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Guerrini, F., Dalai, M., Leonardi, R..  2020.  Minimal Information Exchange for Secure Image Hash-Based Geometric Transformations Estimation. IEEE Transactions on Information Forensics and Security. 15:3482—3496.
Signal processing applications dealing with secure transmission are enjoying increasing attention lately. This paper provides some theoretical insights as well as a practical solution for transmitting a hash of an image to a central server to be compared with a reference image. The proposed solution employs a rigid image registration technique viewed in a distributed source coding perspective. In essence, it embodies a phase encoding framework to let the decoder estimate the transformation parameters using a very modest amount of information about the original image. The problem is first cast in an ideal setting and then it is solved in a realistic scenario, giving more prominence to low computational complexity in both the transmitter and receiver, minimal hash size, and hash security. Satisfactory experimental results are reported on a standard images set.
Agirre, I..  2020.  Safe and secure software updates on high-performance embedded systems. 2020 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W). :68—69.

The next generation of dependable embedded systems feature autonomy and higher levels of interconnection. Autonomy is commonly achieved with the support of artificial intelligence algorithms that pose high computing demands on the hardware platform, reaching a high performance scale. This involves a dramatic increase in software and hardware complexity, fact that together with the novelty of the technology, raises serious concerns regarding system dependability. Traditional approaches for certification require to demonstrate that the system will be acceptably safe to operate before it is deployed into service. The nature of autonomous systems, with potentially infinite scenarios, configurations and unanticipated interactions, makes it increasingly difficult to support such claim at design time. In this context, the extended networking technologies can be exploited to collect post-deployment evidence that serve to oversee whether safety assumptions are preserved during operation and to continuously improve the system through regular software updates. These software updates are not only convenient for critical bug fixing but also necessary for keeping the interconnected system resilient against security threats. However, such approach requires a recondition of the traditional certification practices.

Meshram, C., Obaidat, M. S., Meshram, A..  2020.  New Efficient QERPKC based on Partial Discrete Logarithm Problem. 2020 International Conference on Computer, Information and Telecommunication Systems (CITS). :1–5.
In this study, our aim is to extend the scope for public key cryptography. We offered a new efficient public key encryption scheme using partial discrete logarithm problem (PDLP). It is known as the Quadratic Exponentiation Randomized Public Key Cryptosystem (QERPKC). Security of the presented scheme is based on the hardness of PDLP. We reflect the safety in contrast to trick of certain elements in the offered structure and demonstrated the prospect of creating an extra safety structure. The presented new efficient QERPKC structure is appropriate for low-bandwidth communication, low-storage and low-computation environments.
Xiong, J., Zhang, L..  2020.  Simplified Calculation of Bhattacharyya Parameters in Polar Codes. 2020 IEEE 14th International Conference on Anti-counterfeiting, Security, and Identification (ASID). :169–173.
The construction of polar code refers to selecting K "most reliable polarizing channels" in N polarizing channels to WN(1)transmit information bits. For non-systematic polar code, Arikan proposed a method to measure the channel reliability for BEC channel, which is called Bhattacharyya Parameter method. The calculated complexity of this method is O(N) . In this paper, we find the complementarity of Bhattacharyya Parameter. According to the complementarity, the code construction under a certain channel condition can be quickly deduced from the complementary channel condition.
Algehed, M., Flanagan, C..  2020.  Transparent IFC Enforcement: Possibility and (In)Efficiency Results. 2020 IEEE 33rd Computer Security Foundations Symposium (CSF). :65—78.

Information Flow Control (IFC) is a collection of techniques for ensuring a no-write-down no-read-up style security policy known as noninterference. Traditional methods for both static (e.g. type systems) and dynamic (e.g. runtime monitors) IFC suffer from untenable numbers of false alarms on real-world programs. Secure Multi-Execution (SME) promises to provide secure information flow control without modifying the behaviour of already secure programs, a property commonly referred to as transparency. Implementations of SME exist for the web in the form of the FlowFox browser and as plug-ins to several programming languages. Furthermore, SME can in theory work in a black-box manner, meaning that it can be programming language agnostic, making it perfect for securing legacy or third-party systems. As such SME, and its variants like Multiple Facets (MF) and Faceted Secure Multi-Execution (FSME), appear to be a family of panaceas for the security engineer. The question is, how come, given all these advantages, that these techniques are not ubiquitous in practice? The answer lies, partially, in the issue of runtime and memory overhead. SME and its variants are prohibitively expensive to deploy in many non-trivial situations. The natural question is why is this the case? On the surface, the reason is simple. The techniques in the SME family all rely on the idea of multi-execution, running all or parts of a program multiple times to achieve noninterference. Naturally, this causes some overhead. However, the predominant thinking in the IFC community has been that these overheads can be overcome. In this paper we argue that there are fundamental reasons to expect this not to be the case and prove two key theorems: (1) All transparent enforcement is polynomial time equivalent to multi-execution. (2) All black-box enforcement takes time exponential in the number of principals in the security lattice. Our methods also allow us to answer, in the affirmative, an open question about the possibility of secure and transparent enforcement of a security condition known as Termination Insensitive Noninterference.

