Biblio

The importance and potential advantages with a comprehensive product architecture description are well described in the literature. However, developing such a description takes additional resources, and it is difficult to maintain consistency with evolving implementations. This paper presents an approach and industrial experience which is based on architecture recovery from source code at truck manufacturer Scania CV AB. The extracted representation of the architecture is presented in several views and verified on CAN signal level. Lessons learned are discussed.
 

Feedback loss can severely degrade the overall system performance, in addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications including stochastic and time-critical traffic patterns. Stochastic data has a randomness in its nature which make a great challenge to maintain the real-time control whenever the data is lost. In this paper, we propose a data recovery scheme, called the Efficient Temporal and Spatial Data Recovery (ETSDR) scheme for stochastic incomplete feedback of CPS. In this scheme, we identify the temporal model based on the traffic patterns and consider the spatial effect of the nearest neighbor. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithm regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.
 

Long Term Evolution (LTE) networks designed by 3rd Generation Partnership Project (3GPP) represent a widespread technology. LTE is mainly influenced by high data rates, minimum delay and the capacity due to scalable bandwidth and its flexibility. With the rapid and widespread use LTE networks, and increase the use in data/video transmission and Internet applications in general, accordingly, the challenges of securing and speeding up data communication in such networks is also increased. Authentication in LTE networks is very important process because most of the coming attacks occur during this stage. Attackers try to be authenticated and then launch the network resources and prevent the legitimate users from the network services. The basics of Extensible Authentication Protocol-Authentication and Key Agreement (EAP-AKA) are used in LTE AKA protocol which is called Evolved Packet System AKA (EPS-AKA) protocol to secure LTE network, However it still suffers from various vulnerabilities such as disclosure of the user identity, computational overhead, Man In The Middle (MITM) attack and authentication delay. In this paper, an Efficient EPS-AKA protocol (EEPS-AKA) is proposed to overcome those problems. The proposed protocol is based on the Simple Password Exponential Key Exchange (SPEKE) protocol. Compared to previous proposed methods, our method is faster, since it uses a secret key method which is faster than certificate-based methods, In addition, the size of messages exchanged between User Equipment (UE) and Home Subscriber Server (HSS) is reduced, this reduces authentication delay and storage overhead effectively. The automated validation of internet security protocols and applications (AVISPA) tool is used to provide a formal verification. Results show that the proposed EEPS-AKA is efficient and secure against active and passive attacks.
 

This paper proposes an efficient diagnosis-aware ATPG method that can quickly identify equivalent-fault pairs and generate diagnosis patterns for nonequivalent-fault pairs, where an (non)equivalent-fault pair contains two stuck-at faults that are (not) equivalent. A novel fault injection method is developed which allows one to embed all fault pairs undistinguished by the conventional test patterns into a circuit model with only one copy of the original circuit. Each pair of faults to be processed is transformed to a stuck-at fault and all fault pairs can be dealt with by invoking an ordinary ATPG tool for stuck-at faults just once. High efficiency of diagnosis pattern generation can be achieved due to 1) the circuit to be processed is read only once, 2) the data structure for ATPG process is constructed only once, 3) multiple fault pairs can be processed at a time, and 4) only one copy of the original circuit is needed. Experimental results show that this is the first reported work that can achieve 100% diagnosis resolutions for all ISCAS'89 and IWLS'05 benchmark circuits using an ordinary ATPG tool. Furthermore, we also find that the total number of patterns required to deal with all fault pairs in our method is smaller than that of the current state-of-the-art work.
 

Information technology is continually changing, discoveries are made every other day. Cyber-physical systems consist of both physical and computational elements and are becoming more and more popular in today's society. They are complex systems, used in complex applications. Therefore, security is a critical and challenging aspect when developing cyber-physical systems. In this paper, we present a solution for ensuring data confidentiality and security by combining some of the most common methods in the area of security - cryptography and steganography. Furthermore, we use hierarchical access to information to ensure confidentiality and also increase the overall security of the cyber-physical system.
 

A major issue to secure wireless sensor networks is key distribution. Current key distribution schemes are not fully adapted to the tiny, low-cost, and fragile sensors with limited computation capability, reduced memory size, and battery-based power supply. This paper investigates the design of an efficient key distribution and management scheme for wireless sensor networks. The proposed scheme can ensure the generation and distribution of different encryption keys intended to secure individual and group communications. This is performed based on elliptic curve public key encryption using Diffie-Hellman like key exchange and secret sharing techniques that are applied at different levels of the network topology. This scheme is more efficient and less complex than existing approaches, due to the reduced communication and processing overheads required to accomplish key exchange. Furthermore, few keys with reduced sizes are managed in sensor nodes which optimizes memory usage, and enhances scalability to large size networks.

