Biblio
In this work, we give a lattice attack on the ECDSA implementation in the latest version of OpenSSL, which implement the scalar multiplication by windowed Non-Adjacent Form method. We propose a totally different but more efficient method of extracting and utilizing information from the side-channel results, remarkably improving the previous attacks. First, we develop a new efficient method, which can extract almost all information from the side-channel results, obtaining 105.8 bits of information per signature on average for 256-bit ECDSA. Then in order to make the utmost of our extracted information, we translate the problem of recovering secret key to the Extended Hidden Number Problem, which can be solved by lattice reduction algorithms. Finally, we introduce the methods of elimination, merging, most significant digit recovering and enumeration to improve the attack. Our attack is mounted to the \series secp256k1\ curve, and the result shows that only 4 signatures would be enough to recover the secret key if the Flush+Reload attack is implemented perfectly without any error,which is much better than the best known result needing at least 13 signatures.
The Google Identity Platform is a system that allows a user to sign in to applications and other services by using a Google account. Google Sign-In is one such method for providing one’s identity to the Google Identity Platform. Google Sign-In is available for Android applications and iOS applications, as well as for websites and other devices. Users of Google Sign-In find that it integrates well with the Android platform, but iOS users (iPhone, iPad, etc.) do not have the same experience. The user experience when logging in to a Google account on an iOS application can not only be more tedious than the Android experience, but it also conditions users to engage in behaviors that put the information in their Google accounts at risk.
We give attacks on Feistel-based format-preserving encryption (FPE) schemes that succeed in message recovery (not merely distinguishing scheme outputs from random) when the message space is small. For \$4\$-bit messages, the attacks fully recover the target message using \$2textasciicircum1 examples for the FF3 NIST standard and \$2textasciicircum5 examples for the FF1 NIST standard. The examples include only three messages per tweak, which is what makes the attacks non-trivial even though the total number of examples exceeds the size of the domain. The attacks are rigorously analyzed in a new definitional framework of message-recovery security. The attacks are easily put out of reach by increasing the number of Feistel rounds in the standards.
Privacy-preserving range queries allow encrypting data while still enabling queries on ciphertexts if their corresponding plaintexts fall within a requested range. This provides a data owner the possibility to outsource data collections to a cloud service provider without sacrificing privacy nor losing functionality of filtering this data. However, existing methods for range queries either leak additional information (like the ordering of the complete data set) or slow down the search process tremendously by requiring to query each ciphertext in the data collection. We present a novel scheme that only leaks the access pattern while supporting amortized poly-logarithmic search time. Our construction is based on the novel idea of enabling the cloud service provider to compare requested range queries. By doing so, the cloud service provider can use the access pattern to speed-up search time for range queries in the future. On the one hand, values that have fallen within a queried range, are stored in an interactively built index for future requests. On the other hand, values that have not been queried do not leak any information to the cloud service provider and stay perfectly secure. In order to show its practicability we have implemented our scheme and give a detailed runtime evaluation.
The HTTPS ecosystem, including the SSL/TLS protocol, the X.509 public-key infrastructure, and their cryptographic libraries, is the standardized foundation of Internet Security. Despite 20 years of progress and extensions, however, its practical security remains controversial, as witnessed by recent efforts to improve its design and implementations, as well as recent disclosures of attacks against its deployments. The Everest project is a collaboration between Microsoft Research, INRIA, and the community at large that aims at modelling, programming, and verifying the main HTTPS components with strong machine-checked security guarantees, down to core system and cryptographic assumptions. Although HTTPS involves a relatively small amount of code, it requires efficient low-level programming and intricate proofs of functional correctness and security. To this end, we are also improving our verifications tools (F*, Dafny, Lean, Z3) and developing new ones. In my talk, I will present our project, review our experience with miTLS, a verified reference implementation of TLS coded in F*, and describe current work towards verified, secure, efficient HTTPS.