Zhang, Z., Li, N., Xia, S., Tao, X..  2020.  Fast Cross Layer Authentication Scheme for Dynamic Wireless Network. 2020 IEEE Wireless Communications and Networking Conference (WCNC). :1—6.
Current physical layer authentication (PLA) mechanisms are mostly designed for static communications, and the accuracy degrades significantly when used in dynamic scenarios, where the network environments and wireless channels change frequently. To improve the authentication performance, it is necessary to update the hypothesis test models and parameters in time, which however brings high computational complexity and authentication delay. In this paper, we propose a lightweight cross-layer authentication scheme for dynamic communication scenarios. We use multiple characteristics based PLA to guarantee the reliability and accuracy of authentication, and propose an upper layer assisted method to ensure the performance stability. Specifically, upper layer authentication (ULA) helps to update the PLA models and parameters. By properly choosing the period of triggering ULA, a balance between complexity and performance can be easily obtained. Simulation results show that our scheme can achieve pretty good authentication performance with reduced complexity.
Omori, T., Isono, Y., Kondo, K., Akamine, Y., Kidera, S..  2020.  k-Space Decomposition Based Super-resolution Three-dimensional Imaging Method for Millimeter Wave Radar. 2020 IEEE Radar Conference (RadarConf20). :1–6.
Millimeter wave imaging radar is indispensible for collision avoidance of self-driving system, especially in optically blurred visions. The range points migration (RPM) is one of the most promising imaging algorithms, which provides a number of advantages from synthetic aperture radar (SAR), in terms of accuracy, computational complexity, and potential for multifunctional imaging. The inherent problem in the RPM is that it suffers from lower angular resolution in narrower frequency band even if higher frequency e.g. millimeter wave, signal is exploited. To address this problem, the k-space decomposition based RPM has been developed. This paper focuses on the experimental validation of this method using the X-band or millimeter wave radar system, and demonstrated that our method significantly enhances the reconstruction accuracy in three-dimensional images for the two simple spheres and realistic vehicle targets.
Kubba, Z. M. Jawad, Hoomod, H. K..  2019.  A Hybrid Modified Lightweight Algorithm Combined of Two Cryptography Algorithms PRESENT and Salsa20 Using Chaotic System. 2019 First International Conference of Computer and Applied Sciences (CAS). :199–203.

Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterises the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is applied to generate pseudo-random keys that produce more complexity for the proposed cipher algorithm. The goal of the proposed algorithm is to present a hybrid algorithm by enhancing the complexity of the current PRESENT algorithm while keeping the performance of computational operations as minimal. The proposed algorithm proved working efficiently with fast executed time, and the analysed result of the generated sequence keys passed the randomness of the NIST suite.

Wehbe, R., Williams, R. K..  2019.  Approximate Probabilistic Security for Networked Multi-Robot Systems. 2019 International Conference on Robotics and Automation (ICRA). :1997—2003.

In this paper, we formulate a combinatorial optimization problem that aims to maximize the accuracy of a lower bound estimate of the probability of security of a multi-robot system (MRS), while minimizing the computational complexity involved in its calculation. Security of an MRS is defined using the well-known control theoretic notion of left invertiblility, and the probability of security of an MRS can be calculated using binary decision diagrams (BDDs). The complexity of a BDD depends on the number of disjoint path sets considered during its construction. Taking into account all possible disjoint paths results in an exact probability of security, however, selecting an optimal subset of disjoint paths leads to a good estimate of the probability while significantly reducing computation. To deal with the dynamic nature of MRSs, we introduce two methods: (1) multi-point optimization, a technique that requires some a priori knowledge of the topology of the MRS over time, and (2) online optimization, a technique that does not require a priori knowledge, but must construct BDDs while the MRS is operating. Finally, our approach is validated on an MRS performing a rendezvous objective while exchanging information according to a noisy state agreement process.

