Biblio

When a person gets to a door and wants to get in, what do they do? They knock. In our system, the user's specific knock pattern authenticates their identity, and opens the door for them. The system empowers people's intuitive actions and responses to affect the world around them in a new way. We leverage IOT, and physical computing to make more technology feel like less. From there, the system of a knock based entrance creates affordances in social interaction for shared spaces wherein ownership fluidity and accessibility needs to be balanced with security

Electronic power grid is a distributed network used for transferring electricity and power from power plants to consumers. Based on sensor readings and control system signals, power grid states are measured and estimated. As a result, most conventional attacks, such as denial-of-service attacks and random attacks, could be found by using the Kalman filter. However, false data injection attacks are designed against state estimation models. Currently, distributed Kalman filtering is proved effective in sensor networks for detection and estimation problems. Since meters are distributed in smart power grids, distributed estimation models can be used. Thus in this paper, we propose a diffusion Kalman filter for the power grid to have a good performance in estimating models and to effectively detect false data injection attacks.

While many text-based CAPTCHA schemes have been broken, hollow CAPTCHAs as a new technology have been used by many websites. The generation method of currently used hollow CAPTCHAs is investigated, we found there is color difference between the boundary of characters contour lines and noise arcs. An algorithm of noise arcs removal to deal with this vulnerability is proposed. Furthermore, a de-noising and segmentation scheme for hollow CAPTCHAs with noise arcs is presented. The scheme is verified by the real CAPTCHA data from the website Sina Weibo. The success segmentation rate is 77%. Finally, some advice is given to improve the design of hollow CAPTCHA.

Additive Manufacturing (AM) uses Cyber-Physical Systems (CPS) (e.g., 3D Printers) that are vulnerable to kinetic cyber-attacks. Kinetic cyber-attacks cause physical damage to the system from the cyber domain. In AM, kinetic cyber-attacks are realized by introducing flaws in the design of the 3D objects. These flaws may eventually compromise the structural integrity of the printed objects. In CPS, researchers have designed various attack detection method to detect the attacks on the integrity of the system. However, in AM, attack detection method is in its infancy. Moreover, analog emissions (such as acoustics, electromagnetic emissions, etc.) from the side-channels of AM have not been fully considered as a parameter for attack detection. To aid the security research in AM, this paper presents a novel attack detection method that is able to detect zero-day kinetic cyber-attacks on AM by identifying anomalous analog emissions which arise as an outcome of the attack. This is achieved by statistically estimating functions that map the relation between the analog emissions and the corresponding cyber domain data (such as G-code) to model the behavior of the system. Our method has been tested to detect potential zero-day kinetic cyber-attacks in fused deposition modeling based AM. These attacks can physically manifest to change various parameters of the 3D object, such as speed, dimension, and movement axis. Accuracy, defined as the capability of our method to detect the range of variations introduced to these parameters as a result of kinetic cyber-attacks, is 77.45%.

We present a method for key compression in quantumresistant isogeny-based cryptosystems, which allows a reduction in and transmission costs of per-party public information by a factor of two, with no e ect on security. We achieve this reduction by associating a canonical choice of elliptic curve to each j-invariant, and representing elements on the curve as linear combinations with respect to a canonical choice of basis. This method of compressing public information can be applied to numerous isogeny-based protocols, such as key exchange, zero-knowledge identi cation, and public-key encryption. We performed personal computer and ARM implementations of the key exchange with compression and decompression in C and provided timing results, showing the computational cost of key compression and decompression at various security levels. Our results show that isogeny-based cryptosystems achieve by far the smallest possible key sizes among all existing families of post-quantum cryptosystems at practical security levels; e.g. 3073-bit public keys at the quantum 128-bit security level, comparable to (non-quantum) RSA key sizes.

We present a method for key compression in quantumresistant isogeny-based cryptosystems, which allows a reduction in and transmission costs of per-party public information by a factor of two, with no e ect on security. We achieve this reduction by associating a canonical choice of elliptic curve to each j-invariant, and representing elements on the curve as linear combinations with respect to a canonical choice of basis. This method of compressing public information can be applied to numerous isogeny-based protocols, such as key exchange, zero-knowledge identi cation, and public-key encryption. We performed personal computer and ARM implementations of the key exchange with compression and decompression in C and provided timing results, showing the computational cost of key compression and decompression at various security levels. Our results show that isogeny-based cryptosystems achieve by far the smallest possible key sizes among all existing families of post-quantum cryptosystems at practical security levels; e.g. 3073-bit public keys at the quantum 128-bit security level, comparable to (non-quantum) RSA key sizes.

A Mobile Ad hoc Network (MANET) is a spontaneous network consisting of wireless nodes which are mobile and self-configuring in nature. Devices in MANET can move freely in any direction independently and change its link frequently to other devices. MANET does not have centralized infrastructure and its characteristics makes this network vulnerable to various kinds of attacks. Data transfer is a major problem due to its nature of unreliable wireless medium. Commonly used technique for secure transmission in wireless network is cryptography. Use of cryptography key is often involved in most of cryptographic techniques. Key management is main component in security issues of MANET and various schemes have been proposed for it. In this paper, a study on various kinds of key management techniques in MANET is presented.