The demand for trained cybersecurity operators is growing more quickly than traditional programs in higher education can fill. At the same time, unemployment for returning military veterans has become a nationally discussed problem. We describe the design and launch of New Skills for a New Fight (NSNF), an intensive, one-year program to train military veterans for the cybersecurity field. This non-traditional program, which leverages experience that veterans gained in military service, includes recruitment and selection, a base of knowledge in the form of four university courses in a simultaneous cohort mode, a period of hands-on cybersecurity training, industry certifications and a practical internship in a Security Operations Center (SOC). Twenty veterans entered this pilot program in January of 2016, and will complete in less than a year's time. Initially funded by a global financial services company, the program provides veterans with an expense-free preparation for an entry-level cybersecurity job.
Recent years have witnessed a flourish of hands-on cybersecurity labs and competitions. The information technology (IT) education community has recognized their significant role in boosting students' interest in security and enhancing their security knowledge and skills. Compared to the focus on individual based education materials, much less attention has been paid to the development of tools and materials suitable for team-based security practices, which, however, prevail in real-world environments. One major bottleneck is lack of suitable platforms for this type of practices in IT education community. In this paper, we propose a low-cost, team-oriented cybersecurity practice platform called Platoon. The Platoon platform allows for quickly and automatically creating one or more virtual networks that mimic real-world corporate networks using a regular computer. The virtual environment created by Platoon is suitable for both cybersecurity labs, competitions, and projects. The performance data and user feedback collected from our cyber-defense exercises indicate that Platoon is practical and useful for enhancing students' security learning outcomes.
Friends, family and colleagues at work may repeatedly observe how their peers unlock their smartphones. These "insiders" may combine multiple partial observations to form a hypothesis of a target's secret. This changing landscape requires that we update the methods used to assess the security of unlocking mechanisms against human shoulder surfing attacks. In our paper, we introduce a methodology to study shoulder surfing risks in the insider threat model. Our methodology dissects the authentication process into minimal observations by humans. Further processing is based on simulations. The outcome is an estimate of the number of observations needed to break a mechanism. The flexibility of this approach benefits the design of new mechanisms. We demonstrate the application of our methodology by performing an analysis of the SwiPIN scheme published at CHI 2015. Our results indicate that SwiPIN can be defeated reliably by a majority of the population with as few as 6 to 11 observations.
Technological changes bring great efficiencies and opportunities; however, they also bring new threats and dangers that users are often ill prepared to handle. Some individuals have training at work or school while others have family or friends to help them. However, there are few widely known or ubiquitous educational programs to inform and motivate users to develop safe cybersecurity practices. Additionally, little is known about learning strategies in this domain. Understanding how active Internet users have learned their security practices can give insight into more effective learning methods. I surveyed 800 online labor workers to discover their learning processes. They shared how they had to construct their own schema and negotiate meaning in a complex domain. Findings suggest a need to help users build a dynamic mental model of security. Participants recommend encouraging participatory and constructive learning, multi-model dissemination, and ubiquitous opportunities for learning security behaviors.
This panel will discuss and debate what role(s) the information technology discipline should have in cybersecurity. Diverse viewpoints will be considered including current and potential ACM curricular recommendations, current and potential ABET and NSA accreditation criteria, the emerging cybersecurity discipline(s), consideration of government frameworks, the need for a multi-disciplinary approach to cybersecurity, and what aspects of cybersecurity should be under information technology's purview.
The smart grid changes the way energy is produced and distributed. In addition both, energy and information is exchanged bidirectionally among participating parties. Therefore heterogeneous systems have to cooperate effectively in order to achieve a common high-level use case, such as smart metering for billing or demand response for load curtailment. Furthermore, a substantial amount of personal data is often needed for achieving that goal. Capturing and processing personal data in the smart grid increases customer concerns about privacy and in addition, certain statutory and operational requirements regarding privacy aware data processing and storage have to be met. An increase of privacy constraints, however, often limits the operational capabilities of the system. In this paper, we present an approach that automates the process of finding an optimal balance between privacy requirements and operational requirements in a smart grid use case and application scenario. This is achieved by formally describing use cases in an abstract model and by finding an algorithm that determines the optimum balance by forward mapping privacy and operational impacts. For this optimal balancing algorithm both, a numeric approximation and - if feasible - an analytic assessment are presented and investigated. The system is evaluated by applying the tool to a real-world use case from the University of Southern California (USC) microgrid.
