scholarly journals A Smart Agent Design for Cyber Security Based on Honeypot and Machine Learning

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Nadiya El Kamel ◽  
Mohamed Eddabbah ◽  
Youssef Lmoumen ◽  
Raja Touahni
Keyword(s):  
Machine Learning ◽  
Cyber Security ◽  
Software Systems ◽  
The Internet ◽  
Cyber Attack ◽  
Security Risks ◽  
Network Attack ◽  
Network Information ◽  
Internet Users ◽  
Set Up

The development of Internet and social media contributes to multiplying the data produced on the Internet and the connected nodes, but the default installation and the configuration of variety of software systems represent some security holes and shortcomings, while the majority of Internet users have not really set up safety awareness, leading to huge security risks. With the development of network attack techniques, every host on the Internet has become the target of attacks. Therefore, the network information security cannot be ignored as a problem. To deal with 0-day and future attacks, the honeypot technique can be used not only passively as an information system, but also to reinforce the traditional defense systems against future attacks. In this paper, we present an introduction of machine learning and honeypot systems, and based on these technologies, we design a smart agent for cyber-attack prevention and prediction.

scholarly journals A conceptual framework for cyber security awareness and education in SA

2014 ◽  
Vol 52 ◽  
Author(s):  
Noluxolo Kortjan ◽  
Rossouw Von Solms
Keyword(s):  
South Africa ◽  
Cyber Security ◽  
Developed Countries ◽  
The Internet ◽  
Security Awareness ◽  
Key Factors ◽  
Primary Research ◽  
Daily Lives ◽  
Internet Users ◽  
Positive Effect

The Internet is becoming increasingly interwoven in the daily lives of many individuals, organisations and nations. It has, to a large extent, had a positive effect on the way people communicate. It has also introduced new avenues for business; and it has offered nations an opportunity to govern online. Nevertheless, although cyberspace offers an endless list of services and opportunities, it is also accompanied by many risks, of which many Internet users are not aware. As such, various countries have developed and implemented cyber-security awareness and education measures to counter the perceived ignorance of the Internet users. However, there is currently a definite lack in South Africa (SA) in this regard; as there are currently, little government-led and sponsored cyber-security awareness and education initiatives. The primary research objective of this paper, therefore, is to propose a cyber-security awareness and education framework for SA that would assist in creating a cyber-secure culture in SA among all of the users of the Internet. This framework will be developed on the basis of key factors extrapolated from a comparative analysis of relevant developed countries.

scholarly journals Implementation of ML Algorithm’s for Cyber Security

2021 ◽  
pp. 54-61
Author(s):  
Mohammad Asif ◽  
Prof. E. M. Chirchi
Keyword(s):  
Machine Learning ◽  
Cyber Security ◽  
The Internet ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
System Movement

Machine learning is embraced in an extensive variety of areas where it demonstrates its predominance over customary lead based calculations. These strategies are being coordinated in digital recognition frameworks with the objective of supporting or notwithstanding supplanting the principal level of security experts although the total mechanization of identification and examination is a luring objective, the adequacy of machine learning in digital security must be assessed with the due steadiness. With the improvement of the Internet, digital assaults are changing quickly and the digital security circumstance isn't hopeful. Since information are so critical in ML/DL strategies, we portray a portion of the normally utilized system datasets utilized in ML/DL, examine the difficulties of utilizing ML/DL for digital security and give recommendations to look into bearings. Malware has developed over the previous decades including novel engendering vectors, strong versatility methods and different and progressively propelled assault procedures. The most recent manifestation of malware is the infamous bot malware that furnish the aggressor with the capacity to remotely control traded off machines therefore making them a piece of systems of bargained machines otherwise called botnets. Bot malware depend on the Internet for proliferation, speaking with the remote assailant and executing assorted noxious exercises. As system movement, action is one of the principle characteristics of malware and botnet task, activity investigation is frequently observed as one of the key methods for recognizing traded off machines inside the system. We present an examination, routed to security experts, of machine learning methods connected to the recognition of interruption, malware, and spam.

Security Awareness in the Internet of Everything

2019 ◽  
pp. 272-301 ◽  
Author(s):  
Viacheslav Izosimov ◽  
Martin Törngren
Keyword(s):  
Cyber Security ◽  
Physical System ◽  
System Of Systems ◽  
The Internet ◽  
Security Awareness ◽  
Security Risks ◽  
Interconnected System ◽  
Security Education ◽  
Practical Evaluation ◽  
Explicit Consideration

Our societal infrastructure is transforming into a connected cyber-physical system of systems, providing numerous opportunities and new capabilities, yet also posing new and reinforced risks that require explicit consideration. This chapter addresses risks specifically related to cyber-security. One contributing factor, often neglected, is the level of security education of the users. Another factor, often overlooked, concerns security-awareness of the engineers developing cyber-physical systems. Authors present results of interviews with developers and surveys showing that increase in security-awareness and understanding of security risks, evaluated as low, are the first steps to mitigate the risks. Authors also conducted practical evaluation investigating system connectivity and vulnerabilities in complex multi-step attack scenarios. This chapter advocates that security awareness of users and developers is the foundation to deployment of interconnected system of systems, and provides recommendations for steps forward highlighting the roles of people, organizations and authorities.