A smart grid (SG) consists of many subsystems and networks, all working together as a system of systems, many of which are vulnerable and can be attacked remotely. Therefore, security has been identified as one of the most challenging topics in SG development, and designing a mutual authentication scheme and a key management protocol is the first important step. This paper proposes an efficient scheme that mutually authenticates a smart meter of a home area network and an authentication server in SG by utilizing an initial password, by decreasing the number of steps in the secure remote password protocol from five to three and the number of exchanged packets from four to three. Furthermore, we propose an efficient key management protocol based on our enhanced identity-based cryptography for secure SG communications using the public key infrastructure. Our proposed mechanisms are capable of preventing various attacks while reducing the management overhead. The improved efficiency for key management is realized by periodically refreshing all public/private key pairs as well as any multicast keys in all the nodes using only one newly generated function broadcasted by the key generator entity. Security and performance analyses are presented to demonstrate these desirable attributes.

Key management is the core to ensure the communication security of wireless sensor network. How to establish efficient key management in wireless sensor networks (WSN) is a challenging problem for the constrained energy, memory, and computational capabilities of the sensor nodes. Previous research on sensor network security mainly considers homogeneous sensor networks with symmetric key cryptography. Recent researches have shown that using asymmetric key cryptography in heterogeneous sensor networks (HSN) can improve network performance, such as connectivity, resilience, etc. Considering the advantages and disadvantages of symmetric key cryptography and asymmetric key cryptography, the paper propose an efficient and hybrid key management method for heterogeneous wireless sensor network, cluster heads and base stations use public key encryption method based on elliptic curve cryptography (ECC), while using symmetric encryption method between adjacent nodes in the cluster. The analysis and simulation results show that the proposed key management method can provide better security, prefect scalability and connectivity with saving on storage space.

Effective digital identity management system is a critical enabler of cloud computing, since it supports the provision of the required assurances to the transacting parties. Such assurances sometimes require the disclosure of sensitive personal information. Given the prevalence of various forms of identity abuses on the Internet, a re-examination of the factors underlying cloud services acquisition has become critical and imperative. In order to provide better assurances, parties to cloud transactions must have confidence in service providers' ability and integrity in protecting their interest and personal information. Thus a trusted cloud identity ecosystem could promote such user confidence and assurances. Using a qualitative research approach, this paper explains the role of trust in cloud service acquisition by organizations. The paper focuses on the processes of acquisition of cloud services by financial institutions in Ghana. The study forms part of comprehensive study on the monetization of personal Identity information.

Effective digital identity management system is a critical enabler of cloud computing, since it supports the provision of the required assurances to the transacting parties. Such assurances sometimes require the disclosure of sensitive personal information. Given the prevalence of various forms of identity abuses on the Internet, a re-examination of the factors underlying cloud services acquisition has become critical and imperative. In order to provide better assurances, parties to cloud transactions must have confidence in service providers' ability and integrity in protecting their interest and personal information. Thus a trusted cloud identity ecosystem could promote such user confidence and assurances. Using a qualitative research approach, this paper explains the role of trust in cloud service acquisition by organizations. The paper focuses on the processes of acquisition of cloud services by financial institutions in Ghana. The study forms part of comprehensive study on the monetization of personal Identity information.

Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These hashes find extensive applications in content authentication, image indexing for database search and watermarking. Modern robust hashing algorithms consist of feature extraction, a randomization stage to introduce non-invertibility, followed by quantization and binary encoding to produce a binary hash. This paper describes a novel algorithm for generating an image hash based on Log-Polar transform features. The Log-Polar transform is a part of the Fourier-Mellin transformation, often used in image recognition and registration techniques due to its invariant properties to geometric operations. First, we show that the proposed perceptual hash is resistant to content-preserving operations like compression, noise addition, moderate geometric and filtering. Second, we illustrate the discriminative capability of our hash in order to rapidly distinguish between two perceptually different images. Third, we study the security of our method for image authentication purposes. Finally, we show that the proposed hashing method can provide both excellent security and robustness.
 

