Biblio

In networked systems, monitoring devices such as sensors are typically deployed to monitor various target locations. Targets are the points in the physical space at which events of some interest, such as random faults or attacks, can occur. Most often, these devices have limited energy supplies, and they can operate for a limited duration. As a result, energyefficient monitoring of various target locations through a set of monitoring devices with limited energy supplies is a crucial problem in networked systems. In this paper, we study optimal scheduling of monitoring devices to maximize network coverage for detecting and isolating events on targets for a given network lifetime. The monitoring devices considered could remain active only for a fraction of the overall network lifetime. We formulate the problem of scheduling of monitoring devices as a graph labeling problem, which unlike other existing solutions, allows us to directly utilize the underlying network structure to explore the trade-off between coverage and network lifetime. In this direction, first we propose a greedy heuristic to solve the graph labeling problem, and then provide a game-theoretic solution to achieve optimal graph labeling. Moreover, the proposed setup can be used to simultaneously solve the scheduling and placement of monitoring devices, which yields improved performance as compared to separately solving the placement and scheduling problems. Finally, we illustrate our results on various networks, including real-world water distribution networks.

Web servers use SSL/TLS to establish secure communication between clients and servers. The mechanism of SSL/TLS relies on a key pair to validate the server and to protect the confidentiality of the data. However, many websites are running on third-party servers or on cloud environments where website owners have no control over the physical servers or the software including the operating systems but still need to trust and store the private key on the servers. While it is common to store the encrypted key on the disk, the web server still need a decrypted key inside the memory during the operation. Thus, an adversary could obtain the private key residing on the web server's memory. In this paper, we propose a secure enclave for a web server running the high privilege code that handles the secret keys inside an encrypted memory area by utilizing Intel Software Guard Extension (SGX) whereas other components of the web server outside the trusted computing base are left intact. The experimental results show 19% to 38% implementation overhead depending on which cipher suite is used and how a session key is handled.

In this work, we analyze the feasibility of a physically secure implementation of the quantum-resistant supersingular isogeny Diffie-Hellman (SIDH) protocol. Notably, we analyze the defense against timing attacks, simple power analysis, differential power analysis, and fault attacks. Luckily, the SIDH protocol closely resembles its predecessor, the elliptic curve Diffie-Hellman (ECDH) key exchange. As such, much of the extensive literature in side-channel analysis can also apply to SIDH. In particular, we focus on a hardware implementation that features a true random number generator, ALU, and controller. SIDH is composed of two rounds containing a double-point multiplication to generate a secret kernel point and an isogeny over that kernel to arrive at a new elliptic curve isomorphism. To protect against simple power analysis and timing attacks, we recommend a constant-time implementation with Fermat's little theorem inversion. Differential power analysis targets the power output of the SIDH core over many runs. As such, we recommend scaling the base points by secret scalars so that each iteration has a unique power signature. Further, based on recent oracle attacks on SIDH, we cannot recommend the use of static keys from both parties. The goal of this paper is to analyze the tradeoffs in elliptic curve theory to produce a cryptographically and physically secure implementation of SIDH.

A Software-Defined Wireless Sensor Network (SD-WSN) is a recently developed model which is expected to play a large role not only in the development of the Internet of Things (IoT) paradigm but also as a platform for other applications such as smart water management. This model makes use of a Software-Defined Networking (SDN) approach to manage a Wireless Sensor Network (WSN) in order to solve most of the inherent issues surrounding WSNs. One of the most important aspects of any network, is security. This is an area that has received little attention within the development of SDWSNs, as most research addresses security concerns within SDN and WSNs independently. There is a need for research into the security of SDWSN. Some concepts from both SDN and WSN security can be adjusted to suit the SDWSN model while others cannot. Further research is needed into consolidating SDN and WSN security measures to consider security in SDWSN. Threats, challenges and potential solutions to securing SDWSN are presented by considering both the WSN and SDN paradigms.

Deduplication removes redundant copies of files or data blocks stored on the cloud. Client-side deduplication, where the client only uploads the file upon the request of the server, provides major storage and bandwidth savings, but introduces a number of security concerns. Harnik et al. (2010) showed how cross-user client-side deduplication inherently gives the adversary access to a (noisy) side-channel that may divulge whether or not a particular file is stored on the server, leading to leakage of user information. We provide formal definitions for deduplication strategies and their security in terms of adversarial advantage. Using these definitions, we provide a criterion for designing good strategies and then prove a bound characterizing the necessary trade-off between security and efficiency.

