Biblio

This paper presents a new approach for a dynamic curtailment method for renewable energy sources that guarantees fulfilling of (n-1)-security criteria of the system. Therefore, it is applicable to high voltage distribution grids and has compliance to their planning guidelines. The proposed dynamic curtailment method specifically reduces the power feed-in of renewable energy sources up to a level, where no thermal constraint is exceeded in the (n-1)-state of the system. Based on AC distribution factors, a new formulation of line outage distribution factors is presented that is applicable for outages consisting of a single line or multiple segment lines. The proposed method is tested using a planning study of a real German high voltage distribution grid. The results show that any thermal loading limits are exceeded by using the dynamic curtailment approach. Therefore, a significant reduction of the grid reinforcement can be achieved by using a small amount of curtailed annual energy from renewable energy sources.

Malware analysis relies heavily on the use of virtual machines (VMs) for functionality and safety. There are subtle differences in operation between virtual and physical machines. Contemporary malware checks for these differences and changes its behavior when it detects a VM presence. These anti-VM techniques hinder malware analysis. Existing research approaches to uncover differences between VMs and physical machines use randomized testing, and thus cannot guarantee completeness. In this article, we propose a detect-and-hide approach, which systematically addresses anti-VM techniques in malware. First, we propose cardinal pill testing—a modification of red pill testing that aims to enumerate the differences between a given VM and a physical machine through carefully designed tests. Cardinal pill testing finds five times more pills by running 15 times fewer tests than red pill testing. We examine the causes of pills and find that, while the majority of them stem from the failure of VMs to follow CPU specifications, a small number stem from under-specification of certain instructions by the Intel manual. This leads to divergent implementations in different CPU and VM architectures. Cardinal pill testing successfully enumerates the differences that stem from the first cause. Finally, we propose VM Cloak—a WinDbg plug-in which hides the presence of VMs from malware. VM Cloak monitors each execute malware command, detects potential pills, and at runtime modifies the command’s outcomes to match those that a physical machine would generate. We implemented VM Cloak and verified that it successfully hides VM presence from malware.

Given the growing sophistication of cyber attacks, designing a perfectly secure system is not generally possible. Quantitative security metrics are thus needed to measure and compare the relative security of proposed security designs and policies. Since the investigation of security breaches has shown a strong impact of human errors, ignoring the human user in computing these metrics can lead to misleading results. Despite this, and although security researchers have long observed the impact of human behavior on system security, few improvements have been made in designing systems that are resilient to the uncertainties in how humans interact with a cyber system. In this work, we develop an approach for including models of user behavior, emanating from the fields of social sciences and psychology, in the modeling of systems intended to be secure. We then illustrate how one of these models, namely general deterrence theory, can be used to study the effectiveness of the password security requirements policy and the frequency of security audits in a typical organization. Finally, we discuss the many challenges that arise when adopting such a modeling approach, and then present our recommendations for future work.

Kernel hardening has been an important topic since many applications and security mechanisms often consider the kernel as part of their Trusted Computing Base (TCB). Among various hardening techniques, Kernel Address Space Layout Randomization (KASLR) is the most effective and widely adopted defense mechanism that can practically mitigate various memory corruption vulnerabilities, such as buffer overflow and use-after-free. In principle, KASLR is secure as long as no memory leak vulnerability exists and high entropy is ensured. In this paper, we introduce a highly stable timing attack against KASLR, called DrK, that can precisely de-randomize the memory layout of the kernel without violating any such assumptions. DrK exploits a hardware feature called Intel Transactional Synchronization Extension (TSX) that is readily available in most modern commodity CPUs. One surprising behavior of TSX, which is essentially the root cause of this security loophole, is that it aborts a transaction without notifying the underlying kernel even when the transaction fails due to a critical error, such as a page fault or an access violation, which traditionally requires kernel intervention. DrK turned this property into a precise timing channel that can determine the mapping status (i.e., mapped versus unmapped) and execution status (i.e., executable versus non-executable) of the privileged kernel address space. In addition to its surprising accuracy and precision, DrK is universally applicable to all OSes, even in virtualized environments, and generates no visible footprint, making it difficult to detect in practice. We demonstrated that DrK can break the KASLR of all major OSes (i.e., Windows, Linux, and OS X) with near-perfect accuracy in under a second. Finally, we propose potential countermeasures that can effectively prevent or mitigate the DrK attack. We urge our community to be aware of the potential threat of having Intel TSX, which is present in most recent Intel CPUs – 100% in workstation and 60% in high-end Intel CPUs since Skylake – and is even available on Amazon EC2 (X1).

