Biblio
Reconnaissance might be the longest phase, sometimes take weeks or months. The black hat makes use of passive information gathering techniques. Once the attacker has sufficient statistics, then the attacker starts the technique of scanning perimeter and internal network devices seeking out open ports and related services. In this paper we are showing traffic accountability and time to complete the specific task during reconnaissance phase active scanning with nmap tool and proposed strategies that how to deal with large volumes of hosts and conserve network traffic as well as time of the specific task.
A main goal of the paper is to discuss the world telecommunications strategy in transition to the IP world. The paper discuss the shifting from circuit switching to packet switching in telecommunications and show the main obstacle is excessive software. As a case, we are passing through the three generations of American military communications: (1) implementation of signaling protocol SS7 and Advanced Intelligent Network, (2) transformation from SS7 to IP protocol and, finally, (3) the extremely ambitious cybersecurity issues. We use the newer unclassified open Defense Information Systems Agency documents, particularly: Department of Defense Information Enterprise Architecture; Unified Capabilities the Army. We discuss the newer US Government Accountability Office (2018) report on military equipment cyber vulnerabilities.
In this paper we investigate deceptive defense strategies for web servers. Web servers are widely exploited resources in the modern cyber threat landscape. Often these servers are exposed in the Internet and accessible for a broad range of valid as well as malicious users. Common security strategies like firewalls are not sufficient to protect web servers. Deception based Information Security enables a large set of counter measures to decrease the efficiency of intrusions. In this work we depict several techniques out of the reconnaissance process of an attacker. We match these with deceptive counter measures. All proposed measures are implemented in an experimental web server with deceptive counter measure abilities. We also conducted an experiment with honeytokens and evaluated delay strategies against automated scanner tools.
We consider a cloud based multiserver system consisting of a set of replica application servers behind a set of proxy (indirection) servers which interact directly with clients over the Internet. We study a proactive moving-target defense to thwart a DDoS attacker's reconnaissance phase and consequently reduce the attack's impact. The defense is effectively a moving-target (motag) technique in which the proxies dynamically change. The system is evaluated using an AWS prototype of HTTP redirection and by numerical evaluations of an “adversarial” coupon-collector mathematical model, the latter allowing larger-scale extrapolations.
Cyber reconnaissance is the process of gathering information about a target network for the purpose of compromising systems within that network. Network-based deception has emerged as a promising approach to disrupt attackers' reconnaissance efforts. However, limited work has been done so far on measuring the effectiveness of network-based deception. Furthermore, given that Software-Defined Networking (SDN) facilitates cyber deception by allowing network traffic to be modified and injected on-the-fly, understanding the effectiveness of employing different cyber deception strategies is critical. In this paper, we present a model to study the reconnaissance surface of a network and model the process of gathering information by attackers as interactions with a cyber defensive system that may use deception. To capture the evolution of the attackers' knowledge during reconnaissance, we design a belief system that is updated by using a Bayesian inference method. For the proposed model, we present two metrics based on KL-divergence to quantify the effectiveness of network deception. We tested the model and the two metrics by conducting experiments with a simulated attacker in an SDN-based deception system. The results of the experiments match our expectations, providing support for the model and proposed metrics.