The secure hash algorithm (SHA)-3 has been selected in 2012 and will be used to provide security to any application which requires hashing, pseudo-random number generation, and integrity checking. This algorithm has been selected based on various benchmarks such as security, performance, and complexity. In this paper, in order to provide reliable architectures for this algorithm, an efficient concurrent error detection scheme for the selected SHA-3 algorithm, i.e., Keccak, is proposed. To the best of our knowledge, effective countermeasures for potential reliability issues in the hardware implementations of this algorithm have not been presented to date. In proposing the error detection approach, our aim is to have acceptable complexity and performance overheads while maintaining high error coverage. In this regard, we present a low-complexity recomputing with rotated operands-based scheme which is a step-forward toward reducing the hardware overhead of the proposed error detection approach. Moreover, we perform injection-based fault simulations and show that the error coverage of close to 100% is derived. Furthermore, we have designed the proposed scheme and through ASIC analysis, it is shown that acceptable complexity and performance overheads are reached. By utilizing the proposed high-performance concurrent error detection scheme, more reliable and robust hardware implementations for the newly-standardized SHA-3 are realized.
 

Hashing algorithms are used extensively in information security and digital forensics applications. This paper presents an efficient parallel algorithm hash computation. It's a modification of the SHA-1 algorithm for faster parallel implementation in applications such as the digital signature and data preservation in digital forensics. The algorithm implements recursive hash to break the chain dependencies of the standard hash function. We discuss the theoretical foundation for the work including the collision probability and the performance implications. The algorithm is implemented using the OpenMP API and experiments performed using machines with multicore processors. The results show a performance gain by more than a factor of 3 when running on the 8-core configuration of the machine.

The detectability of malicious circuitry on FPGAs with varying placement properties yet has to be investigated. The authors utilize a Xilinx Virtex-II Pro target platform in order to insert a sequential denial-of-service Trojan into an existing AES design by manipulating a Xilinx-specific, intermediate file format prior to the bitstream generation. Thereby, there is no need for an attacker to acquire access to the hardware description language representation of a potential target architecture. Using a side-channel analysis setup for electromagnetic emanation (EM) measurements, they evaluate the detectability of different Trojan designs with varying location and logic distribution properties. The authors successfully distinguish the malicious from the genuine designs and provide information on how the location and distribution properties of the Trojan logic affect its detectability. To the best of their knowledge, this has been the first practically conducted Trojan detection using localized EM measurements.
 

The modular exponentiation is an important operation for cryptographic transformations in public key cryptosystems like the Rivest, Shamir and Adleman, the Difie and Hellman and the ElGamal schemes. computing ax mod n and axby mod n for very large x,y and n are fundamental to the efficiency of almost all pubic key cryptosystems and digital signature schemes. To achieve high level of security, the word length in the modular exponentiations should be significantly large. The performance of public key cryptography is primarily determined by the implementation efficiency of the modular multiplication and exponentiation. As the words are usually large, and in order to optimize the time taken by these operations, it is essential to minimize the number of modular multiplications. In this paper we are presenting efficient algorithms for computing ax mod n and axbymod n. In this work we propose four algorithms to evaluate modular exponentiation. Bit forwarding (BFW) algorithms to compute ax mod n, and to compute axby mod n two algorithms namely Substitute and reward (SRW), Store and forward(SFW) are proposed. All the proposed algorithms are efficient in terms of time and at the same time demands only minimal additional space to store the pre-computed values. These algorithms are suitable for devices with low computational power and limited storage.
 

Hashing algorithms are used extensively in information security and digital forensics applications. This paper presents an efficient parallel algorithm hash computation. It's a modification of the SHA-1 algorithm for faster parallel implementation in applications such as the digital signature and data preservation in digital forensics. The algorithm implements recursive hash to break the chain dependencies of the standard hash function. We discuss the theoretical foundation for the work including the collision probability and the performance implications. The algorithm is implemented using the OpenMP API and experiments performed using machines with multicore processors. The results show a performance gain by more than a factor of 3 when running on the 8-core configuration of the machine.
 

Educators and sponsors endorse competitions as a strong, positive influence on career choice. However, empirical studies of cybersecurity competitions are lacking, and evidence from computer science and mathematics competitions has been mixed. Here we report initial results from an ongoing study of the National Cyber League to provide a glimpse of the role of competitions in fostering cybersecurity career engagement. Preliminary results suggest that cyber competitions attract experienced individuals who will remain in the profession for the long-term, but future research is needed to understand how cyber competitions may engage women and those new to the field.