User uses smartphones for web surfing and browsing data. Many smartphones are embedded with inbuilt location aware system called GPS [Global Positioning System]. Using GPS user have to register and share his all private information to the LBS server. LBS is nothing but Location Based Service. Simply user sends the query to the LBS server. Then what is happening the LBS server gives a private information regarding particular user location. There will be a possibility to misuse this information so using mobile crowd method hides user location from LBS server and avoid sharing of privacy information with server. Our solution does not required to change the LBS server architecture.
This paper introduces a research agenda focusing on cybersecurity in the context of product lifecycle management. The paper discusses research directions on critical protection techniques, including protection techniques from insider threat, access control systems, secure supply chains and remote 3D printing, compliance techniques, and secure collaboration techniques. The paper then presents an overview of DBSAFE, a system for protecting data from insider threat.
Information and communication technologies have augmented interoperability and rapidly advanced varying industries, with vast complex interconnected networks being formed in areas such as safety-critical systems, which can be further categorised as critical infrastructures. What also must be considered is the paradigm of the Internet of Things which is rapidly gaining prevalence within the field of wireless communications, being incorporated into areas such as e-health and automation for industrial manufacturing. As critical infrastructures and the Internet of Things begin to integrate into much wider networks, their reliance upon communication assets by third parties to ensure collaboration and control of their systems will significantly increase, along with system complexity and the requirement for improved security metrics. We present a critical analysis of the risk assessment methods developed for generating attack graphs. The failings of these existing schemas include the inability to accurately identify the relationships and interdependencies between the risks and the reduction of attack graph size and generation complexity. Many existing methods also fail due to the heavy reliance upon the input, identification of vulnerabilities, and analysis of results by human intervention. Conveying our work, we outline our approach to modelling interdependencies within large heterogeneous collaborative infrastructures, proposing a distributed schema which utilises network modelling and attack graph generation methods, to provide a means for vulnerabilities, exploits and conditions to be represented within a unified model.
The smart grid aims to improve the efficiency, reliability and safety of the electric system via modern communication system, it's necessary to utilize cloud computing to process and store the data. In fact, it's a promising paradigm to integrate smart grid into cloud computing. However, access to cloud computing system also brings data security issues. This paper focuses on the protection of user privacy in smart meter system based on data combination privacy and trusted third party. The paper demonstrates the security issues for smart grid communication system and cloud computing respectively, and illustrates the security issues for the integration. And we introduce data chunk storage and chunk relationship confusion to protect user privacy. We also propose a chunk information list system for inserting and searching data.
Coactive Design is a new approach to address the increasingly sophisticated roles that people and robots play as the use of robots expands into new, complex domains. The approach is motivated by the desire for robots to perform less like teleoperated tools or independent automatons and more like interdependent teammates. In this article, we describe what it means to be interdependent, why this is important, and the design implications that follow from this perspective. We argue for a human-robot system model that supports interdependence through careful attention to requirements for observability, predictability, and directability. We present a Coactive Design method and show how it can be a useful approach for developers trying to understand how to translate high-level teamwork concepts into reusable control algorithms, interface elements, and behaviors that enable robots to fulfill their envisioned role as teammates. As an example of the coactive design approach, we present our results from the DARPA Virtual Robotics Challenge, a competition designed to spur development of advanced robots that can assist humans in recovering from natural and man-made disasters. Twenty-six teams from eight countries competed in three different tasks providing an excellent evaluation of the relative effectiveness of different approaches to human-machine system design.
The objective of this paper is to explore the current notions of systems and “System of Systems” and establish the case for quantitative characterization of their structural, behavioural and contextual facets that will pave the way for further formal development (mathematical formulation). This is partly driven by stakeholder needs and perspectives and also in response to the necessity to attribute and communicate the properties of a system more succinctly, meaningfully and efficiently. The systematic quantitative characterization framework proposed will endeavor to extend the notion of emergence that allows the definition of appropriate metrics in the context of a number of systems ontologies. The general characteristic and information content of the ontologies relevant to system and system of system will be specified but not developed at this stage. The current supra-system, system and sub-system hierarchy is also explored for the formalisation of a standard notation in order to depict a relative scale and order and avoid the seemingly arbitrary attributions.