Today's cellular core, which connects the radio access network to the Internet, relies on fixed hardware appliances placed at a few dedicated locations and uses relatively static routing policies. As such, today's core design has key limitations—it induces inefficient provisioning tradeoffs and is poorly equipped to handle overload, failure scenarios, and diverse application requirements. To address these limitations, ongoing efforts envision "clean slate" solutions that depart from cellular standards and routing protocols; e.g., via programmable switches at base stations and per-flow SDN-like orchestration. The driving question of this work is to ask if a clean-slate redesign is necessary and if not, how can we design a flexible cellular core that is minimally disruptive. We propose KLEIN, a design that stays within the confines of current cellular standards and addresses the above limitations by combining network functions virtualization with smart resource management. We address key challenges w.r.t. scalability and responsiveness in realizing KLEIN via backwards-compatible orchestration mechanisms. Our evaluations through data-driven simulations and real prototype experiments using OpenAirInterface show that KLEIN can scale to billions of devices and is close to optimal for wide variety of traffic and deployment parameters.

Cloud computing is one of the happening technologies in these years and gives scope to lot of research ideas. Banks are likely to enter the cloud computing field because of abundant advantages offered by cloud like reduced IT costs, pay-per-use modeling, and business agility and green IT. Main challenges to be addressed while moving bank to cloud are security breach, governance, and Service Level Agreements (SLA). Banks should not give prospect for security breaches at any cost. Access control and authorization are vivacious solutions to security risks. Thus we are proposing a knowledge based security model addressing the present issue. Separate ontologies for subject, object, and action elements are created and an authorization rule is framed by considering the inter linkage between those elements to ensure data security with restricted access. Moreover banks are now using Software as a Service (SaaS), which is managed by Cloud Service Providers (CSPs). Banks rely upon the security measures provided by CSPs. If CSPs follow traditional security model, then the data security will be a big question. Our work facilitates the bank to pose some security measures on their side along with the security provided by the CSPs. Banks can add and delete rules according to their needs and can have control over the data in addition to CSPs. We also showed the performance analysis of our model and proved that our model provides secure access to bank data.

In the context of service-oriented applications, the self-healing property provides reliable execution in order to support failures and assist automatic recovery techniques. This paper presents a knowledge-based approach for self-healing Composite Service (CS) applications. A CS is an application composed by a set of services interacting each other and invoked on the Web. Our approach is supported by Service Agents, which are in charge of the CS fault-tolerance execution control, making decisions about the selection of recovery and proactive strategies. Service Agents decisions are based on the information they have about the whole application, about themselves, and about what it is expected and what it is really happening at run-time. Hence, application knowledge for decision making comprises off-line precomputed global and local information, user QoS preferences, and propagated actual run-time information. Our approach is evaluated experimentally using a case study.

We show that the Kolmogorov extension theorem and the Doob martingale convergence theorem are two aspects of a common generalization, namely a colimit-like construction in a category of Radon spaces and reversible Markov kernels. The construction provides a compositional denotational semantics for lossless iteration in probabilistic programming languages, even in the absence of a natural partial order.

Customer Edge Switching (CES) is an experimental Internet architecture that provides reliable and resilient multi-domain communications. It provides resilience against security threats because domains negotiate inbound and outbound policies before admitting new traffic. As CES and its signalling protocols are being prototyped, there is a need for independent testing of the CES architecture. Hence, our research goal is to develop an automated test framework that CES protocol designers and early adopters can use to improve the architecture. The test framework includes security, functional, and performance tests. Using the Robot Framework and STRIDE analysis, in this paper we present this automated security test framework. By evaluating sample test scenarios, we show that the Robot Framework and our CES test suite have provided productive discussions about this new architecture, in addition to serving as clear, easy-to-read documentation. Our research also confirms that test automation can be useful to improve new protocol architectures and validate their implementation.

It is accepted that the way a person types on a keyboard contains timing patterns, which can be used to classify him/her, is known as keystroke dynamics. Keystroke dynamics is a behavioural biometric modality, whose performances, however, are worse than morphological modalities such as fingerprint, iris recognition or face recognition. To cope with this, we propose to combine keystroke dynamics with soft biometrics. Soft biometrics refers to biometric characteristics that are not sufficient to authenticate a user (e.g. height, gender, skin/eye/hair colour). Concerning keystroke dynamics, three soft categories are considered: gender, age and handedness. We present different methods to combine the results of a classical keystroke dynamics system with such soft criteria. By applying simple sum and multiply rules, our experiments suggest that the combination approach performs better than the classification approach with best result of 5.41% of equal error rate. The efficiency of our approaches is illustrated on a public database.