ICT in Chinese Higher Education

2021 ◽  
pp. 1614-1627
Author(s):  
Xiaobin Li
Keyword(s):  
Higher Education ◽  
Significant Proportion ◽  
Chinese Higher Education ◽  
The Internet ◽  
Higher Education System ◽  
Network Information ◽  
Internet Users ◽  
The World ◽  
Information And Communication ◽  
Education In China

A recent report from China Internet Network Information Center indicates that by the end of June 2015, 668 million Chinese have used the internet, which places China as the country with the most internet users in the world. As more Chinese get online, the internet has been integrated into providing education in China, where the age group using the internet the most often is between the ages of 20 and 29. Many of these youth are higher education students. With 34.6 million students the Chinese higher education system is the largest in the world, in which a significant proportion of the students' learning has been impacted by information and communication technology (ICT). The purpose of this article is to provide an overview of how the development of ICT in China has influenced higher education, what opportunities ICT offers for higher education, and what challenges Chinese face in further developing higher education with ICT.

Human Factors in Cybersecurity

2021 ◽  
pp. 1695-1725
Author(s):  
Xichen Zhang ◽  
Ali A. Ghorbani
Keyword(s):  
Human Factors ◽  
Cyber Security ◽  
Security And Privacy ◽  
The Internet ◽  
Online Behavior ◽  
Weakest Link ◽  
Internet Users ◽  
Daily Behavior ◽  
Privacy Issues ◽  
The Internet Of Things

Over recent years, the extensive development of information technology has dramatically advanced the way that people use the internet. The fast growth of the internet of things and mobile crowdsensing applications raise challenging security and privacy issues for the society. More often than before, malicious attackers exploit human vulnerability as the weakest link to launch cyberattacks and conduct fraudulent online activities. How to profile users' daily behavior becomes an essential component for identifying users' vulnerable/malicious level and predicting the potential cyber threats. In this chapter, the authors discuss human factors and their related issues in cyber security and privacy. Three categories of human behaviors—desktop behavior, mobile behavior, and online behavior—and their corresponding security and privacy issues are demonstrated in detail to estimate the vulnerabilities of internet users. Some future directions related to human-factor based security and privacy issues are proposed at the end of this chapter.

Impact of Internet Use on Civic Engagement in Chinese Rural Areas

2012 ◽  
pp. 296-313
Author(s):  
Jian-Chuan Zhang ◽  
Ying Qin
Keyword(s):  
Civic Engagement ◽  
Rural Areas ◽  
Internet Use ◽  
Public Affairs ◽  
The Internet ◽  
Network Information ◽  
Internet Users ◽  
Political Impact ◽  
Preliminary Study ◽  
Use Of The Internet

Few prior studies have addressed the political impact of the Internet on civic engagement in rural areas. This preliminary study aims to explore the connection between Internet use and civic engagement of rural Internet users. Based on the surveys implemented by the China Internet Network Information Center (CNNIC), the authors find that using the Internet does enhance the level of civic engagement among rural Internet users in China. However, better use of the Internet faces some obstacles, too. They are the young age of rural users and the limited Net bandwidth. Implications of these obstacles are discussed. The chapter concludes that, under certain circumstances, there is great potential for Chinese rural Internet users to become more actively engaged in public affairs in the future.

scholarly journals A Strengthening Asean Cyber Cooperation in Countering Cyber Terrorist Groups Activities on the Internet by Implementing the Six-Ware Cyber Security Framework

2018 ◽  
Vol 13 ◽  
pp. 3288-3300
Author(s):  
Rudy Agus Gemilang Gultom ◽  
Asep Adang Supriyadi ◽  
Tatan Kustana
Keyword(s):  
Cyber Security ◽  
Negative Impact ◽  
The Internet ◽  
Security Framework ◽  
Security Issue ◽  
Cyber Terrorism ◽  
Asean Member ◽  
Internet Users ◽  
Terrorist Groups ◽  
And Control

Nowadays, the extremism, radicalism and terrorism groups have taken advantages the use of Internet access to support their activities, i.e, member recruitment, propaganda, fundraising, cyberattack actions against their targets, etc. This is one of the issues of cyber security as a negative impact of internet utilization especially by the extremism, radicalism and terrorism groups. They know the benefits of the internet services and social media can be used to facilitate the control of information in their organizational command and control system.  In order to tackle this cyber security issue, the internet users in Association of Southeast Asian Nations (ASEAN) member countries should get more understanding as well as protection from their government against the danger of cyber extremism, cyber radicalism or cyber terrorism activities over the Internet. Therefore, this paper tries to explain the need of an ASEAN Cyber Security Framework standard in order to countering cyber terrorism activities via Internet as well as introducing the initial concept of Six-Ware Cyber Security Framework (SWCSF). 