Chen, Z., Jia, Z., Wang, Z., Jafar, S. A..  2020.  GCSA Codes with Noise Alignment for Secure Coded Multi-Party Batch Matrix Multiplication. 2020 IEEE International Symposium on Information Theory (ISIT). :227—232.

A secure multi-party batch matrix multiplication problem (SMBMM) is considered, where the goal is to allow a master to efficiently compute the pairwise products of two batches of massive matrices, by distributing the computation across S servers. Any X colluding servers gain no information about the input, and the master gains no additional information about the input beyond the product. A solution called Generalized Cross Subspace Alignment codes with Noise Alignment (GCSA- NA) is proposed in this work, based on cross-subspace alignment codes. The state of art solution to SMBMM is a coding scheme called polynomial sharing (PS) that was proposed by Nodehi and Maddah-Ali. GCSA-NA outperforms PS codes in several key aspects - more efficient and secure inter-server communication, lower latency, flexible inter-server network topology, efficient batch processing, and tolerance to stragglers.

Zhou, J.-L., Wang, J.-S., Zhang, Y.-X., Guo, Q.-S., Li, H., Lu, Y.-X..  2020.  Particle Swarm Optimization Algorithm with Variety Inertia Weights to Solve Unequal Area Facility Layout Problem. 2020 Chinese Control And Decision Conference (CCDC). :4240–4245.
The unequal area facility layout problem (UA-FLP) is to place some objects in a specified space according to certain requirements, which is a NP-hard problem in mathematics because of the complexity of its solution, the combination explosion and the complexity of engineering system. Particle swarm optimization (PSO) algorithm is a kind of swarm intelligence algorithm by simulating the predatory behavior of birds. Aiming at the minimization of material handling cost and the maximization of workshop area utilization, the optimization mathematical model of UA-FLPP is established, and it is solved by the particle swarm optimization (PSO) algorithm which simulates the design of birds' predation behavior. The improved PSO algorithm is constructed by using nonlinear inertia weight, dynamic inertia weight and other methods to solve static unequal area facility layout problem. The effectiveness of the proposed method is verified by simulation experiments.
Phu, T. N., Hoang, L., Toan, N. N., Tho, N. Dai, Binh, N. N..  2019.  C500-CFG: A Novel Algorithm to Extract Control Flow-based Features for IoT Malware Detection. 2019 19th International Symposium on Communications and Information Technologies (ISCIT). :568—573.

{Static characteristic extraction method Control flow-based features proposed by Ding has the ability to detect malicious code with higher accuracy than traditional Text-based methods. However, this method resolved NP-hard problem in a graph, therefore it is not feasible with the large-size and high-complexity programs. So, we propose the C500-CFG algorithm in Control flow-based features based on the idea of dynamic programming, solving Ding's NP-hard problem in O(N2) time complexity, where N is the number of basic blocks in decom-piled executable codes. Our algorithm is more efficient and more outstanding in detecting malware than Ding's algorithm: fast processing time, allowing processing large files, using less memory and extracting more feature information. Applying our algorithms with IoT data sets gives outstanding results on 2 measures: Accuracy = 99.34%

Akbarzadeh, Aida, Pandey, Pankaj, Katsikas, Sokratis.  2019.  Cyber-Physical Interdependencies in Power Plant Systems: A Review of Cyber Security Risks. 2019 IEEE Conference on Information and Communication Technology. :1—6.

Realizing the importance of the concept of “smart city” and its impact on the quality of life, many infrastructures, such as power plants, began their digital transformation process by leveraging modern computing and advanced communication technologies. Unfortunately, by increasing the number of connections, power plants become more and more vulnerable and also an attractive target for cyber-physical attacks. The analysis of interdependencies among system components reveals interdependent connections, and facilitates the identification of those among them that are in need of special protection. In this paper, we review the recent literature which utilizes graph-based models and network-based models to study these interdependencies. A comprehensive overview, based on the main features of the systems including communication direction, control parameters, research target, scalability, security and safety, is presented. We also assess the computational complexity associated with the approaches presented in the reviewed papers, and we use this metric to assess the scalability of the approaches.

Rafati, Jacob, DeGuchy, Omar, Marcia, Roummel F..  2018.  Trust-Region Minimization Algorithm for Training Responses (TRMinATR): The Rise of Machine Learning Techniques. 2018 26th European Signal Processing Conference (EUSIPCO). :2015—2019.