Nonverbal cues are considered the most important part in social communication. Many people desire people; but due to the stigma and unavailability of resources, they are unable to practice their social skills. In this work, we envision a virtual assistant that can give individuals real-time feedback on their smiles, eye-contact, body language and volume modulation that is available anytime, anywhere using a computer browser. To instantiate our idea, we have set up a Wizard-of-Oz study in the context of speed-dating with 47 individuals. We collected videos of the participants having a conversation with a virtual agent before and after of a speed-dating session. This study revealed that the participants who used our system improved their gesture in a face-to-face conversation. Our next goal is to explore different machine learning techniques on the facial and prosodic features to automatically generate feedback on the nonverbal cues. In addition, we want to explore different strategies of conveying real-time feedback that is non-threatening, repeatable, objective and more likely to transfer to a real-world conversation.

SDN (Software Defined Network) separates control plane from data plane (forwarding plane) which leads programmability of network and scalability, flexibility of existed network. nevertheless, the reason that security requirements had never considered during the initial design of SDN brought various security issues. And this security issues includes vulnerabilities (such as unauthorized access, data modification and leakage) and attacks (for example, DoS (Denial of Service) and MIITM (Main-in-the-Middle attack)). In this paper, we proposed SEaaS (Security as a Service) which can provide security within SDN environment. Also, we suggest authentication mechanism between application and controller among the various services of SEaaS.

Subliminal channels in digital signatures provide a very effective method to clandestinely leak information from inside a system to a third party outside. Information can be hidden in signature parameters in a way that both network operators and legitimate receivers would not notice any suspicious traces. Subliminal channels have previously been discovered in other signatures, such as ElGamal and ECDSA. Those signatures are usually just sparsely exchanged in network protocols, e.g. during authentication, and their usability for leaking information is therefore limited. With the advent of high-speed signatures such as EdDSA, however, scenarios become feasible where numerous packets with individual signatures are transferred between communicating parties. This significantly increases the bandwidth for transmitting subliminal information. Examples are broadcast clock synchronization or signed sensor data export. A subliminal channel in signatures appended to numerous packets allows the transmission of a high amount of hidden information, suitable for large scale data exfiltration or even the operation of command and control structures. In this paper, we show the existence of a broadband subliminal channel in the EdDSA signature scheme. We then discuss the implications of the subliminal channel in practice using thee different scenarios: broadcast clock synchronization, signed sensor data export, and classic TLS. We perform several experiments to show the use of the subliminal channel and measure the actual bandwidth of the subliminal information that can be leaked. We then discuss the applicability of different countermeasures against subliminal channels from other signature schemes to EdDSA but conclude that none of the existing solutions can sufficiently protect against data exfiltration in network protocols secured by EdDSA.

This paper investigates the trade-off between security and usability in recognition-based graphical authentication mechanisms. Through a user study (N=103) based on a real usage scenario, it draws insights about the security strength and memorability of a chosen password with respect to the amount of images presented to users during sign-up. In particular, it reveals the users' predisposition in following predictable patterns when selecting graphical passwords, and its effect on practical security strength. It also demonstrates that a "sweet-spot" exists between security and usability in graphical authentication approaches on the basis of adjusting accordingly the image grid size presented to users when creating passwords. The results of the study can be leveraged by researchers and practitioners engaged in designing intelligent graphical authentication user interfaces for striking an appropriate balance between security and usability.

The Internet of Things (IoT) creates value by connecting digital processes to the physical world using embedded sensors, actuators and wireless networks. The IoT is increasingly intertwined with critical industrial processes, yet contemporary IoT devices offer limited security features, creating a large new attack surface and inhibiting the adoption of IoT technologies. Hardware security modules address this problem, however, their use increases the cost of embedded IoT devices. Furthermore, millions of IoT devices are already deployed without hardware security support. This paper addresses this problem by introducing a Security MicroVisor (SμV) middleware, which provides memory isolation and custom security operations using software virtualisation and assembly-level code verification. We showcase SμV by implementing a key security feature: remote attestation. Evaluation shows extremely low overhead in terms of memory, performance and battery lifetime for a representative IoT device.

