Biblio

We propose a lightweight RFID authentication protocol that supports forward and backward security. The only cryptographic mechanism that this protocol uses is a pseudorandom number generator (PRNG) that is shared with the backend Server. Authentication is achieved by exchanging a few numbers (3 or 5) drawn from the PRNG. The lookup time is constant, and the protocol can be easily adapted to prevent online man-in-the-middle relay attacks. Security is proven in the UC security framework.

Protecting energy consumers's data and privacy is a key factor for the further adoption and diffusion of smart grid technologies and applications. However, current smart grid initiatives and implementations around the globe tend to either focus on the need for technical security to the detriment of privacy or consider privacy as a feature to add after system design. This paper aims to contribute towards filling the gap between this fact and the accepted wisdom that privacy concerns should be addressed as early as possible (preferably when modeling system's requirements). We present a methodological framework for tackling privacy concerns throughout all phases of the smart grid system development process. We describe methods and guiding principles to help smart grid engineers to elicit and analyze privacy threats and requirements from the outset of the system development, and derive the best suitable countermeasures, i.e. privacy enhancing technologies (PETs), accordingly. The paper also provides a summary of modern PETs, and discusses their context of use and contributions with respect to the underlying privacy engineering challenges and the smart grid setting being considered.

The automatic face tracking and detection has been one of the fastest developing areas due to its wide range of application, security and surveillance application in particular. It has been one of the most interest subjects, which suppose but yet to be wholly explored in various research areas due to various distinctive factors: varying ethnic groups, sizes, orientations, poses, occlusions and lighting conditions. The focus of this paper is to propose an improve algorithm to speed up the face tracking and detection process with the simple and efficient proposed novel edge detector to reject the non-face-likes regions, hence reduce the false detection rate in an automatic face tracking and detection in still images with multiple faces for facial expression system. The correct rates of 95.9% on the Haar face detection and proposed novel edge detector, which is higher 6.1% than the primitive integration of Haar and canny edge detector.

Information Technology (IT) security is a growing concern for governments around the world. Cyber terrorism poses a direct threat to the security of the nations' critical infrastructures and ITs as a low-cost asymmetric warfare element. Most of these nations are aware of the vulnerability of the information technologies and the significance of protecting critical infrastructures. To counteract the threat of potentially disastrous cyber attacks, nations' policy makers are increasingly pondering on the use of deterrence strategies to supplement cyber defense. Nations create their own national policies and strategies which cover cyber security countermeasures including cyber defense and deterrence against cyber threats. But it is rather hard to cope with the threat by means of merely `national' cyber defense policies and strategies, since the cyberspace spans worldwide and attack's origin can even be overseas. The term “cyber terrorism” is another source of controversy. An agreement on a common definition of cyber terrorism among the nations is needed. However, the international community has not been able to succeed in developing a commonly accepted comprehensive definition of “terrorism” itself. This paper evaluates the importance of building international cooperation on cyber defense and deterrence against cyber terrorism. It aims to improve and further existing contents and definitions of cyber terrorism; discusses the attractiveness of cyber attacks for terrorists and past experiences on cyber terrorism. It emphasizes establishing international legal measures and cooperation between nations against cyber terrorism in order to maintain the international stability and prosperity. In accordance with NATO's new strategic concept, it focuses on developing the member nations' ability to prevent, detect, defend against and recover from cyber attacks to enhance and coordinate national cyber defense capabilities. It provides necessary steps that have to be taken globally in order to counter cyber terrorism.

Computational soundness results show that under certain conditions it is possible to conclude computational security whenever symbolic security holds. Unfortunately, each soundness result is usually established for some set of cryptographic primitives and extending the result to encompass new primitives typically requires redoing most of the work. In this paper we suggest a way of getting around this problem. We propose a notion of computational soundness that we term deduction soundness. As for other soundness notions, our definition captures the idea that a computational adversary does not have any more power than a symbolic adversary. However, a key aspect of deduction soundness is that it considers, intrinsically, the use of the primitives in the presence of functions specified by the adversary. As a consequence, the resulting notion is amenable to modular extensions. We prove that a deduction sound implementation of some arbitrary primitives can be extended to include asymmetric encryption and public data-structures (e.g. pairings or list), without repeating the original proof effort. Furthermore, our notion of soundness concerns cryptographic primitives in a way that is independent of any protocol specification language. Nonetheless, we show that deduction soundness leads to computational soundness for languages (or protocols) that satisfy a so called commutation property.

