Cyber Threats Detection and Mitigation Using Machine Learning

Author(s):  
Vaishnavi Ambalavanan ◽  
Shanthi Bala P.

Cyberspace plays a dominant role in the world of electronic communication. It is a virtual space where the interconnecting network has an independent technology infrastructure. The internet is the baseline for the cyberspace which can be openly accessible. Cyber-security is a set of techniques used to protect network integrity and data from vulnerability. The protection mechanism involves the identification of threats and taking precaution by predicting the vulnerabilities in the environment. The main cause of security violation will be threats, that are caused by the intruder who attacks the network or any electronic devices with the intention to cause damage in the communication network. These threats must be taken into consideration for the mitigation process to improve the system efficiency and performance. Machine learning helps to increase the accuracy level in the detection of threats and their mitigation process in an efficient way. This chapter describes the way in which threats can be detected and mitigated in cyberspace with certain strategies using machine learning.

Author(s):  
Charu Virmani ◽  
Tanu Choudhary ◽  
Anuradha Pillai ◽  
Manisha Rani

With the exponential rise in technological awareness in the recent decades, technology has taken over our lives for good, but with the application of computer-aided technological systems in various domains of our day-to-day lives, the potential risks and threats have also come to the fore, aiming at the various security features that include confidentiality, integrity, authentication, authorization, and so on. Computer scientists the world over have tried to come up, time and again, with solutions to these impending problems. With time, attackers have played out complicated attacks on systems that are hard to comprehend and even harder to mitigate. The very fact that a huge amount of data is processed each second in organizations gave birth to the concept of Big Data, thereby making the systems more adept and intelligent in dealing with unprecedented attacks on a real-time basis. This chapter presents a study about applications of machine learning algorithms in cyber security.


Author(s):  
Sailesh Suryanarayan Iyer ◽  
Sridaran Rajagopal

Knowledge revolution is transforming the globe from traditional society to a technology-driven society. Online transactions have compounded, exposing the world to a new demon called cybercrime. Human beings are being replaced by devices and robots, leading to artificial intelligence. Robotics, image processing, machine vision, and machine learning are changing the lifestyle of citizens. Machine learning contains algorithms which are capable of learning from historical occurrences. This chapter discusses the concept of machine learning, cyber security, cybercrime, and applications of machine learning in cyber security domain. Malware detection and network intrusion are a few areas where machine learning and deep learning can be applied. The authors have also elaborated on the research advancements and challenges in machine learning related to cyber security. The last section of this chapter lists the future trends and directions in machine learning and cyber security.


2022 ◽  
Author(s):  
Usman Akanbi

The Covid-19 pandemic is an unforeseen occurrence that took the world by storm. Governments and businesses were unprepared, hence the large-scale impact it continuously has on the planet. It has permanently revolutionised how we live, work and interact with technology. With this new way of living, businesses and governments had to adapt to a new form of survival, and so did cybercriminals; there was a surge in cyber threats due to our newfound dependence on technology. This paper emphasises the common types of cyber threats and the targeted industries. These attacks were more successful because people were uneasy and desperate, which gave the criminals more incentive to attack businesses. To avoid being a cyber target, I have provided recommendations against future threats.


2021 ◽  
pp. 19-27
Author(s):  
Nazar Demchyshak ◽  
Anastasiia Shkyria

Purpose. The aim of the article is substantiation of approaches of domestic and foreign scientists to risk management in the financial sector of Ukraine in the context of cyber threats and the need to ensure national security and post-pandemic economic recovery. Methodology of research. General scientific and special methods of scientific research are used in the article, in particular: induction, deduction, scientific abstraction - to reveal the essence of the concepts of "cyber threat", “cyber security" and "digitalization"; statistical and graphical methods - to assess the current situation in the field of cyber defence in the world and the national cyber security index; methods of analysis and synthesis - in substantiating the conclusions of the research. Finding. Definitions of cyber risk, approaches to its interpretation and classification were considered. The importance of cyber security in the digitalization of the national economy was argued. The Strategy of Ukrainian Financial Sector Development until 2025 is analysed. The world statistics of frequency and losses due to cyber-attacks are studied and the cyber threats that caused the greatest losses in Ukraine are identified. The analysis of Ukraine’s positions in the National Cyber Security Index 2020 is carried out. The directions of cyber threat prevention that can be useful for Ukrainian companies are substantiated. Originality. The author’s definition of the term "cyber risk" is proposed, in which special attention in focused on the effects of cyber threats. The importance of cyber risk management in the conditions of inevitability of digitalization in the financial sector of Ukraine is substantiated. Approaches to the prevention of cyber-attacks, the implementation of which is necessary for the successful digital transformation of Ukraine, are proposed. Practical value. The results of the research will contribute to the formation of an effective risk management system in the financial sector of Ukraine in terms of digitalization of the financial space and post-pandemic recovery of the national economy. Key words: national security, cyber risk, cyber threat, cyber defence, digitalization, post-pandemic recovery, fintech.


2022 ◽  
pp. 146-187
Author(s):  
Mazoon Hashil Alrubaiei ◽  
Maiya Hamood Al-Saadi ◽  
Hothefa Shaker ◽  
Bara Sharef ◽  
Shahnawaz Khan

IoT represents a technologically bright future where heterogeneously connected devices will be connected to the internet and make intelligent collaborations with other objects to extend the borders of the world with physical entities and virtual components. Despite rapid evolution, this environment is still facing new challenges and security issues that need to be addressed. This chapter will give a comprehensive view of IoT technologies. It will discuss the IoT security scope in detail. Furthermore, a deep analysis of the most recent proposed mechanisms is classified. This study will be a guide for future studies, which direct to three primary leading technologies—machine learning (ML), blockchain, and artificial intelligence (AI)—as intelligent solutions and future directions for IoT security issues.