Ensuring the reliability of applications is becoming an increasingly important challenge as high-performance computing (HPC) systems experience an ever-growing number of faults, errors and failures. While the HPC community has made substantial progress in developing various resilience solutions, it continues to rely on platform-based metrics to quantify application resiliency improvements. The resilience of an HPC application is concerned with the reliability of the application outcome as well as the fault handling efficiency. To understand the scope of impact, effective coverage and performance efficiency of existing and emerging resilience solutions, there is a need for new metrics. In this paper, we develop new ways to quantify resilience that consider both the reliability and the performance characteristics of the solutions from the perspective of HPC applications. As HPC systems continue to evolve in terms of scale and complexity, it is expected that applications will experience various types of faults, errors and failures, which will require applications to apply multiple resilience solutions across the system stack. The proposed metrics are intended to be useful for understanding the combined impact of these solutions on an application's ability to produce correct results and to evaluate their overall impact on an application's performance in the presence of various modes of faults.

Current threat models typically consider all possible ways an attacker can penetrate a system and assign probabilities to each path according to some metric (e.g. time-to-compromise). In this paper we discuss how this view hinders the realness of both technical (e.g. attack graphs) and strategic (e.g. game theory) approaches of current threat modeling, and propose to steer away by looking more carefully at attack characteristics and attacker environment. We use a toy threat model for ICS attacks to show how a realistic view of attack instances can emerge from a simple analysis of attack phases and attacker limitations.

Combining Error-Correction Coding ECC and cryptography was proposed in the recent decade making use of bit-quality parameters to improve the error correction capability. Most of such techniques combine authentication crypto-functions jointly with ECC codes to improve system reliability, while fewer proposals involve ciphering functions with ECC to improve reliability. In this work, we propose practical and pragmatic low-cost approaches for making use of existing ciphering functions for reliability improvement. The presented techniques show that ciphering functions (as deterministic, non-linear bijective functions) can serve to achieve error correction enhancement and hence allow error recovery and scalable security trade-offs with or without additional ECC components. We demonstrate two best-effort error-correcting strategies. It is further shown, that the targeted reliability improvement is scalable to attain practical usability. The first proposed technique is pure-cipher-based error correction procedure deploying hard decision, best-effort operations to improve the system-survivability without changing system configuration. The second strategy is making use of ECC in combination with the ciphering function to enhance system-survivability. The correction procedures are based on simple experimental search-and-modify the corrupted ciphertext until predefined criteria become valid. This procedure may, however, turn out to become equivalent to a successful integrity/authenticity attack that may reduce the system security level, however in a scalable and predictable non-significant fashion.

We have formalized the functional specification of HMAC-DRBG (NIST 800-90A), and we have proved its cryptographic security-that its output is pseudorandom–using a hybrid game-based proof. We have also proved that the mbedTLS implementation (C program) correctly implements this functional specification. That proof composes with an existing C compiler correctness proof to guarantee, end-to-end, that the machine language program gives strong pseudorandomness. All proofs (hybrid games, C program verification, compiler, and their composition) are machine-checked in the Coq proof assistant. Our proofs are modular: the hybrid game proof holds on any implementation of HMAC-DRBG that satisfies our functional specification. Therefore, our functional specification can serve as a high-assurance reference.

Differential privacy is an approach that preserves patient privacy while permitting researchers access to medical data. This paper presents mechanisms proposed to satisfy differential privacy while answering a given workload of range queries. Representing input data as a vector of counts, these methods partition the vector according to relationships between the data and the ranges of the given queries. After partitioning the vector into buckets, the counts of each bucket are estimated privately and split among the bucket's positions to answer the given query set. The performance of the proposed method was evaluated using different workloads over several attributes. The results show that partitioning the vector based on the data can produce more accurate answers, while partitioning the vector based on the given workload improves privacy. This paper's two main contributions are: (1) improving earlier work on partitioning mechanisms by building a greedy algorithm to partition the counts' vector efficiently, and (2) its adaptive algorithm considers the sensitivity of the given queries before providing results.

