Time Protection: the Missing OS Abstraction

Timing channels enable data leakage that threatens the security of computer systems, from cloud platforms to smartphones and browsers executing untrusted third-party code. Preventing unauthorised information flow is a core duty of the operating system, however, present OSes are unable to prevent timing channels. We argue that OSes must provide time protection in addition to the established memory protection. We examine the requirements of time protection, present a design and its implementation in the seL4 microkernel, and evaluate its efficacy as well as performance overhead on Arm and x86 processors

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics

The accurate and efficient solution of Maxwell's equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation applications. Therefore, many efforts are focussed on the development of new and more efficient approach to solve Maxwell's equation. The interest in CEM applications is growing on. Several problems, hard to figure out few years ago, can now be easily addressed thanks to the reliability and flexibility of new technologies, together with the increased computational power. This technology evolution opens the possibility to address large and complex tasks. Many of these applications aim to simulate the electromagnetic behavior, for example in terms of input impedance and radiation pattern in antenna problems, or Radar Cross Section for scattering applications. Instead, problems, which solution requires high accuracy, need to implement full wave analysis techniques, e.g., virtual prototyping context, where the objective is to obtain reliable simulations in order to minimize measurement number, and as consequence their cost. Besides, other tasks require the analysis of complete structures (that include an high number of details) by directly simulating a CAD Model. This approach allows to relieve researcher of the burden of removing useless details, while maintaining the original complexity and taking into account all details. Unfortunately, this reduction implies: (a) high computational effort, due to the increased number of degrees of freedom, and (b) worsening of spectral properties of the linear system during complex analysis. The above considerations underline the needs to identify appropriate information technologies that ease solution achievement and fasten required elaborations. The authors analysis and expertise infer that Grid Computing techniques can be very useful to these purposes. Grids appear mainly in high performance computing environments. In this context, hundreds of off-the-shelf nodes are linked together and work in parallel to solve problems, that, previously, could be addressed sequentially or by using supercomputers. Grid Computing is a technique developed to elaborate enormous amounts of data and enables large-scale resource sharing to solve problem by exploiting distributed scenarios. The main advantage of Grid is due to parallel computing, indeed if a problem can be split in smaller tasks, that can be executed independently, its solution calculation fasten up considerably. To exploit this advantage, it is necessary to identify a technique able to split original electromagnetic task into a set of smaller subproblems. The Domain Decomposition (DD) technique, based on the block generation algorithm introduced in Matekovits et al. (2007) and Francavilla et al. (2011), perfectly addresses our requirements (see Section 3.4 for details). In this chapter, a Grid Computing infrastructure is presented. This architecture allows parallel block execution by distributing tasks to nodes that belong to the Grid. The set of nodes is composed by physical machines and virtualized ones. This feature enables great flexibility and increase available computational power. Furthermore, the presence of virtual nodes allows a full and efficient Grid usage, indeed the presented architecture can be used by different users that run different applications

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

A Survey of Techniques for Improving Security of GPUs

Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest `link' in the security `chain'. In this paper, we present a survey of techniques for analyzing and improving GPU security. We classify the works on key attributes to highlight their similarities and differences. More than informing users and researchers about GPU security techniques, this survey aims to increase their awareness about GPU security vulnerabilities and potential countermeasures

CacheZoom: How SGX Amplifies The Power of Cache Attacks

In modern computing environments, hardware resources are commonly shared, and parallel computation is widely used. Parallel tasks can cause privacy and security problems if proper isolation is not enforced. Intel proposed SGX to create a trusted execution environment within the processor. SGX relies on the hardware, and claims runtime protection even if the OS and other software components are malicious. However, SGX disregards side-channel attacks. We introduce a powerful cache side-channel attack that provides system adversaries a high resolution channel. Our attack tool named CacheZoom is able to virtually track all memory accesses of SGX enclaves with high spatial and temporal precision. As proof of concept, we demonstrate AES key recovery attacks on commonly used implementations including those that were believed to be resistant in previous scenarios. Our results show that SGX cannot protect critical data sensitive computations, and efficient AES key recovery is possible in a practical environment. In contrast to previous works which require hundreds of measurements, this is the first cache side-channel attack on a real system that can recover AES keys with a minimal number of measurements. We can successfully recover AES keys from T-Table based implementations with as few as ten measurements.Comment: Accepted at Conference on Cryptographic Hardware and Embedded Systems (CHES '17

A Reconfigurable Platform For Cognitive Radio

Today¿s rigid spectrum allocation scheme creates a spectrum scarcity problem for future wireless communications. Measurements show that a wide range of the allocated frequency bands are rarely used. Cognitive radio is a novel approach to improve the spectrum usage, which is able to sense the spectrum and adapt its transmission while coexisting with the licensed spectrum user. A reconfigurable radio platform is required to provide enough adaptivity for cognitive radio. In this paper, we propose a cognitive radio system architecture and discuss its possible implementation on a heterogeneous reconfigurable radio platform

Towards a cyber physical system for personalised and automatic OSA treatment

Obstructive sleep apnea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very important task in medicine in many scenarios, as for example for making instantaneous pressure adjustments that should take place when Automatic Positive Airway Pressure (APAP) devices are used during the treatment of OSA. In this paper the design of a possible Cyber Physical System (CPS) suited to real-time monitoring of OSA is described, and its software architecture and possible hardware sensing components are detailed. It should be emphasized here that this paper does not deal with a full CPS, rather with a software part of it under a set of assumptions on the environment. The paper also reports some preliminary experiments about the cognitive and learning capabilities of the designed CPS involving its use on a publicly available sleep apnea database

Service Level Agreement-based GDPR Compliance and Security assurance in (multi)Cloud-based systems

Compliance with the new European General Data Protection Regulation (Regulation (EU) 2016/679) and security assurance are currently two major challenges of Cloud-based systems. GDPR compliance implies both privacy and security mechanisms definition, enforcement and control, including evidence collection. This paper presents a novel DevOps framework aimed at supporting Cloud consumers in designing, deploying and operating (multi)Cloud systems that include the necessary privacy and security controls for ensuring transparency to end-users, third parties in service provision (if any) and law enforcement authorities. The framework relies on the risk-driven specification at design time of privacy and security level objectives in the system Service Level Agreement (SLA) and in their continuous monitoring and enforcement at runtime.The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644429 and No 780351, MUSA project and ENACT project, respectively. We would also like to acknowledge all the members of the MUSA Consortium and ENACT Consortium for their valuable help