Mobile users access location services from a location based server. While doing so, the user's privacy is at risk. The server has access to all details about the user. Example the recently visited places, the type of information he accesses. We have presented synergetic technique to safeguard location privacy of users accessing location-based services via mobile devices. Mobile devices have a capability to form ad-hoc networks to hide a user's identity and position. The user who requires the service is the query originator and who requests the service on behalf of query originator is the query sender. The query originator selects the query sender with equal probability which leads to anonymity in the network. The location revealed to the location service provider is a rectangle instead of exact co-ordinate. In this paper we have simulated the mobile network and shown the results for cloaking area sizes and performance against the variation in the density of users.
To allow fine-grained access control of sensitive data, researchers have proposed various types of functional encryption schemes, such as identity-based encryption, searchable encryption and attribute-based encryption. We observe that it is difficult to define some complex access policies in certain application scenarios by using these schemes individually. In this paper, we attempt to address this problem by proposing a functional encryption approach named Key-Policy Attribute-Based Encryption with Attribute Extension (KP-ABE-AE). In this approach, we utilize extended attributes to integrate various encryption schemes that support different access policies under a common top-level KP-ABE scheme, thus expanding the scope of access policies that can be defined. Theoretical analysis and experimental studies are conducted to demonstrate the applicability of the proposed KP-ABE-AE. We also present an optimization for a special application of KP-ABE-AE where IPE schemes are integrated with a KP-ABE scheme. The optimization results in an integrated scheme with better efficiency when compared to the existing encryption schemes that support the same scope of access policies.
This article addresses trust in computer systems as a social phenomenon, which depends on the type of relationship that is established through the computer, or with other individuals. It starts by theoretically contextualizing trust, and then situates trust in the field of computer science. Then, describes the proposed model, which builds on what one perceives to be trustworthy and is influenced by a number of factors such as the history of participation and user's perceptions. It ends by situating the proposed model as a key contribution for leveraging trustful interactions and ends by proposing it used to serve as a complement to foster user's trust needs in what concerns Human-computer Iteration or Computermediated Interactions.
Today, beyond a legitimate usage, the numerous advantages of cloud computing are exploited by attackers, and Botnets supporting DDoS attacks are among the greatest beneficiaries of this malicious use. Such a phenomena is a major issue since it strongly increases the power of distributed massive attacks while involving the responsibility of cloud service providers that do not own appropriate solutions. In this paper, we present an original approach that enables a source-based de- tection of UDP-flood DDoS attacks based on a distributed system behavior analysis. Based on a principal component analysis, our contribution consists in: (1) defining the involvement of system metrics in a botcoud's behavior, (2) showing the invariability of the factorial space that defines a botcloud activity and (3) among several legitimate activities, using this factorial space to enable a botcloud detection.
Today, beyond a legitimate usage, the numerous advantages of cloud computing are exploited by attackers, and Botnets supporting DDoS attacks are among the greatest beneficiaries of this malicious use. Such a phenomena is a major issue since it strongly increases the power of distributed massive attacks while involving the responsibility of cloud service providers that do not own appropriate solutions. In this paper, we present an original approach that enables a source-based de- tection of UDP-flood DDoS attacks based on a distributed system behavior analysis. Based on a principal component analysis, our contribution consists in: (1) defining the involvement of system metrics in a botcoud's behavior, (2) showing the invariability of the factorial space that defines a botcloud activity and (3) among several legitimate activities, using this factorial space to enable a botcloud detection.
Applications such as fleet management and logistics, emergency response, public security and surveillance or mobile workforce management use geo-positioning and mobile networks as means of enabling real-time monitoring, communication and collaboration among a possibly large set of mobile nodes. The majority of those systems require real-time tracking of mobile nodes (e.g. vehicles, people or mobile robots), reliable communication to/from the nodes, as well as group communication among the mobile nodes. In this paper we describe a distributed middleware with focus on management of context-defined groups of mobile nodes, and group communication with large sets of nodes. We also present a prototype Fleet Tracking and Management system based on our middleware, give an example of how context-specific group communication can enhance the node's mutual awareness, and show initial performance results that indicate small overhead and latency of the group communication and management.
In this article, researcher collaboration patterns and research topics on Intelligence and Security Informatics (ISI) are investigated using social network analysis approaches. The collaboration networks exhibit scale-free property and small-world effect. From these networks, the authors obtain the key researchers, institutions, and three important topics.