Phishing is referred as an attempt to obtain sensitive information, such as usernames, passwords, and credit card details (and, indirectly, money), for malicious reasons, by disguising as a trustworthy entity in an electronic communication [1]. Hackers and malicious users, often use Emails as phishing tools to obtain the personal data of legitimate users, by sending Emails with authentic identities, legitimate content, but also with malicious URL, which help them to steal consumer's data. The high dimensional data in phishing context contains large number of redundant features that significantly elevate the classification error. Additionally, the time required to perform classification increases with the number of features. So extracting complex Features from phishing Emails requires us to determine which Features are relevant and fundamental in phishing detection. The dominant approaches in phishing are based on machine learning techniques; these rely on manual feature engineering, which is time consuming. On the other hand, deep learning is a promising alternative to traditional methods. The main idea of deep learning techniques is to learn complex features extracted from data with minimum external contribution [2]. In this paper, we propose new phishing detection and prevention approach, based first on our previous spam filter [3] to classify textual content of Email. Secondly it's based on Autoencoder and on Denoising Autoencoder (DAE), to extract relevant and robust features set of URL (to which the website is actually directed), therefore the features space could be reduced considerably, and thus decreasing the phishing detection time.

We study the notion of stability and perturbation resilience introduced by Bilu and Linial (2010) and Awasthi, Blum, and Sheffet (2012). A combinatorial optimization problem is α-stable or α-perturbation-resilient if the optimal solution does not change when we perturb all parameters of the problem by a factor of at most α. In this paper, we give improved algorithms for stable instances of various clustering and combinatorial optimization problems. We also prove several hardness results. We first give an exact algorithm for 2-perturbation resilient instances of clustering problems with natural center-based objectives. The class of clustering problems with natural center-based objectives includes such problems as k-means, k-median, and k-center. Our result improves upon the result of Balcan and Liang (2016), who gave an algorithm for clustering 1+√2≈2.41 perturbation-resilient instances. Our result is tight in the sense that no polynomial-time algorithm can solve (2−ε)-perturbation resilient instances of k-center unless NP = RP, as was shown by Balcan, Haghtalab, and White (2016). We then give an exact algorithm for (2−2/k)-stable instances of Minimum Multiway Cut with k terminals, improving the previous result of Makarychev, Makarychev, and Vijayaraghavan (2014), who gave an algorithm for 4-stable instances. We also give an algorithm for (2−2/k+δ)-weakly stable instances of Minimum Multiway Cut. Finally, we show that there are no robust polynomial-time algorithms for n1−ε-stable instances of Set Cover, Minimum Vertex Cover, and Min 2-Horn Deletion (unless P = NP).

Security protection is a concern for the Internet of Things (IoT) which performs data exchange autonomously over the internet for remote monitoring, automation and other applications. IoT implementations has raised concerns over its security and various research has been conducted to find an effective solution for this. Thus, this work focus on the analysis of an asymmetric encryption scheme, AA-Beta (AAβ) on a platform constrained in terms of processor capability, storage and random access Memory (RAM). For this work, the platform focused is ARM Cortex-M7 microcontroller. The encryption and decryption's performance on the embedded microcontroller is realized and time executed is measured. By enabled the I-Cache (Instruction cache) and D-Cache (Data Cache), the performances are 50% faster compared to disabled the D-Cache and I-Cache. The performance is then compared to our previous work on System on Chip (SoC). This is to analyze the gap of the SoC that has utilized the full GNU Multiple Precision Arithmetic Library (GMP) package versus ARM Cortex-M7 that using the mini-gmp package in term of the footprint and the actual performance.

The collection of high frequency metering data in the emerging smart grid gives rise to the concern of consumer privacy. Anonymization of metering data is one of the proposed approaches in the literature, which enables transmission of unmasked data while preserving the privacy of the sender. Distributed anonymization methods can reduce the dependency on service providers, thus promising more privacy for the consumers. However, the distributed communication among the end-users introduces overhead and requires methods to prevent external attacks. In this paper, we propose four variants of a distributed anonymization method for smart metering data privacy, referred to as the Collaborative Anonymity Set Formation (CASF) method. The performance overhead analysis and security analysis of the variants are done using NS-3 simulator and the Scyther tool, respectively. It is shown that the proposed scheme enhances the privacy preservation functionality of an existing anonymization scheme, while being robust against external attacks.

