Biblio
In NATO, an attack on one is an attack on all. In recent years, this tenet has been extended to mean that a cyberattack on one is a cyberattack on all. But does what makes sense in the physical world also make sense if extended into cyberspace? And if there is virtue in collective cyberspace defense, is NATO necessarily the right grouping - in a world where, as far as the United States and the United Kingdom are concerned, more of what constitutes cyber defense circulates within the Five Eyes coalition rather than within NATO? To explore these issues, this essay moots the creation of a Baltic-area cyberspace alliance, considers what it would do, assesses its costs and benefits for its members, and concludes by considering whether such an alliance would be also be in the interest of the U.S. Keys to this discussion are (1) the distinction between what constitutes an “attack” in a medium where occupation may result and actions in media where occupation is (currently) meaningless and effects almost always reversible, (2) what collective defense should mean in cyberspace - and where responsibilities may be best discharged within the mix of hardness, pre-emption, and deterrence that constitute defense, (3) the relationship between cyberspace defense and information warfare defense, and (4) the relevance to alliance formation of the fact that while war is dull, dirty, and dangerous, cyber war is none of these three.
The present paper describes some of the results obtained in the Faculty of Computer Systems and Technology at Technical University of Sofia in the implementation of project related to the application of intelligent methods for increasing the security in computer networks. Also is made a survey about existing hybrid methods, which are using several artificial intelligent methods for cyber defense. The paper introduces a model for intrusion detection systems where multi agent systems are the bases and artificial intelligence are applicable by the means simple real-time models constructed in laboratory environment.
Cyber defense can no longer be limited to intrusion detection methods. These systems require malicious activity to enter an internal network before an attack can be detected. Having advanced, predictive knowledge of future attacks allow a potential victim to heighten security and possibly prevent any malicious traffic from breaching the network. This paper investigates the use of Auto-Regressive Integrated Moving Average (ARIMA) models and Bayesian Networks (BN) to predict future cyber attack occurrences and intensities against two target entities. In addition to incident count forecasting, categorical and binary occurrence metrics are proposed to better represent volume forecasts to a victim. Different measurement periods are used in time series construction to better model the temporal patterns unique to each attack type and target configuration, seeing over 86% improvement over baseline forecasts. Using ground truth aggregated over different measurement periods as signals, a BN is trained and tested for each attack type and the obtained results provided further evidence to support the findings from ARIMA. This work highlights the complexity of cyber attack occurrences; each subset has unique characteristics and is influenced by a number of potential external factors.
The cyber threat landscape is a constantly morphing surface; the need for cyber defenders to develop and create proactive threat intelligence is on the rise, especially on critical infrastructure environments. It is commonly voiced that Supervisory Control and Data Acquisition (SCADA) systems and Industrial Control Systems (ICS) are vulnerable to the same classes of threats as other networked computer systems. However, cyber defense in operational ICS is difficult, often introducing unacceptable risks of disruption to critical physical processes. This is exacerbated by the notion that hardware used in ICS is often expensive, making full-scale mock-up systems for testing and/or cyber defense impractical. New paradigms in cyber security have focused heavily on using deception to not only protect assets, but also gather insight into adversary motives and tools. Much of the work that we see in today's literature is focused on creating deception environments for traditional IT enterprise networks; however, leveraging our prior work in the domain, we explore the opportunities, challenges and feasibility of doing deception in ICS networks.