All Outputs (9)

A torture-free cyber space : a human right (2017)
Journal Article
Newbery, S., & Dehghantanha, A. (2017). A torture-free cyber space : a human right. Computer Fraud and Security, 2017(11), 14-19. https://doi.org/10.1016/S1361-3723%2817%2930083-0

Definitions of torture range from the emotive to the legal. The media sometimes uses the term in a loose or informal sense – for example, to refer to the pain felt when one's sports team loses a crucial game. This dangerous practice detracts from the... Read More about A torture-free cyber space : a human right.

A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence (2017)
Journal Article
Kiwia, D., Dehghantanha, A., Choo, K., & Slaughter, J. (2017). A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence. Journal of Computational Science, 27, 394-409

Malware such as banking Trojans are popular with financially-motivated cybercriminals. Detection of banking Trojans remains a challenging task, due to the constant evolution of techniques used to obfuscate and circumvent existing detection and securi... Read More about A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence.

Intelligent OS X malware threat detection with code inspection (2017)
Journal Article
HaddadPajouh, H., Dehghantanha, A., Khayami, R., & Choo, R. (2017). Intelligent OS X malware threat detection with code inspection. Journal of Computer Virology and Hacking Techniques, 14(3), 213-223. https://doi.org/10.1007/s11416-017-0307-5

With the increasing market share of Mac OS X operating system, there is a corresponding increase in the number of malicious programs (malware) designed to exploit vulnerabilities on Mac OS X platforms. However, existing manual and heuristic OS X malw... Read More about Intelligent OS X malware threat detection with code inspection.

Non-reciprocity compensation combined with turbo codes for secret key generation in vehicular ad hoc social IoT networks (2017)
Journal Article
Epiphaniou, G., Karadimas, P., Dhouha Kbaier Ben, I., Al-Khateeb, H., Dehghantanha, A., & Choo, K. (2018). Non-reciprocity compensation combined with turbo codes for secret key generation in vehicular ad hoc social IoT networks. IEEE Internet of Things, 5(4), 2496-2505. https://doi.org/10.1109/JIOT.2017.2764384

The physical attributes of the dynamic vehicle-to-vehicle (V2V) propagation channel can be utilised for the generation of highly random and symmetric cryptographic keys. However, in a physical-layer key agreement scheme, non-reciprocity due to inhere... Read More about Non-reciprocity compensation combined with turbo codes for secret key generation in vehicular ad hoc social IoT networks.

Know abnormal, find evil : frequent pattern mining for ransomware threat hunting and intelligence (2017)
Journal Article
Homayoun, S., Dehghantanha, A., Ahmadzadeh, M., Hashemi, S., & Khayami, R. (2020). Know abnormal, find evil : frequent pattern mining for ransomware threat hunting and intelligence. IEEE Transactions on Emerging Topics in Computing, 8(2), 341-351. https://doi.org/10.1109/TETC.2017.2756908

Emergence of crypto-ransomware has significantly changed the cyber threat landscape. A crypto ransomware removes data custodian access by encrypting valuable data on victims’ computers and requests a ransom payment to reinstantiate custodian acces... Read More about Know abnormal, find evil : frequent pattern mining for ransomware threat hunting and intelligence.

Detecting crypto-ransomware in IoT networks based on energy consumption footprint (2017)
Journal Article
energy consumption footprint. Journal of Ambient Intelligence and Humanized Computing, 9(4), 1141-1152. https://doi.org/10.1007/s12652-017-0558-5

An Internet of Things (IoT) architecture generally consists of a wide range of Internet-connected devices or things such as Android devices, and devices that have more computational capabilities (e.g., storage capacities) are likely to be targeted by... Read More about Detecting crypto-ransomware in IoT networks based on energy consumption footprint.

CloudMe forensics : a case of big-data investigation (2017)
Journal Article
Teing, Y., Dehghantanha, A., & Raymond Choo, K. (2017). CloudMe forensics : a case of big-data investigation. Concurrency and Computation: Practice and Experience, 30(5), https://doi.org/10.1002/cpe.4277

The significant increase in the volume, variety and velocity of data complicates cloud forensic efforts, as such big data will, at some point, become computationally expensive to be fully extracted and analyzed in a timely manner. Thus, it is importa... Read More about CloudMe forensics : a case of big-data investigation.

Greening cloud-enabled big data storage forensics : Syncany as a case study (2017)
Journal Article
Teing, Y., Dehghantanha, A., Raymond Choo, K., Abdullah, M., & Muda, Z. (2019). Greening cloud-enabled big data storage forensics : Syncany as a case study. IEEE Transactions on Sustainable Computing, 4(2), 204-216. https://doi.org/10.1109/TSUSC.2017.2687103

The pervasive nature of cloud-enabled big data storage solutions introduces new challenges in the identification, collection, analysis, preservation and archiving of digital evidences. Investigation of such complex platforms to locate and recover tra... Read More about Greening cloud-enabled big data storage forensics : Syncany as a case study.

Machine learning aided android malware classification (2017)
Journal Article
Nikola, M., Dehghantanha, A., & Kim-Kwang Raymond, C. (2017). Machine learning aided android malware classification. Computers and Electrical Engineering, 61, 266-274. https://doi.org/10.1016/j.compeleceng.2017.02.013

The widespread adoption of Android devices and their capability to store access significant private and confidential information have resulted in these devices being targeted by malware developers. Existing Android malware analysis techniques can be... Read More about Machine learning aided android malware classification.