Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …

Intrusion detection is one of the important security problems in todays cyber world. A
significant number of techniques have been developed which are based on machine …

Cyber-threat protection is today's one of the most challenging research branches of
information technology, while the exponentially increasing number of tiny, connected …

Abstract Machine Learning (ML) techniques are becoming an invaluable support for network
intrusion detection, especially in revealing anomalous flows, which often hide cyber-threats …

Adversarial examples are inputs to a machine learning system intentionally crafted by an
attacker to fool the model into producing an incorrect output. These examples have achieved …

The emergence of Internet connectivity has led to a significant increase in the volume and
complexity of cyber attacks. Abnormal behavior detection systems are valuable tools for …

Network Traffic Monitoring and Analysis (NTMA) represents a key component for network
management, especially to guarantee the correct operation of large-scale networks such as …

In recent years, advancements in the field of the artificial intelligence (AI) gained a huge
momentum due to the worldwide appliance of this technology by the industry. One of the …

Ransomware is a special type of malicious software that encrypts the user's assets and
makes it unavailable to the users until a ransom is paid to the ransomware author. Such …

Network attacks are serious concerns in today's increasingly interconnected society. Recent
studies have applied conventional machine learning to network attack detection by learning …