Computer crime is a topic prevalent in both the research literature and in industry, due to a number of recent high-profile cyber attacks on e-commerce organizations. While technical means for defending against internal and external hackers have been discussed at great length, researchers have shown a distinct preference towards understanding deterrence of the internal threat and have paid little attention to external deterrence. This paper uses the criminological thesis known as Broken Windows Theory to understand how external computer criminals might be deterred from attacking a particular organization. The theory's focus upon disorder as a precursor to crime is discussed, and the notion of decreasing public IS disorder to create the illusion of strong information systems security is examined. A case study of a victim e-commerce organization is reviewed in light of the theory and implications for research and practice are discussed.

This paper studies Wireless Information-Theoretic Security for low-speed mobility in autonomic networks. More specifically, the impact of user movement on the Probability of Non-Zero Secrecy Capacity and Outage Secrecy Capacity for different channel conditions has been investigated. This is accomplished by establishing a link between different user locations and the boundaries of information-theoretic secure communication. Human mobility scenarios are considered, and its impact on physical layer security is examined, considering quasi-static Rayleigh channels for the fading phenomena. Simulation results have shown that the Secrecy Capacity depends on the relative distance of legitimate and illegitimate (eavesdropper) users in reference to the given transmitter.

Current post-mortem cyber-forensic techniques may cause significant disruption to the evidence gathering process by breaking active network connections and unmounting encrypted disks. Although newer live forensic analysis tools can preserve active state, they may taint evidence by leaving footprints in memory. To help address these concerns we present Forenscope, a framework that allows an investigator to examine the state of an active system without the effects of taint or forensic blurriness caused by analyzing a running system. We show how Forenscope can fit into accepted workflows to improve the evidence gathering process. Forenscope preserves the state of the running system and allows running processes, open files, encrypted filesystems and open network sockets to persist during the analysis process. Forenscope has been tested on live systems to show that it does not operationally disrupt critical processes and that it can perform an analysis in less than 15 seconds while using only 125 KB of memory. We show that Forenscope can detect stealth rootkits, neutralize threats and expedite the investigation process by finding evidence in memory.

In this paper we propose a mechanism of prediction of domestic human activity in a smart home context. We use those predictions to adapt the behavior of home appliances whose impact on the environment is delayed (for example the heating). The behaviors of appliances are built by a reinforcement learning mechanism. We compare the behavior built by the learning approach with both a merely reactive behavior and a state-remanent behavior.

In this paper, a wireless multicast scenario is considered in which the transmitter sends a common message to a group of client receivers through quasi-static Rayleigh fading channel in the presence of an eavesdropper. The communication between transmitter and each client receiver is said to be secured if the eavesdropper is unable to decode any information. On the basis of an information-theoretic formulation of the confidential communications between transmitter and a group of client receivers, we define the expected secrecy sum-mutual information in terms of secure outage probability and provide a complete characterization of maximum transmission rate at which the eavesdropper is unable to decode any information. Moreover, we find the probability of non-zero secrecy mutual information and present an analytical expression for ergodic secrecy multicast mutual information of the proposed model.

Insider threat makes great damage to the security of information system, traditional security methods are extremely difficult to work. Insider attack identification plays an important role in insider threat detection. Monitoring user's abnormal behavior is an effective method to detect impersonation, this method is applied to insider threat identification, to built user's behavior attribute information database based on weights changeable feedback tree augmented Bayes network, but data is massive, using the dimensionality reduction based on rough set, to establish the process information model of user's behavior attribute. Using the minimum risk Bayes decision can effectively identify the real identity of the user when user's behavior departs from the characteristic model.

Edge detection of bottle opening is a primary section to the machine vision based bottle opening detection system. This paper, taking advantage of the Balloon Snake, on the PET (Polyethylene Terephthalate) images sampled at rotating bottle-blowing machine producing pipelines, extracts the opening. It first uses the grayscale weighting average method to calculate the centroid as the initial position of Snake and then based on the energy minimal theory, it extracts the opening. Experiments show that compared with the conventional edge detection and center location methods, Balloon Snake is robust and can easily step over the weak noise points. Edge extracted thorough Balloon Snake is more integral and continuous which provides a guarantee to correctly judge the opening.

