Search results for "Advanced persistent threat"
showing 5 items of 5 documents
State of the Art Literature Review on Network Anomaly Detection
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory
2018
Advanced Persistent Threat(APT) attacks are a major concern for the modern societal digital infrastructures due to their highly sophisticated nature. The purpose of these attacks varies from long period espionage in high level environment to causing maximal destruction for targeted cyber environment. Attackers are skilful and well funded by governments in many cases. Due to sophisticated methods it is highly important to study proper countermeasures to detect these attacks as early as possible. Current detection methods under-performs causing situations where an attack can continue months or even years in a targeted environment. We propose a novel method for analysing APT attacks through OO…
A Novel Deep Learning Stack for APT Detection
2019
We present a novel Deep Learning (DL) stack for detecting Advanced Persistent threat (APT) attacks. This model is based on a theoretical approach where an APT is observed as a multi-vector multi-stage attack with a continuous strategic campaign. To capture these attacks, the entire network flow and particularly raw data must be used as an input for the detection process. By combining different types of tailored DL-methods, it is possible to capture certain types of anomalies and behaviour. Our method essentially breaks down a bigger problem into smaller tasks, tries to solve these sequentially and finally returns a conclusive result. This concept paper outlines, for example, the problems an…
State of the Art Literature Review on Network Anomaly Detection with Deep Learning
2018
As network attacks are evolving along with extreme growth in the amount of data that is present in networks, there is a significant need for faster and more effective anomaly detection methods. Even though current systems perform well when identifying known attacks, previously unknown attacks are still difficult to identify under occurrence. To emphasize, attacks that might have more than one ongoing attack vectors in one network at the same time, or also known as APT (Advanced Persistent Threat) attack, may be hardly notable since it masquerades itself as legitimate traffic. Furthermore, with the help of hiding functionality, this type of attack can even hide in a network for years. Additi…
Tietoturvan ihmiselementti : sosiaalinen manipulointi
2017
Tämän tutkielman aiheena on sosiaalinen manipulointi, tietoturvan ihmiselementti ja sen huomioon ottaminen ja hyökkäysten ehkäiseminen yrityksen tai organisaation tietoturvassa. Sosiaalisella manipuloinnilla tarkoitetaan tutkielman kontekstissa tietojärjestelmän käyttäjiin kohdistuvaa manipulointia, jonka tavoitteena on informaation keruu tai tietojärjestelmään murtautuminen. Aihetta on tärkeää tutkia, sillä useat tietoturva-asiantuntijat ovat yhtä mieltä siitä, että merkittävin tietojärjestelmän tietoturvauhka on sen käyttäjät ja heidän tietoturvallisuuden näkökulmasta tekemät inhimilliset erehdykset. Sosiaalinen manipulointi kohdistuu juuri tähän tietoturvan heikkouteen. Tutkielman tuloks…