Author(s):  
Tarik Alafif ◽  
Abdul Muneeim Tehame ◽  
Saleh Bajaba ◽  
Ahmed Barnawi ◽  
Saad Zia

With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.


2020 ◽  
Author(s):  
Abhilasha Semwal

Interestingly art is full of reproductions. Some are replicas, like Mona Lisa and others are fake or forgeries, like the ‘Vermeers’ painted by Han van Meegeren that was sold for $60 million (Kreuger and van Meegeren 2010).Now the distinction between real and fake is based on the concept of authenticity. The question is, is this artefact what it claims to be? The answer seems simple, but in reality, things are complicated. Today, the painting of the forger John Myatt are so famous that they are valued at up to $40,000 each, as ‘genuine fake’ (Furlong 1986). So technically, they are not what they say they are, but they are authentically painted by him and not by any other forger. And they are beautiful, “a bit as if one were to utter a beautiful lie, not any ordinary lie.”According to research out of cyber security company, Deeptrace, the numbers of ‘deepfake’ videos on the internet have doubled in just nine months from 7,964 in December 2018 to 14,698. Of these ‘deepfakes’, 96% were pornographic, often with a face of a celebrity morphed onto the body of an adult actor engaged in sexual activity . Accordingly, Facebook has invested $ 10M into research effort to produce a database and benchmark for detecting deepfakes, and is partnering with top research institutions such as MIT, UC Berkeley, and Cornell Tech . It is clear that deepfakes are alarming and firms like Facebook are doing something about it, but the question is what are deepfakes? And why are they alarming?Due to increased concentration of users around social media and democratization of means by which deepfakes are produced, the web is seeing and increasing propagation of hyper-realistic deepfakes without technical understanding of machine learning, and their increased realism and scale is largely due to improvements in the organization of datasets being fed into machine learning algorithms, as well as the introduction of Generative Adversarial Network (GANs).When truths are indistinguishable from falsehoods, we put at risk our democracy, our ‘national security, and public safety. When the world of the ‘perfect’ deepfake, the waters of fact and fiction are muddled, creating a fog of questioning what’s real and what’s fake?How might deepfakes make us question our national security in times of war? Deepfakes sent from adversaries can show our soldiers killing civilian to invoke an environment of distrust and instability.


2019 ◽  
Author(s):  
A Oruc ◽  
Fred Flinstone

Cyber security in the maritime industry became crucial due to both academic researches and incidents. There are academic studies that show vulnerabilities in various navigation equipments such as GPS, ECDIS, AIS and ARPA-Radar. Additionally, there are different cyber incidents around the world. Developments in technology, autonomous ship projects, academic studies and cyber incidents in the sector put in action IMO. As per ISM Code, all shipping companies are mandatory to add “Guidelines on Maritime Cyber Risk Management” manual to their SMS manuals until 1st January 2021. Both OCIMF and CDI failed to be indifferent to developments that are important for tanker operators as well as IMO. While OCIMF added cybersecurity-related questions to vetting programs called TMSA 3 and VIQ 7, CDI also added cybersecurity-related items in SIR 9.8.1 edition. On the other hand, RightShip provides significant vetting service for dry cargo ships. “Inspection and Assessment Report” is issued by RigthShip for dry cargo ships. Questions related with cybersecurity was added with Revision No: 11 dated on 11th May 2017 in “Inspection and Assessment Report”. In this study, cyber security related questions which are asked during TMSA, SIRE and CDI vettings which play a critical role for commercial life of tanker firms, were analyzed. Moreover, questions and efficiency of RightShip that offers vetting service for dry cargo ships, were assessed to maritime cyber security. Also, cybersecurity-related questions in vetting questionnaires were interpreted by the author. These comments rely on benchmarking meetings among tanker operators where the author personally attended, and interview with key persons. Noted observations during vettings may negatively impact both commercial life and reputation of the tanker operators. That’s why the firm names and interviewee names were kept confidential. In this study, it was seen that although IMO demanded verification of cyber security-related implementations for the ship operators until 1st January 2021, this process started earlier for tanker operators.


2019 ◽  
pp. 1189-1199
Author(s):  
David Gould

This article includes a perspective on cyber security through the lens of the World Economic Forum Resilience Framework. As cyber threats are a continual threat to organizations, it may be useful to consider resilience as a complementary approach to technological responses. The problem is that organizations cannot generate a sufficient number and types of responses to cyber security threats as the number of threats and associated costs continues to increase. The purpose of this article is to explore some possible practices and approaches to counter the ongoing and escalating cyber security threats, with the understanding and wisdom that not all threats will be possible to stop. Resilience is a complementary factor to directly countering threats by taking actions to backup information, having access to additional equipment as needed, by budgeting for failure, preparing for unexpected circumstances among other activities. Concepts from evolution and game theory are introduced within the resilience discussion.


In the field of information technology cyber security plays a vital role. Securing information is the biggest challenge now a days. As the word cyber security comes in our mind the fear of cybercrime comes in us at the same time. Cyber threats are nothing but an activity by which any targeted system can be compromised by altering the availability, integrity, and confidentiality of the system. To overcome such type of threats there are number of mechanisms available. Recently the Machine Learning (ML) approaches have proved to be a milestone for the classification of NetFlows. The NetFlow is a network protocol designed by CISCO which is used to collect the network traffic (NetFlows). In this paper J48 and Random Forest (RF) machine learning algorithms are used for classification of cyber threats using NetFlows. The results are obtained by applying classification algorithms on NetFlows using Weka ML tool and RStudio. A comparison is made in various perspectives like accuracy, true positive (TP), false positive (FP), etc


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