9,019 research outputs found
Securing Real-Time Internet-of-Things
Modern embedded and cyber-physical systems are ubiquitous. A large number of
critical cyber-physical systems have real-time requirements (e.g., avionics,
automobiles, power grids, manufacturing systems, industrial control systems,
etc.). Recent developments and new functionality requires real-time embedded
devices to be connected to the Internet. This gives rise to the real-time
Internet-of-things (RT-IoT) that promises a better user experience through
stronger connectivity and efficient use of next-generation embedded devices.
However RT- IoT are also increasingly becoming targets for cyber-attacks which
is exacerbated by this increased connectivity. This paper gives an introduction
to RT-IoT systems, an outlook of current approaches and possible research
challenges towards secure RT- IoT frameworks
Side-channel based intrusion detection for industrial control systems
Industrial Control Systems are under increased scrutiny. Their security is
historically sub-par, and although measures are being taken by the
manufacturers to remedy this, the large installed base of legacy systems cannot
easily be updated with state-of-the-art security measures. We propose a system
that uses electromagnetic side-channel measurements to detect behavioural
changes of the software running on industrial control systems. To demonstrate
the feasibility of this method, we show it is possible to profile and
distinguish between even small changes in programs on Siemens S7-317 PLCs,
using methods from cryptographic side-channel analysis.Comment: 12 pages, 7 figures. For associated code, see
https://polvanaubel.com/research/em-ics/code
A Novel Side-Channel in Real-Time Schedulers
We demonstrate the presence of a novel scheduler side-channel in preemptive,
fixed-priority real-time systems (RTS); examples of such systems can be found
in automotive systems, avionic systems, power plants and industrial control
systems among others. This side-channel can leak important timing information
such as the future arrival times of real-time tasks.This information can then
be used to launch devastating attacks, two of which are demonstrated here (on
real hardware platforms). Note that it is not easy to capture this timing
information due to runtime variations in the schedules, the presence of
multiple other tasks in the system and the typical constraints (e.g.,
deadlines) in the design of RTS. Our ScheduLeak algorithms demonstrate how to
effectively exploit this side-channel. A complete implementation is presented
on real operating systems (in Real-time Linux and FreeRTOS). Timing information
leaked by ScheduLeak can significantly aid other, more advanced, attacks in
better accomplishing their goals
Discovering New Vulnerabilities in Computer Systems
Vulnerability research plays a key role in preventing and defending against malicious computer system exploitations. Driven by a multi-billion dollar underground economy, cyber criminals today tirelessly launch malicious exploitations, threatening every aspect of daily computing. to effectively protect computer systems from devastation, it is imperative to discover and mitigate vulnerabilities before they fall into the offensive parties\u27 hands. This dissertation is dedicated to the research and discovery of new design and deployment vulnerabilities in three very different types of computer systems.;The first vulnerability is found in the automatic malicious binary (malware) detection system. Binary analysis, a central piece of technology for malware detection, are divided into two classes, static analysis and dynamic analysis. State-of-the-art detection systems employ both classes of analyses to complement each other\u27s strengths and weaknesses for improved detection results. However, we found that the commonly seen design patterns may suffer from evasion attacks. We demonstrate attacks on the vulnerabilities by designing and implementing a novel binary obfuscation technique.;The second vulnerability is located in the design of server system power management. Technological advancements have improved server system power efficiency and facilitated energy proportional computing. However, the change of power profile makes the power consumption subjected to unaudited influences of remote parties, leaving the server systems vulnerable to energy-targeted malicious exploit. We demonstrate an energy abusing attack on a standalone open Web server, measure the extent of the damage, and present a preliminary defense strategy.;The third vulnerability is discovered in the application of server virtualization technologies. Server virtualization greatly benefits today\u27s data centers and brings pervasive cloud computing a step closer to the general public. However, the practice of physical co-hosting virtual machines with different security privileges risks introducing covert channels that seriously threaten the information security in the cloud. We study the construction of high-bandwidth covert channels via the memory sub-system, and show a practical exploit of cross-virtual-machine covert channels on virtualized x86 platforms
Machine Learning based Anomaly Detection for Cybersecurity Monitoring of Critical Infrastructures
openManaging critical infrastructures requires to increasingly rely on Information and Communi-
cation Technologies. The last past years showed an incredible increase in the sophistication
of attacks. For this reason, it is necessary to develop new algorithms for monitoring these
infrastructures. In this scenario, Machine Learning can represent a very useful ally. After a
brief introduction on the issue of cybersecurity in Industrial Control Systems and an overview
of the state of the art regarding Machine Learning based cybersecurity monitoring, the
present work proposes three approaches that target different layers of the control network
architecture. The first one focuses on covert channels based on the DNS protocol, which can
be used to establish a command and control channel, allowing attackers to send malicious
commands. The second one focuses on the field layer of electrical power systems, proposing
a physics-based anomaly detection algorithm for Distributed Energy Resources. The third
one proposed a first attempt to integrate physical and cyber security systems, in order to face
complex threats. All these three approaches are supported by promising results, which gives
hope to practical applications in the next future.openXXXIV CICLO - SCIENZE E TECNOLOGIE PER L'INGEGNERIA ELETTRONICA E DELLE TELECOMUNICAZIONI - Elettromagnetismo, elettronica, telecomunicazioniGaggero, GIOVANNI BATTIST
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