scholarly journals An Effective Method for Predicting Malware Family

2020 ◽  
Vol 9 (4) ◽  
pp. 1230-1233
Keyword(s):  
Machine Learning ◽  
Malware Detection ◽  
Malicious Code ◽  
The Internet ◽  
Security Threats ◽  
Learning Approaches ◽  
Computer Viruses ◽  
Software Products ◽  
Internet Users ◽  
Rapid Spread

Today, many of devices are connected to internet through networks. Malware (such as computer viruses, trojans, ransomware, and bots) has becoming a critical concern and evolving security threats to the internet users nowadays. To make legitimate users safe from these attacks, many anti-malware software products has been developed. Which provide the major defensive methods against those malwares. Due to rapid spread and easiness of generating malicious code, the number of new malware samples has dramatically increased. There need to take an immediate action against these increase in malware samples which would result in an intelligent method for malware detection. Machine learning approaches are one of the efficient choices to deal with the problem which helps to distinguish malware from benign ones. In this paper we are considering xception model for malware detection. This experiment results shows the efficiency of our proposed method, which gives 98% accuracy with malimg dataset. This paper helps network security area for their efficient works.

scholarly journals An Efficient Classifier for U2R, R2L, DoS Attack

2020 ◽  
Vol 9 (1) ◽  
pp. 644-647
Keyword(s):  
Machine Learning ◽  
Network Security ◽  
Learning Algorithms ◽  
Research Area ◽  
Attack Detection ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Detection Accuracy ◽  
Cyber Attack ◽  
Detection Systems

The internet has become an irreplaceable communicating and informative tool in the current world. With the ever-growing importance and massive use of the internet today, there has been interesting from researchers to find the perfect Cyber Attack Detection Systems (CADSs) or rather referred to as Intrusion Detection Systems (IDSs) to protect against the vulnerabilities of network security. CADS presently exist in various variants but can be largely categorized into two broad classifications; signature-based detection and anomaly detection CADSs, based on their approaches to recognize attack packets.The signature-based CADS use the well-known signatures or fingerprints of the attack packets to signal the entry across the gateways of secured networks. Signature-based CADS can only recognize threats that use the known signature, new attacks with unknown signatures can, therefore, strike without notice. Alternatively, anomaly-based CADS are enabled to detect any abnormal traffic within the network and report. There are so many ways of identifying anomalies and different machine learning algorithms are introduced to counter such threats. Most systems, however, fall short of complete attack prevention in the real world due system administration and configuration, system complexity and abuse of authorized access. Several scholars and researchers have achieved a significant milestone in the development of CADS owing to the importance of computer and network security. This paper reviews the current trends of CADS analyzing the efficiency or level of detection accuracy of the machine learning algorithms for cyber-attack detection with an aim to point out to the best. CADS is a developing research area that continues to attract several researchers due to its critical objective.

scholarly journals Cyber-Attack Scoring Model Based on the Offensive Cybersecurity Framework

2021 ◽  
Vol 11 (16) ◽  
pp. 7738
Author(s):  
Kyounggon Kim ◽  
Faisal Abdulaziz Alfouzan ◽  
Huykang Kim
Keyword(s):  
Cyber Security ◽  
Personal Information ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Infrastructures ◽  
Cyber Attack ◽  
Security Framework ◽  
Scoring Model ◽  
Advanced Persistent Threats ◽  
The World

Cyber-attacks have become commonplace in the world of the Internet. The nature of cyber-attacks is gradually changing. Early cyber-attacks were usually conducted by curious personal hackers who used simple techniques to hack homepages and steal personal information. Lately, cyber attackers have started using sophisticated cyber-attack techniques that enable them to retrieve national confidential information beyond the theft of personal information or defacing websites. These sophisticated and advanced cyber-attacks can disrupt the critical infrastructures of a nation. Much research regarding cyber-attacks has been conducted; however, there has been a lack of research related to measuring cyber-attacks from the perspective of offensive cybersecurity. This motivated us to propose a methodology for quantifying cyber-attacks such that they are measurable rather than abstract. For this purpose, we identified each element of offensive cybersecurity used in cyber-attacks. We also investigated the extent to which the detailed techniques identified in the offensive cyber-security framework were used, by analyzing cyber-attacks. Based on these investigations, the complexity and intensity of cyber-attacks can be measured and quantified. We evaluated advanced persistent threats (APT) and fileless cyber-attacks that occurred between 2010 and 2020 based on the methodology we developed. Based on our research methodology, we expect that researchers will be able to measure future cyber-attacks.

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