Phishing is an act of creating a website similar to a legitimate website with a motive of
stealing user's confidential information. Phishing fraud might be the most popular …

Most anomaly detection systems rely on machine learning algorithms to derive a model of
normality that is later used to detect suspicious events. Some works conducted over the last …

In this paper, we introduce a novel methodology to automatically generate HTTP intrusion
signatures for Network Intrusion Detection Systems (NIDS). Our approach relies on the use …

A novel approach to defacement detection is proposed in this paper, addressing explicitly
the possible presence of a passive adversary. Defacement detection is an important security …

Most network attacks occur at the application layer, where many application layer protocols
exist. These protocols have different structures and functionalities, posing feature extraction …

When compared to signature-based Intrusion Detection Systems (IDS), anomaly detectors
present the potential advantage of detecting previously unseen attacks, which makes them …

We propose a general framework for keyed learning, where a secret key is used as an
additional input of an adversarial learning system. We also define models and formal …

The security of information has become even more important with the increased use of the
internet, mobile communication and even social networking, all of which have intensified the …

Defacement Response via Keyed Learning Page 1 Defacement Response via Keyed
Learning Francesco Bergadano, Fabio Carretto Department of Computer Science University of …

With the anomaly detection systems, many approaches and techniques have been
developed to track novel attacks on the systems. Anomaly detection systems based on …