Feature-driven anomalous behaviour detection and incident classification model for ICS in water treatment plants
- Gabriela Ahmadi-Assalemi,
- Haider Al-Khateeb,
- Tanaka Laura Makonese,
- Vladlena Benson,
- Samiya Khan,
- Usman Javed Butt
Industry 5.0 envisions humans working alongside emerging technologies and enabled by the fusion of devices and sensors using information and communication technologies (ICT) to facilitate process automation, monitoring and distributed control in ...
An approach towards development of a supervisory control and data acquisition system forensics framework: concerns and challenges
In the highly competitive technology market, supervisory control and data acquisition/industrial control systems (SCADA/ICS) have seen quick growth. They are also at the heart of operational technology (OT), which is used in businesses and processing ...
Blockchain as an indispensable asset for educational institutions: a systematic review
Blockchain is eminently flourishing as an open distributed data structure to record digital transactions efficiently and permanently in cryptographically linked time-ordered sets of blocks. Integration of blockchain into education opens new possibilities ...
IoT security: a systematic literature review of feature selection methods for machine learning-based attack classification
In the age of the internet of things (IoT), ensuring security is crucial to protect the interconnected devices and systems. The capacity to identify cyberattacks is essential for IoT security, hence many academics have focused their efforts on developing ...
A novel scalable and cost efficient blockchain solution for managing lifetime vaccination records based on patient preference
This study aims to design a novel, cost-efficient blockchain-based solution for managing lifetime vaccination records based on patient preference. The proposed design reduces fraud in vaccination certification by providing QR code-based validation. The ...
Network security attack classification: leveraging machine learning methods for enhanced detection and defence
The rapid growth and advancement of information exchange over the internet and mobile technologies have resulted in a significant increase in malicious network attacks. Machine learning (ML) algorithms have emerged as crucial tools in network security ...
VLMDALP: design of an efficient VARMA LSTM-based model for identification of DDoS attacks using application-level packet analysis
A novel approach for detecting application-level distributed denial-of-service (DDoS) attacks in networks is introduced. By merging vector autoregressive moving average (VARMA) and long short-term memory (LSTM) techniques, our hybrid model efficiently ...
Forensic investigation and analysis of malware in Windows OS
Malware has become a pervasive concern for malware analysts and digital forensics. This research investigates malware forensics to detect, investigate, and analyse malicious software. The research examines the application of digital forensic science to ...
Adversarial attacks on machine learning-based cyber security systems: a survey of techniques and defences
Machine learning (ML) has been increasingly adopted in the field of cyber security to enhance the detection and prevention of cyber threats. However, recent studies have demonstrated that ML-based cyber security systems are vulnerable to adversarial ...
Secure system to secure crime data using hybrid: RSA-AES and hybrid: Blowfish-Triple DES
Data security is the project's primary goal. We suggest hybrid cryptography as a technique to keep the data secure. When the sender tries to email the recipient the criminal data, it will be encrypted with a symmetric key utilising symmetric encryption. ...
Exploring advanced steganography techniques for secure digital image communication: a comparative analysis and performance evaluation
- Rohit Deval,
- Nachiket Gupte,
- Johann Kyle Pinto,
- Adwaita Raj Modak,
- Akshat Verma,
- Anirudh Sharma,
- S.P. Raja
This is a digital age. In a world where everything seems to be public, privacy and confidentiality have never been more important. So, the combination of this aspect of our life and this need of our age is the ability to securely hide data in the digital ...
The legal authority of the electronic authentication certificate and its role in proving e-commerce transactions
This article analyses the concept of the electronic authentication certificate and shows its types issued by electronic authentication authorities according to the function they perform and the purpose of their issuance. It will also show the legal ...
IoT security using deep learning algorithm: intrusion detection model using LSTM
Internet of things (IoT) and the integration of many gadgets is rapidly becoming a reality. IoT devices, particularly edge devices, are particularly vulnerable to cyberattacks as a result of the proliferation of device-to-device (D2D) connectivity ...
