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Security Requirements Engineering via Commitments
No full textSecurity Requirements Engineering (SRE) is concerned with the identification of security needs and the specification of security requirements of the system-to-be. Mainstream approaches to SRE either focus on technical security mechanisms or suggest high-level organizational abstractions that are hard to map to the actual design. Social commitments are a simple yet powerful abstraction to model social interactions and can be used effectively to specify security requirements. In this paper, we build on our previous work proposing a novel goal-oriented modelling language called SecCo—Security via Commitments—where the concept of social commitment between social and technical actors is adopted to specify security requirements. Commitments enable the development of robust applications, wherein security needs are satisfied by assigning contractual validity to interactions
Solving the problem of electrostatics with a dipole source by means of the duality method
No full textAim of this note is to give a simple and direct proof of the existence and uniqueness of the solution to the problem of electrostatics when the source (namely, the applied current density) is a dipole. The result is obtained by using the classical duality method
Event Detection and Scene Attraction by Very Simple Contextual Cues
No full textWe detect and arrange events in private photo archives by putting these photos into context. The problem is seen as a fully auto- mated mining in one’s personal life and behavior. To this end, we build a contextual meaningful hierarchy of events based on personal photos. With the analysis of very simple cues of time, space and perceptual visual appearance we are refining and validating the event borders and their relation in an iterative way. Beginning with discriminating between routine and unusual events, we are able to robustly recognize the basic nature of an event. Further combination of the given cues efficiently gives a hierarchy of events that coincides with the given ground-truth at an F-measure of 0.83 for event detection and 0.70 for its hierarchical representation. We process the given task in a fully unsupervised and computationally inexpensive manner. Using standard clustering and machine learning techniques, sparse events in the collection would tend to be neglected by automated approaches. Opposed to these methods, the proposed approach is invariant to the distribution of the photo collection regarding the sparsity and denseness in time, space and visual appearance. This is improved by introducing a momentum of attraction measure for a meaningful representation of personal events. "© ACM, 2011. This is the authors version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in J-MRE '11: Proceedings of the 2011 joint ACM workshop on Modeling and representing events, http://dx.doi.org/10.1145/2072508.2072510"
A survey of runtime policy enforcement techniques and implementations
No full textRuntime techniques bring new promises of accuracy and flexibility in enforcing security policies. While static security enforcement was previously studied and classified, this work is the first to survey the state of the art on runtime security enforcement. Our purpose is to encourage a better understanding of limitations and advantages of enforcement techniques and their implementations. We classify techniques by criteria such as abstraction level, enforced policies and security guarantees. We analyse several implementations of each technique, from the point of view of trust model, policy language and performance overhead. Finally, we discuss research issues for further investigation in policy enforcement
Scalable Similarity Matching in Streaming Time Series
No full textNowadays online monitoring of data streams is essential in many real life applications, like sensor network monitoring, manufacturing process control, and video surveillance. One major problem in this area is the online identification of streaming sequences similar to a predefined set of pattern-sequences. In this paper, we present a novel solution that extends the state of the art both in terms of effectiveness and efficiency. We propose the first online similarity matching algorithm based on Longest Common SubSequence that is specifically designed to operate in a streaming context, and that can effectively handle time scaling, as well as noisy data. In order to deal with high stream rates and multiple streams, we extend the algorithm to operate on multilevel approximations of the streaming data, therefore quickly pruning the search space. Finally, we incorporate in our approach error estimation mechanisms in order to reduce the number of false negatives. We perform an extensive experimental evaluation using forty real datasets, diverse in nature and characteristics, and we also compare our approach to previous techniques. The experiments demonstrate the validity of our approach. The original publication is available in PAKDD 2012, Proceedings in Lecture Notes in Artificial Intelligence (LNAI), Springer Verlag (www.springerlink.com)
Probabilistic representations for the solutions of higher order differential equations
No full textA probabilistic representation for the solution of the partial differential equation , \alpha\in\C_+, is constructed in terms of the expectation with respect to the measure associated to a complex-valued stochastic process
Revisiting the Wackernagelposition. The Evolution of the Cimbrian Pronominal System
No full textThe present contribution reconstructs the development of the personal object pronouns of Cimbrian, a German dialect spoken in Northern Italy which evolved many centuries in close contact with northern Italy’s Romance dialects. With reference to their functional status and their clausal position we discover that Cimbrian’s object pronouns started from a German model and have over time become closer to a Romance one. In the older Cimbrian texts, these elements are clearly recognizable as full phrases (XP), occupying the traditional Wackernagelposition; in modern writings they behave as heads (X°) and appear only in an ‘adverbal’ position, i.e. enclitic to the finite verb, similarly to the syntax of Romance object pronouns. The fact that they cannot be realized as proclitic to the finite verb – like the Romance ones – shows however that the original Germanic syntax limits the influence of that Romance. Attempting to explain this phenomenon, this current study suggests revisiting the structure of the Wackernagelposition
TwoLayered Architecture for PeertoPeer Concept Search
No full textPeer-to-peer search is an alternative to address the scalability concerns regarding centralized search, due to its inherent scalability in terms of computational resources. Concept search is an information retrieval approach which is based on retrieval models and data structures of syntactic search, but which searches for concepts rather than words thus addressing the ambiguity problems of syntactic search approach. In this paper, we combine peer-to-peer search with concept search and compare two di®erent approaches to peer-to-peer concept-based search. In a single layer peer-to-peer concept search, a single universal knowledge is used to map terms to concepts. In a two layered peer-to-peer concept search, the universal knowledge is used in identifying the appropriate community given query terms and the community's background knowledge is used to map query terms to appropriate concepts within selected community. Since the search is done only in relevant communities, there will be improvement in bandwidth utilization for search. Since two layered peer-to-peer concept search uses the community's background knowledge to map terms to concepts, it improves quality and e±ciency of search. We perform experiments to compare the two layered peer-to-peer concept search with single layered peer-to-peer concept search and present our results in this paper. We also show in this paper how the two layers of knowledge help in achieving scalable and interoperable semantics
Awareness Requirements for Adaptive Systems
No full textRecently, there has been a growing interest in self-adaptive systems. Roadmap papers in this area point to feedback loops as a promising way of operationalizing adaptivity in such systems. In this paper, we present a new type of requirement – called Awareness Requirement – that can refer to other requirements and their success/failures, constituting requirements for such feedback loops. We propose a way to elicit and formalize such requirements and validate our proposal using a monitoring framework. We further discuss how feedback loops could be implemented to provide adaptivity mechanisms to systems
Timing of Investment and Dynamic Pricing in Privatized Sectors
No full textFirms in equipment-intensive sectors, where investment in production is performed at diminishing marginal cost, spend billions of dollars in equipment and production capacity. Typically, this expenditure is induced by either the replacement of existing equipment, which deteriorates with age and can result in higher operating costs and lower production capacity, or further investment, to benefit from any technological improvement embedded in new equipment. We identify the optimal price policy, and the ensuing optimal sequence of investment timing a privatized firm selects through time and compare them with choices made at the time when such a type of firm was under public-ownership