The Domain Name System (DNS) is widely seen as a vital protocol of the modern Internet. For example, popular services like load balancers and Content Delivery Networks heavily rely on DNS. Because of its important role, DNS is also a desirable target for malicious activities such as spamming, phishing, and botnets. To protect networks against these attacks, a number of DNS-based security approaches have been proposed. The key insight of our study is to measure the effectiveness of security approaches that rely on DNS in large-scale networks. For this purpose, we answer the following questions, How often is DNS used? Are most of the Internet flows established after contacting DNS? In this study, we collected data from the University of Auckland campus network with more than 33,000 Internet users and processed it to find out how DNS is being used. Moreover, we studied the flows that were established with and without contacting DNS. Our results show that less than 5 percent of the observed flows use DNS. Therefore, we argue that those security approaches that solely depend on DNS are not sufficient to protect large-scale networks.

Botnet detection represents one of the most crucial prerequisites of successful botnet neutralization. This paper explores how accurate and timely detection can be achieved by using supervised machine learning as the tool of inferring about malicious botnet traffic. In order to do so, the paper introduces a novel flow-based detection system that relies on supervised machine learning for identifying botnet network traffic. For use in the system we consider eight highly regarded machine learning algorithms, indicating the best performing one. Furthermore, the paper evaluates how much traffic needs to be observed per flow in order to capture the patterns of malicious traffic. The proposed system has been tested through the series of experiments using traffic traces originating from two well-known P2P botnets and diverse non-malicious applications. The results of experiments indicate that the system is able to accurately and timely detect botnet traffic using purely flow-based traffic analysis and supervised machine learning. Additionally, the results show that in order to achieve accurate detection traffic flows need to be monitored for only a limited time period and number of packets per flow. This indicates a strong potential of using the proposed approach within a future on-line detection framework.

This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the γ-filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and electroencephalographic time series prediction, complex nonlinear system identification, and adaptive antenna array processing demonstrate the potential of the approach for scenarios where recursivity and nonlinearity have to be readily combined.

Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques.
 

The University of Illinois at Urbana Champaign (Illinois), Pacific Northwest National Labs (PNNL), and the University of Southern California Information Sciences Institute (USC-ISI) consortium is working toward providing tools and expertise to enable collaborative research to improve security and resiliency of cyber physical systems. In this extended abstract we discuss the challenges and the solution space. We demonstrate the feasibility of some of the proposed components through a wide-area situational awareness experiment for the power grid across the three sites.
 

Persisting to ignore the consequences of Cyber Warfare will bring severe concerns to all people. Hackers and governments alike should understand the barriers of which their methods take them. Governments use Cyber Warfare to give them a tactical advantage over other countries, defend themselves from their enemies or to inflict damage upon their adversaries. Hackers use Cyber Warfare to gain personal information, commit crimes, or to reveal sensitive and beneficial intelligence. Although both methods can provide ethical uses, the equivalent can be said at the other end of the spectrum. Knowing and comprehending these devices will not only strengthen the ability to detect these attacks and combat against them but will also provide means to divulge despotic government plans, as the outcome of Cyber Warfare can be worse than the outcome of conventional warfare. The paper discussed the concept of ethics and reasons that led to use information technology in military war, the effects of using cyber war on civilians, the legality of the cyber war and ways of controlling the use of information technology that may be used against civilians. This research uses a survey methodology to overlook the awareness of Arab citizens towards the idea of cyber war, provide findings and evidences of ethics behind the offensive cyber warfare. Detailed strategies and approaches should be developed in this aspect. The author recommended urging the scientific and technological research centers to improve the security and develop defending systems to prevent the use of technology in military war against civilians.
 

Efficient and secure search on encrypted data is an important problem in computer science. Users having large amount of data or information in multiple documents face problems with their storage and security. Cloud services have also become popular due to reduction in cost of storage and flexibility of use. But there is risk of data loss, misuse and theft. Reliability and security of data stored in the cloud is a matter of concern, specifically for critical applications and ones for which security and privacy of the data is important. Cryptographic techniques provide solutions for preserving the confidentiality of data but make the data unusable for many applications. In this paper we report a novel approach to securely store the data on a remote location and perform search in constant time without the need for decryption of documents. We use bloom filters to perform simple as well advanced search operations like case sensitive search, sentence search and approximate search.
 

Port hopping is a typical moving target defense, which constantly changes service port number to thwart reconnaissance attack. It is effective in hiding service identities and confusing potential attackers, but it is still unknown how effective port hopping is and under what circumstances it is a viable proactive defense because the existed works are limited and they usually discuss only a few parameters and give some empirical studies. This paper introduces urn model and quantifies the likelihood of attacker success in terms of the port pool size, number of probes, number of vulnerable services, and hopping frequency. Theoretical analysis shows that port hopping is an effective and promising proactive defense technology in thwarting network attacks.