Although a fairly new topic in the context of cyber security, situation awareness (SA) has a far longer history of study and applications in such areas as control of complex enterprises and in conventional warfare. Far more is known about the SA in conventional military conflicts, or adversarial engagements, than in cyber ones. By exploring what is known about SA in conventional–-also commonly referred to as kinetic–-battles, we may gain insights and research directions relevant to cyber conflicts. For this reason, having outlined the foundations and challenges on CSA in the previous chapter, we proceed to discuss the nature of SA in conventional (often called kinetic) conflict, review what is known about this kinetic SA (KSA), and then offer a comparison with what is currently understood regarding the cyber SA (CSA). We find that challenges and opportunities of KSA and CSA are similar or at least parallel in several important ways. With respect to similarities, in both kinetic and cyber worlds, SA strongly impacts the outcome of the mission. Also similarly, cognitive biases are found in both KSA and CSA. As an example of differences, KSA often relies on commonly accepted, widely used organizing representation–-map of the physical terrain of the battlefield. No such common representation has emerged in CSA, yet.

In Wireless sensor networks (WSNs), many tiny sensor nodes communicate using wireless links and collaborate with each other. The data collected by each of the nodes is communicated towards the gateway node after carrying out aggregation of the data by different nodes. It is necessary to secure the data collected by the WSN nodes while they communicate among themselves using multi hop wireless links. To meet this objective it is required to make use of energy efficient cryptographic algorithms so that the same can be ported over the resource constrained nodes. It is needed to create trust initially among the WSN nodes while using any of the cryptographic algorithms. Towards this, a key management technique needs to be made use of. Due to the resource constrained nature of the WSN nodes and the remote deployment of the nodes, an implementation of conventional key management techniques is infeasible. This work proposes a key management technique, with its reduced resource overheads, which is highly suited to be used in hierarchical WSN applications. Both Identity based key management (IBK) and probabilistic key pre-distribution schemes are made use of at different hierarchical levels. The proposed key management technique has been implemented using IRIS WSN nodes. A comparison of resource overheads has also been carried out.

Cloud computing paradigm is being used because of its low up-front cost. In recent years, even mobile phone users store their data at Cloud. Customer information stored at Cloud needs to be protected against potential intruders as well as cloud service provider. There is threat to the data in transit and data at cloud due to different possible attacks. Organizations are transferring important information to the Cloud that increases concern over security of data. Cryptography is common approach to protect the sensitive information in Cloud. Cryptography involves managing encryption and decryption keys. In this paper, we compare key management methods, apply key management methods to various cloud environments and analyze symmetric key cryptography algorithms.

By enabling a direct comparison of different security solutions with respect to their relative effectiveness, a network security metric may provide quantifiable evidences to assist security practitioners in securing computer networks. However, research on security metrics has been hindered by difficulties in handling zero-day attacks exploiting unknown vulnerabilities. In fact, the security risk of unknown vulnerabilities has been considered as something unmeasurable due to the less predictable nature of software flaws. This causes a major difficulty to security metrics, because a more secure configuration would be of little value if it were equally susceptible to zero-day attacks. In this paper, we propose a novel security metric, k-zero day safety, to address this issue. Instead of attempting to rank unknown vulnerabilities, our metric counts how many such vulnerabilities would be required for compromising network assets; a larger count implies more security because the likelihood of having more unknown vulnerabilities available, applicable, and exploitable all at the same time will be significantly lower. We formally define the metric, analyze the complexity of computing the metric, devise heuristic algorithms for intractable cases, and finally demonstrate through case studies that applying the metric to existing network security practices may generate actionable knowledge.

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.

Wireless sensor networks offer benefits in several applications but are vulnerable to various security threats, such as eavesdropping and hardware tampering. In order to reach secure communications among nodes, many approaches employ symmetric encryption. Several key management schemes have been proposed in order to establish symmetric keys. The paper presents an innovative key management scheme called random seed distribution with transitory master key, which adopts the random distribution of secret material and a transitory master key used to generate pairwise keys. The proposed approach addresses the main drawbacks of the previous approaches based on these techniques. Moreover, it overperforms the state-of-the-art protocols by providing always a high security level.

An identity authentication scheme is proposed combining with biometric encryption, public key cryptography of homomorphism and predicate encryption technology under the cloud computing environment. Identity authentication scheme is proposed based on the voice and homomorphism technology. The scheme is divided into four stages, register and training template stage, voice login and authentication stage, authorization stage, and audit stage. The results prove the scheme has certain advantages in four aspects.

With the rapid development of mobile internet, mobile devices are requiring more complex authorization policy to ensure an secure access control on mobile data. However mobiles have limited resources (computing, storage, etc.) and are not suitable to execute complex operations. Cloud computing is an increasingly popular paradigm for accessing powerful computing resources. Intuitively we can solve that problem by moving the complex access control process to the cloud and implement a fine-grained access control relying on the powerful cloud. However the cloud computation may not be trusted, a crucial problem is how to verify the correctness of such computations. In this paper, we proposed a public verifiable cloud access control scheme based on Parno's public verifiable computation protocol. For the first time, we proposed the conception and concrete construction of verifiable cloud access control. Specifically, we firstly design a user private key revocable Key Policy Attribute Based Encryption (KP-ABE) scheme with non-monotonic access structure, which can be combined with the XACML policy perfectly. Secondly we convert the XACML policy into the access structure of KP-ABE. Finally we construct a security provable public verifiable cloud access control scheme based on the KP-ABE scheme we designed.