The rise of ransomware and emerging security challenges in the Internet of Things

Yaqoob, Ibrar; Ahmed, Ejaz; Rehman, Muhammad Habib ur; Ahmed, Abdelmuttlib Ibrahim Abdalla; Al-Garadi, Mohammed Ali; Imran, Muhammad; Guizani, Mohsen

doi:10.1016/j.comnet.2017.09.003

Cited by 231 publications

(123 citation statements)

References 48 publications

Supporting

Mentioning

119

Contrasting

Unclassified

Order By: Relevance

“…This software will run a code injection attack. The injected malicious software has a dynamic nature, and new types of attacks are constantly introduced to violate IoT components remarkably because IoT systems have a naturally large, well-connected surface [24,74]. Meanwhile, data tampering is the act of intentionally changing (deleting, changing, manipulating or editing) information via unauthorised operations.…”

Section: ) Cyber Threatsmentioning

confidence: 99%

“…Consequently, detecting these malware attacks by traditional methods is difficult [262,263]. The number of emerging IoT security threats [24]., such as zero-day attacks, is continuously growing at an alarming rate [24]. For example, the Mirai botnet and its derivations are becoming an alarming threat to the security of IoT systems [7,9].…”

Section: B Learning Strategies For Effective Iot Security 1) Zero-damentioning

confidence: 99%

See 1 more Smart Citation

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Al-Garadi

Mohamed

Al-Ali

et al. 2020

IEEE Commun. Surv. Tutorials

Self Cite

835

333

View full text Add to dashboard Cite

The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. It is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. On the one hand, IoT technologies play a crucial role in enhancing several real-life smart applications that can improve life quality. On the other hand, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network security and application security, for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to secure the IoT ecosystem effectively. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory curiosity to practical machinery in several important applications. The ability to monitor IoT devices intelligently provides a significant solution to new or zero-day attacks. ML/DL are powerful methods of data exploration for learning about 'normal' and 'abnormal' behaviour according to how IoT components and devices perform within the IoT environment. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems.IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions.

show abstract

Section: ) Cyber Threatsmentioning

confidence: 99%

Section: B Learning Strategies For Effective Iot Security 1) Zero-damentioning

confidence: 99%

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Al-Garadi

Mohamed

Al-Ali

et al. 2020

IEEE Commun. Surv. Tutorials

Self Cite

835

333

View full text Add to dashboard Cite

show abstract

“…Even though previous operating system targets were essentially Windows computers, nowadays a wider range of infected equipment and OS is noticed: MacOS, IoT devices and Cellphones (Android OS) [35,41]. Previous work has been carried out knowing the signature of the ransomware on the file system that is the encryption of all victims' files.…”

Section: Introductionmentioning

confidence: 99%

Ransomware Network Traffic Analysis for Pre-encryption Alert

Moussaileb

Cuppens

Lanet³

et al. 2020

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Cyber Security researchers are in an ongoing battle against ransomware attacks. Some exploits begin with social engineering methods to install payloads on victims' computers, followed by a communication with command and control servers for data exchange. To scale down these attacks, scientists should shed light on the danger of those rising intrusions to prevent permanent data loss. To join this arm race against malware, we propose in this paper an analysis of various ransomware families based on the collected system and network logs from a computer. We delve into malicious network traffic generated by these samples to perform a packet level detection. Our goal is to reconstruct ransomware's full activity to check if its network communication is distinguishable from benign traffic. Then, we examine if the first packet sent occurs before data's encryption to alert the administrators or afterwards. We aim to define the first occurrence of the alert raised by malicious network traffic and where it takes place in a ransomware workflow. Logs collected are available at http://serveur2.seres.rennes.telecom-bretagne.eu/data/RansomwareData/.

show abstract

“…This can be done without the intervention of the humans. The number of IoT devices is estimated to cross 225 billion within 2020 and a major share of this will be wearable devices [1]. Real world applications of IoT has been increasing and smart homes that use these devices are growing.…”

Section: Introductionmentioning

confidence: 99%

“…It is also not necessary that they will be implemented in smart homes only, even ordinary homes might have some independent smart devices [2]. The devices are also implemented in smart connected cars [3,4], smart monitoring systems [5,6], intelligent parking systems [7], and intelligent meters [8,9]. The number of cyber-attacks in the connected world are growing at an alarming rate.…”

Section: Introductionmentioning

confidence: 99%

Mélange of IoT and Ransomware

2019

IJITEE

View full text Add to dashboard Cite

The use of IoT devices are increasing rapidly. Since it integrates lots of devices, it provides lots of benefits to the users. Large companies also have started using it for coordination between the people and machines. However, Security is a major issue faced by IoT network. Trust is something that is necessary between the devices, which means that the data is transmitted without any tests to the trusted devices. IoT devices have very less security features since upgrades and patches are virtually non-existent. This makes it vulnerable to various attacks like Ransomware. Hackers will simply be able to take control of an IoT device and demand ransom for letting it go. This may get problematic especially in household devices. It is necessary to identify a solution for this this since IoT is still in the budding stage. Hence this work will analyse various available attacks in IoT and provide solutions to combat the ransomware.

show abstract

The rise of ransomware and emerging security challenges in the Internet of Things

Cited by 231 publications

References 48 publications

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

Ransomware Network Traffic Analysis for Pre-encryption Alert

Mélange of IoT and Ransomware

Contact Info

Product

Resources

About