Traditionally, network and system configurations are static. Attackers have plenty of time to exploit the system's vulnerabilities and thus they are able to choose when to launch attacks wisely to maximize the damage. An unpredictable system configuration can significantly lift the bar for attackers to conduct successful attacks. Recent years, moving target defense (MTD) has been advocated for this purpose. An MTD mechanism aims to introduce dynamics to the system through changing its configuration continuously over time, which we call adaptations. Though promising, the dynamic system reconfiguration introduces overhead to the applications currently running in the system. It is critical to determine the right time to conduct adaptations and to balance the overhead afforded and the security levels guaranteed. This problem is known as the MTD timing problem. Little prior work has been done to investigate the right time in making adaptations. In this paper, we take the first step to both theoretically and experimentally study the timing problem in moving target defenses. For a broad family of attacks including DDoS attacks and cloud covert channel attacks, we model this problem as a renewal reward process and propose an optimal algorithm in deciding the right time to make adaptations with the objective of minimizing the long-term cost rate. In our experiments, both DDoS attacks and cloud covert channel attacks are studied. Simulations based on real network traffic traces are conducted and we demonstrate that our proposed algorithm outperforms known adaptation schemes.

Infrastructure-as-a-Service (IaaS) clouds such as OpenStack consist of two kinds of nodes in their infrastructure: control nodes and compute nodes. While control nodes run all critical services, compute nodes host virtual machines of customers. Given the large number of compute nodes, and the fact that they are hosting VMs of (possibly malicious) customers, it is possible that some of the compute nodes may be compromised. This paper examines the impact of such a compromise. We focus on OpenStack, a popular open-source cloud plat- form that is widely adopted. We show that attackers com- promising a single compute node can extend their controls over the entire cloud infrastructure. They can then gain free access to resources that they have not paid for, or even bring down the whole cloud to affect all customers. This startling result stems from the cloud platform's misplaced trust, which does not match today's threats. To overcome the weakness, we propose a new system, called SOS , for hardening OpenStack. SOS limits trust on compute nodes. SOS consists of a framework that can enforce a wide range of security policies. Specifically, we applied mandatory access control and capabilities to con- fine interactions among different components. Effective confinement policies are generated automatically. Furthermore, SOS requires no modifications to the OpenStack. This has allowed us to deploy SOS on multiple versions of OpenStack. Our experimental results demonstrate that SOS is scalable, incurs negligible overheads and offers strong protection.

This paper describes multiple system security engineering techniques for assessing system security vulnerabilities and discusses the application of these techniques at different system maturity points. The proposed vulnerability assessment approach allows a systems engineer to identify and assess vulnerabilities early in the life cycle and to continually increase the fidelity of the vulnerability identification and assessment as the system matures.

This paper briefly presents a position that hardware-based roots of trust, integrated in silicon with System-on-Chip (SoC) solutions, represent the most current stage in a progression of technologies aimed at realizing the most foundational computer security concepts. A brief look at this historical progression from a personal perspective is followed by an overview of more recent developments, with particular focus on a root of trust for cryptographic key provisioning and SoC feature management aimed at achieving supply chain assurances and serves as a basis for trust that is linked to properties enforced in hardware. The author assumes no prior knowledge of these concepts and developments by the reader.

An integrity checking and recovery (ICAR) system is presented here, which protects file system integrity and automatically restores modified files. The system enables files cryptographic hashes generation and verification, as well as configuration of security constraints. All of the crucial data, including ICAR system binaries, file backups and hashes database are stored in a physically write-protected storage to eliminate the threat of unauthorised modification. A buffering mechanism was designed and implemented in the system to increase operation performance. Additionally, the system supplies user tools for cryptographic hash generation and security database management. The system is implemented as a kernel extension, compliant with the Linux security model. Experimental evaluation of the system was performed and showed an approximate 10% performance degradation in secured file access compared to regular access.
 

This paper presents a middleware solution to secure data and network in the e-healthcare system. The e-Healthcare Systems are a primary concern due to the easiest deployment area accessibility of the sensor devices. Furthermore, they are often interacting closely in cooperation with the physical environment and the surrounding people, where such exposure increases security vulnerabilities in cases of improperly managed security of the information sharing among different healthcare organizations. Hence, healthcare-specific security standards such as authentication, data integrity, system security and internet security are used to ensure security and privacy of patients' information. This paper discusses security threats on e-Healthcare Systems where an attacker can access both data and network using masquerade attack Moreover, an efficient and cost effective approach middleware solution is discussed for the delivery of secure services.

One of the criticisms of traditional security approaches is that they present a static target for attackers. Critics state, with good justification, that by allowing the attacker to reconnoiter a system at leisure to plan an attack, defenders are immediately disadvantaged. To address this, the concept of moving-target defense (MTD) has recently emerged as a new paradigm for protecting computer networks and systems.
 

In this paper, we propose a remote password authentication scheme based on 3-D geometry with biometric value of a user. It is simple and practically useful and also a legal user can freely choose and change his password using smart card that contains some information. The security of the system depends on the points on the diagonal of a cuboid in 3D environment. Using biometric value makes the points more secure because the characteristics of the body parts cannot be copied or stolen.