Industrial networking has many issues based on the type of industries, data storage, data centers, and cloud computing, etc. Green data storage improves the scientific, commercial and industrial profile of the networking. Future industries are looking for cybersecurity solution with the low-cost resources in which the energy serving is the main problem in the industrial networking. To improve these problems, green data storage will be the priority because data centers and cloud computing deals with the data storage. In this analysis, we have decided to use solar energy source and different light rays as methodologies include a prism and the Li-Fi techniques. In this approach, light rays sent through the prism which allows us to transmit the data with different frequencies. This approach provides green energy and maximum protection within the data center. As a result, we have illustrated that cloud services within the green data center in industrial networking will achieve better protection with the low-cost energy through this analysis. Finally, we have to conclude that Li-Fi enhances the use of green energy and protection which are advantages to current and future industrial networking.

Guidelines, directives, and policy statements are usually presented in ``linear'' text form - word after word, page after page. However necessary, this practice impedes full understanding, obscures feedback dynamics, hides mutual dependencies and cascading effects and the like, - even when augmented with tables and diagrams. The net result is often a checklist response as an end in itself. All this creates barriers to intended realization of guidelines and undermines potential effectiveness. We present a solution strategy using text as ``data'', transforming text into a structured model, and generate a network views of the text(s), that we then can use for vulnerability mapping, risk assessments and control point analysis. We apply this approach using two NIST reports on cybersecurity of smart grid, more than 600 pages of text. Here we provide a synopsis of approach, methods, and tools. (Elsewhere we consider (a) system-wide level, (b) aviation e-landscape, (c) electric vehicles, and (d) SCADA for smart grid).

Integration of information technologies with the current power infrastructure promises something further than a smart grid: implementation of smart cities. Power efficient cities will be a significant step toward greener cities and a cleaner environment. However, the extensive use of information technologies in smart cities comes at a cost of reduced privacy. In particular, consumers' power profiles will be accessible by third parties seeking information over consumers' personal habits. In this paper, a methodology for enhancing privacy of electricity consumption patterns is proposed and tested. The proposed method exploits digital connectivity and predictive tools offered via smart grids to morph consumption patterns by grouping consumers via an optimization scheme. To that end, load anticipation, correlation and Theil coefficients are utilized synergistically with genetic algorithms to find an optimal assembly of consumers whose aggregated pattern hides individual consumption features. Results highlight the efficiency of the proposed method in enhancing privacy in the environment of smart cities.

Due to the growing performance requirements, embedded systems are increasingly more complex. Meanwhile, they are also expected to be reliable. Guaranteeing reliability on complex systems is very challenging. Consequently, there is a substantial need for designs that enable the use of unverified components such as real-time operating system (RTOS) without requiring their correctness to guarantee safety. In this work, we propose a novel approach to design a controller that enables the system to restart and remain safe during and after the restart. Complementing this controller with a switching logic allows the system to use complex, unverified controller to drive the system as long as it does not jeopardize safety. Such a design also tolerates faults that occur in the underlying software layers such as RTOS and middleware and recovers from them through system-level restarts that reinitialize the software (middleware, RTOS, and applications) from a read-only storage. Our approach is implementable using one commercial off-the-shelf (COTS) processing unit. To demonstrate the efficacy of our solution, we fully implement a controller for a 3 degree of freedom (3DOF) helicopter. We test the system by injecting various types of faults into the applications and RTOS and verify that the system remains safe.

Predict software program reliability turns into a completely huge trouble in these days. Ordinary many new software programs are introducing inside the marketplace and some of them dealing with failures as their usage/managing is very hard. and plenty of shrewd strategies are already used to are expecting software program reliability. In this paper we're giving a sensible knowledge and the difference among those techniques with my new method. As a result, the prediction fashions constructed on one dataset display a extensive decrease in their accuracy when they are used with new statistics. The aim of this assessment, SE issues which can be of sensible importance are software development/cost estimation, software program reliability prediction, and so forth, and also computing its broaden computational equipment with enhanced power, scalability, flexibility and that can engage more successfully with human beings.