NEMESYS: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem

As a consequence of the growing popularity of smart mobile devices, mobile malware is clearly on the rise, with attackers targeting valuable user information and exploiting vulnerabilities of the mobile ecosystems. With the emergence of large-scale mobile botnets, smartphones can also be used to launch attacks on mobile networks. The NEMESYS project will develop novel security technologies for seamless service provisioning in the smart mobile ecosystem, and improve mobile network security through better understanding of the threat landscape. NEMESYS will gather and analyze information about the nature of cyber-attacks targeting mobile users and the mobile network so that appropriate counter-measures can be taken. We will develop a data collection infrastructure that incorporates virtualized mobile honeypots and a honeyclient, to gather, detect and provide early warning of mobile attacks and better understand the modus operandi of cyber-criminals that target mobile devices. By correlating the extracted information with the known patterns of attacks from wireline networks, we will reveal and identify trends in the way that cyber-criminals launch attacks against mobile devices.Comment: Accepted for publication in Proceedings of the 28th International Symposium on Computer and Information Sciences (ISCIS'13); 9 pages; 1 figur

Three Decades of Deception Techniques in Active Cyber Defense -- Retrospect and Outlook

Deception techniques have been widely seen as a game changer in cyber defense. In this paper, we review representative techniques in honeypots, honeytokens, and moving target defense, spanning from the late 1980s to the year 2021. Techniques from these three domains complement with each other and may be leveraged to build a holistic deception based defense. However, to the best of our knowledge, there has not been a work that provides a systematic retrospect of these three domains all together and investigates their integrated usage for orchestrated deceptions. Our paper aims to fill this gap. By utilizing a tailored cyber kill chain model which can reflect the current threat landscape and a four-layer deception stack, a two-dimensional taxonomy is developed, based on which the deception techniques are classified. The taxonomy literally answers which phases of a cyber attack campaign the techniques can disrupt and which layers of the deception stack they belong to. Cyber defenders may use the taxonomy as a reference to design an organized and comprehensive deception plan, or to prioritize deception efforts for a budget conscious solution. We also discuss two important points for achieving active and resilient cyber defense, namely deception in depth and deception lifecycle, where several notable proposals are illustrated. Finally, some outlooks on future research directions are presented, including dynamic integration of different deception techniques, quantified deception effects and deception operation cost, hardware-supported deception techniques, as well as techniques developed based on better understanding of the human element.Comment: 19 page

Stochastic Tools for Network Intrusion Detection

With the rapid development of Internet and the sharp increase of network crime, network security has become very important and received a lot of attention. We model security issues as stochastic systems. This allows us to find weaknesses in existing security systems and propose new solutions. Exploring the vulnerabilities of existing security tools can prevent cyber-attacks from taking advantages of the system weaknesses. We propose a hybrid network security scheme including intrusion detection systems (IDSs) and honeypots scattered throughout the network. This combines the advantages of two security technologies. A honeypot is an activity-based network security system, which could be the logical supplement of the passive detection policies used by IDSs. This integration forces us to balance security performance versus cost by scheduling device activities for the proposed system. By formulating the scheduling problem as a decentralized partially observable Markov decision process (DEC-POMDP), decisions are made in a distributed manner at each device without requiring centralized control. The partially observable Markov decision process (POMDP) is a useful choice for controlling stochastic systems. As a combination of two Markov models, POMDPs combine the strength of hidden Markov Model (HMM) (capturing dynamics that depend on unobserved states) and that of Markov decision process (MDP) (taking the decision aspect into account). Decision making under uncertainty is used in many parts of business and science.We use here for security tools.We adopt a high-quality approximation solution for finite-space POMDPs with the average cost criterion, and their extension to DEC-POMDPs. We show how this tool could be used to design a network security framework.Comment: Accepted by International Symposium on Sensor Networks, Systems and Security (2017

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Impact of the Shodan Computer Search Engine on Internet-facing Industrial Control System Devices

The Shodan computer search engine crawls the Internet attempting to identify any connected device. Using Shodan, researchers identified thousands of Internet-facing devices associated with industrial controls systems (ICS). This research examines the impact of Shodan on ICS security, evaluating Shodan\u27s ability to identify Internet-connected ICS devices and assess if targeted attacks occur as a result of Shodan identification. In addition, this research evaluates the ability to limit device exposure to Shodan through service banner manipulation. Shodan\u27s impact was evaluated by deploying four high-interaction, unsolicited honeypots over a 55 day period, each configured to represent Allen-Bradley programmable logic controllers (PLC). All four honeypots were successfully indexed and identifiable via the Shodan web interface in less than 19 days. Despite being indexed, there was no increased network activity or targeted ICS attacks. Although results indicate Shodan is an effective reconnaissance tool, results contrast claims of its use to broadly identify and target Internet-facing ICS devices. Additionally, the service banner for two PLCs were modified to evaluate the impact on Shodan indexing capabilities. Findings demonstrated service banner manipulation successfully limited device exposure from Shodan queries

Using Global Honeypot Networks to Detect Targeted ICS Attacks

Defending industrial control systems (ICS) in the cyber domain is both helped and hindered by bespoke systems integrating heterogeneous devices for unique purposes. Because of this fragmentation, observed attacks against ICS have been targeted and skilled, making them difficult to identify prior to initiation. Furthermore, organisations may be hesitant to share business-sensitive details of an intrusion that would otherwise assist the security community. In this work, we present the largest study of high-interaction ICS honeypots to date and demonstrate that a network of internet-connected honeypots can be used to identify and profile targeted ICS attacks. Our study relies on a network of 120 high-interaction honeypots in 22 countries that mimic programmable logic controllers and remote terminal units. We provide a detailed analysis of 80,000 interactions over 13 months, of which only nine made malicious use of an industrial protocol. Malicious interactions included denial of service and replay attacks that manipulated logic, leveraged protocol implementation gaps and exploited buffer overflows. While the yield was small, the impact was high, as these were skilled, targeted exploits previously unknown to the ICS community. By comparison with other ICS honeypot studies, we demonstrate that high-quality deception over long periods is necessary for such a honeypot network to be effective. As part of this argument, we discuss the accidental and intentional reasons why an internet-connected honeypot might be targeted. We also provide recommendations for effective, strategic use of such networks.Gates Cambridge Trus