The installation of a protection system can provide protection by either deterring or stopping an attacker. Both modes of effectiveness-deterring and stopping-are uncertain. Some have guessed that deterrence plays a much bigger role than stopping force. The force of deterrence should therefore be of considerable interest, especially if its effect could be estimated and incorporated into a larger risk analysis and business case for developing and buying new systems, but nowhere has it been estimated quantitatively. The effect of one type of deterrence, namely, influencing an attacker's choice of targets-or target shifting, biasing an attacker away from some targets toward others-is assessed quantitatively here using a game-theoretic approach. It is shown that its positive effects are significant. It features as a force multiplier on the order of magnitude or more, even for low-performance security countermeasures whose effectiveness may be compromised somewhat, of necessity, in order to keep the number of false alarms serviceably low. The analysis furthermore implies that there are certain minimum levels of stopping performance that a protection should provide in order to avoid attracting the choice of attackers (under deterrence). Nothing in the analysis argues for complacency in security. Developers must still design the best affordable systems. The analysis enters into the middle ground of security, between no protection and impossibly perfect protection. It counters the criticisms that some raise about lower-level, affordable, sustainable measures that security providers naturally gravitate toward. Although these measures might in some places be defeated in ways that a non-expert can imagine, the measures are not for that reason irresponsible or to be dismissed. Their effectiveness can be much greater than they first appear.

Insider attacks is a well-known problem acknowledged as a threat as early as 1980s. The threat is attributed to legitimate users who take advantage of familiarity with the computational environment and abuse their privileges, can easily cause significant damage or losses. In this paper, we present an active defense model and framework of insider threat detection and sense. Firstly, we describe the hierarchical framework which deal with insider threat from several aspects, and subsequently, show a hierarchy-mapping based insider threats model, the kernel of the threats detection, sense and prediction. The experiments show that the model and framework could sense the insider threat in real-time effectively.

In self-organized wireless network, such as ad hoc network, sensor network or mesh network, nodes are independent individuals which have different benefit; Therefore, selfish nodes refuse to forward packets for other nodes in order to save energy which causes the network fault. At the same time, some nodes may be malicious, whose aim is to damage the network. In this paper, we analyze the cooperation stimulation and security in self-organized wireless networks under a game theoretic framework. We first analyze a four node wireless network in which nodes share the channel by relaying for others during its idle periods in order to help the other nodes, each node has to use a part of its available channel capacity. And then, the fault tolerance and security problem is modeled as a non-cooperative game in which each player maximizes its own utility function. The goal of the game is to maximize the utility function in the giving condition in order to get better network efficiency. At last, for characterizing the efficiency of Nash equilibria, we analyze the so called price of anarchy, as the ratio between the objective function at the worst Nash equilibrium and the optimal objective function. Our results show that the players can get the biggest payoff if they obey cooperation strategy.

We investigate the potential of an information-spectrum approach to information-theoretic security. We show how this approach provides conceptually simple yet powerful results that can be used to investigate complex communication scenarios. In particular, we illustrate the usefulness of information-spectrum methods by analyzing the effect of channel state information (CSI) on the secure rates achievable over wiretap channels. We establish a formula for secrecy capacity, which we then specialize to compute achievable rates for ergodic fading channels in the presence of imperfect CSI. Our results confirm the importance of having some knowledge about the eavesdropper's channel, but also show that imperfect CSI does not necessarily preclude security.

By accurately measuring risk for enterprise networks, attack graphs allow network defenders to understand the most critical threats and select the most effective countermeasures. This paper describes substantial enhancements to the NetSPA attack graph system required to model additional present-day threats (zero-day exploits and client-side attacks) and countermeasures (intrusion prevention systems, proxy firewalls, personal firewalls, and host-based vulnerability scans). Point-to-point reachability algorithms and structures were extensively redesigned to support "reverse" reachability computations and personal firewalls. Host-based vulnerability scans are imported and analyzed. Analysis of an operational network with 84 hosts demonstrates that client-side attacks pose a serious threat. Experiments on larger simulated networks demonstrated that NetSPA's previous excellent scaling is maintained. Less than two minutes are required to completely analyze a four-enclave simulated network with more than 40,000 hosts protected by personal firewalls.

