of malicious
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14

Patel, Himanshu, Deep Patel, Jaspreet Ahluwalia, et al. "Evaluation of Survivability of the Automatically Obfuscated Android Malware." Applied Sciences 12, no. 10 (2022): 4969. http://dx.doi.org/10.3390/app12104969.

Повний текст джерела
Анотація:
Malware is a growing threat to all mobile platforms and hundreds of new malicious applications are being detected every day. At the same time, the development of automated software obfuscation techniques allows for the easy production of new malware variants even by attackers with entry-level programming skills. Such obfuscation techniques can evade the signature-based mechanism implemented in current antimalware technology. This paper presents the results of a study that examined how automated obfuscation techniques affect malicious and benign applications by two widely used malware detection
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15

Biberaj, Aleksander, Enida Sheme, Alban Rakipi, Sonila Xhaferllari, Renalda Kushe, and Mirjeta Alinci. "Cyber Attack Against E-Albania and Its Social, Economic and Strategic Effects." Journal of Corporate Governance, Insurance, and Risk Management 9, no. 2 (2022): 341–47. http://dx.doi.org/10.56578/jcgirm090204.

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Анотація:
Purpose: During last years, even because of pandemic situation caused by covid-19 virus, in Albania most of governmental public services for citizens, businesses and other customers were offered in an electronic way by creating a national database (e-Albania), offering more than 2200 services. As this electronic system was newly implemented, time after time it was attacked from hackers in different sectors of services, causing the interruption of service for hours, downloading all the confidential information and publishing them. After several partial attacks, in July 2022 came the general att
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16

Biran, Yahav, George Collins, Borky John M, and Joel Dubow. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. 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Khan, Mossaraf. "Malware Analysis Using Volatility." Digital Forensics (4n6) Journal, May 1, 2020, 8–14. http://dx.doi.org/10.46293/4n6/2020.02.02.01.

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Анотація:
Volatile Data of a computer is a temporary and they are created when a computer system is running aka in operational condition. They are removed immediately when the system powered off. It is stored on the Random Access Memory (RAM) and other temporary storage units such as Registars of the Computer and not in the main storage partitions of Hard Drives. It could be emails related information, chats or browser history, running processes related information, unsaved data, clipboard contents etc. The analysis of volatile memory for extracting forensic artifacts is called Memory Forensic. Volatile
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Dambra, Savino, Leyla Bilge, and Davide Balzarotti. "A Comparison of Systemic and Systematic Risks of Malware Encounters in Consumer and Enterprise Environments." ACM Transactions on Privacy and Security, October 3, 2022. http://dx.doi.org/10.1145/3565362.

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Malware is still a widespread problem and it is used by malicious actors to routinely compromise the security of computer systems. Consumers typically rely on a single AV product to detect and block possible malware infections, while corporations often install multiple security products, activate several layers of defenses, and establish security policies among employees. However, if a better security posture should lower the risk of malware infections, the actual extent to which this happens is still under debate by risk analysis experts. Moreover, the difference in risks encountered by consu
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