Contrary to widespread assumption, dynamic RAM (DRAM), the main memory in most modern computers, retains its contents for several seconds after power is lost, even at room temperature and even if removed from a motherboard. Although DRAM becomes less reliable when it is not refreshed, it is not immediately erased, and its contents persist sufficiently for malicious (or forensic) acquisition of usable full-system memory images. We show that this phenomenon limits the ability of an operating system to protect cryptographic key material from an attacker with physical access to a machine. It poses a particular threat to laptop users who rely on disk encryption: we demonstrate that it could be used to compromise several popular disk encryption products without the need for any special devices or materials. We experimentally characterize the extent and predictability of memory retention and report that remanence times can be increased dramatically with simple cooling techniques. We offer new algorithms for finding cryptographic keys in memory images and for correcting errors caused by bit decay. Though we discuss several strategies for mitigating these risks, we know of no simple remedy that would eliminate them.

REMAN is a reputation management infrastructure for composite Web services. It supports the aggregation of client feedback on the perceived QoS of external services, using reputation mechanisms to build service rankings. Changes in rankings are pro-actively notified to composite service clients to enable self-tuning properties in their execution.

A THz image edge detection approach based on wavelet and neural network is proposed in this paper. First, the source image is decomposed by wavelet, the edges in the low-frequency sub-image are detected using neural network method and the edges in the high-frequency sub-images are detected using wavelet transform method on the coarsest level of the wavelet decomposition, the two edge images are fused according to some fusion rules to obtain the edge image of this level, it then is projected to the next level. Afterwards the final edge image of L-1 level is got according to some fusion rule. This process is repeated until reaching the 0 level thus to get the final integrated and clear edge image. The experimental results show that our approach based on fusion technique is superior to Canny operator method and wavelet transform method alone.

Vehicle-logo location is a crucial step in vehicle-logo recognition system. In this paper, a novel approach of the vehicle-logo location based on edge detection and morphological filter is proposed. Firstly, the approximate location of the vehicle-logo region is determined by the prior knowledge about the position of the vehicle-logo; Secondly, the texture measure is defined to recognize the texture of the vehicle-logo background; Then, vertical edge detection is executed for the vehicle-logo background with the horizontal texture and horizontal edge detection is implemented for the vehicle-logo background with the vertical texture; Finally, position of the vehicle-logo is located accurately by mathematical morphology filter. Experimental results show the proposed method is effective.

In this paper we consider the pollution attack in network coded systems where network nodes are computationally limited. We consider the combined use of cryptographic signature based security and information theoretic network error correction and propose a fountain-like network error correction code construction suitable for this purpose.

BootJacker is a proof-of-concept attack tool which demonstrates that authentication mechanisms employed by an operating system can be bypassed by obtaining physical access and simply forcing a restart. The key insight that enables this attack is that the contents of memory on some machines are fully preserved across a warm boot. Upon a reboot, BootJacker uses this residual memory state to revive the original host operating system environment and run malicious payloads. Using BootJacker, an attacker can break into a locked user session and gain access to open encrypted disks, web browser sessions or other secure network connections. BootJacker's non-persistent design makes it possible for an attacker to leave no traces on the victim machine.

Different organizations or countries maybe adopt different PKI trust model in real applications. On a large scale, all certification authorities (CA) and end entities construct a huge mesh network. PKI trust model exhibits unstructured mesh network as a whole. However, mesh trust model worsens computational complexity in certification path processing when the number of PKI domains increases. This paper proposes an enhanced mesh trust model for PKI. Keys generation and signature are fulfilled in Trusted Platform Module (TPM) for higher security level. An algorithm is suggested to improve the performance of certification path processing in this model. This trust model is less complex but more efficient and robust than the existing PKI trust models.

In this paper we consider recovering data from USB Flash memory sticks after they have been damaged or electronically erased. We describe the physical structure and theory of operation of Flash memories; review the literature of Flash memory data recovery; and report results of new experiments in which we damage USB Flash memory sticks and attempt to recover their contents. The experiments include smashing and shooting memory sticks, incinerating them in petrol and cooking them in a microwave oven.