Deep learning is a highly effective machine learning technique for large-scale problems. The optimization of nonconvex functions in deep learning literature is typically restricted to the class of first-order algorithms. These methods rely on gradient information because of the computational complexity associated with the second derivative Hessian matrix inversion and the memory storage required in large scale data problems. The reward for using second derivative information is that the methods can result in improved convergence properties for problems typically found in a non-convex setting such as saddle points and local minima. In this paper we introduce TRMinATR - an algorithm based on the limited memory BFGS quasi-Newton method using trust region - as an alternative to gradient descent methods. TRMinATR bridges the disparity between first order methods and second order methods by continuing to use gradient information to calculate Hessian approximations. We provide empirical results on the classification task of the MNIST dataset and show robust convergence with preferred generalization characteristics.

Mitra, Aritra, Abbas, Waseem, Sundaram, Shreyas.  2018.  On the Impact of Trusted Nodes in Resilient Distributed State Estimation of LTI Systems. 2018 IEEE Conference on Decision and Control (CDC). :4547—4552.

We address the problem of distributed state estimation of a linear dynamical process in an attack-prone environment. A network of sensors, some of which can be compromised by adversaries, aim to estimate the state of the process. In this context, we investigate the impact of making a small subset of the nodes immune to attacks, or “trusted”. Given a set of trusted nodes, we identify separate necessary and sufficient conditions for resilient distributed state estimation. We use such conditions to illustrate how even a small trusted set can achieve a desired degree of robustness (where the robustness metric is specific to the problem under consideration) that could otherwise only be achieved via additional measurement and communication-link augmentation. We then establish that, unfortunately, the problem of selecting trusted nodes is NP-hard. Finally, we develop an attack-resilient, provably-correct distributed state estimation algorithm that appropriately leverages the presence of the trusted nodes.

Jawad Kubba, Zaid M., Hoomod, Haider K..  2019.  A Hybrid Modified Lightweight Algorithm Combined of Two Cryptography Algorithms PRESENT and Salsa20 Using Chaotic System. 2019 First International Conference of Computer and Applied Sciences (CAS). :199–203.
Cryptography algorithms play a critical role in information technology against various attacks witnessed in the digital era. Many studies and algorithms are done to achieve security issues for information systems. The high complexity of computational operations characterises the traditional cryptography algorithms. On the other hand, lightweight algorithms are the way to solve most of the security issues that encounter applying traditional cryptography in constrained devices. However, a symmetric cipher is widely applied for ensuring the security of data communication in constraint devices. In this study, we proposed a hybrid algorithm based on two cryptography algorithms PRESENT and Salsa20. Also, a 2D logistic map of a chaotic system is applied to generate pseudo-random keys that produce more complexity for the proposed cipher algorithm. The goal of the proposed algorithm is to present a hybrid algorithm by enhancing the complexity of the current PRESENT algorithm while keeping the performance of computational operations as minimal. The proposed algorithm proved working efficiently with fast executed time, and the analysed result of the generated sequence keys passed the randomness of the NIST suite.
Zhao, Zhen, Lai, Jianchang, Susilo, Willy, Wang, Baocang, Hu, Yupu, Guo, Fuchun.  2019.  Efficient Construction for Full Black-Box Accountable Authority Identity-Based Encryption. IEEE Access. 7:25936—25947.

Accountable authority identity-based encryption (A-IBE), as an attractive way to guarantee the user privacy security, enables a malicious private key generator (PKG) to be traced if it generates and re-distributes a user private key. Particularly, an A-IBE scheme achieves full black-box security if it can further trace a decoder box and is secure against a malicious PKG who can access the user decryption results. In PKC'11, Sahai and Seyalioglu presented a generic construction for full black-box A-IBE from a primitive called dummy identity-based encryption, which is a hybrid between IBE and attribute-based encryption (ABE). However, as the complexity of ABE, their construction is inefficient and the size of private keys and ciphertexts in their instantiation is linear in the length of user identity. In this paper, we present a new efficient generic construction for full black-box A-IBE from a new primitive called token-based identity-based encryption (TB-IBE), without using ABE. We first formalize the definition and security model for TB-IBE. Subsequently, we show that a TB-IBE scheme satisfying some properties can be converted to a full black-box A-IBE scheme, which is as efficient as the underlying TB-IBE scheme in terms of computational complexity and parameter sizes. Finally, we give an instantiation with the computational complexity as O(1) and the constant size master key pair, private keys, and ciphertexts.

Jiang, Feng, Qi, Buren, Wu, Tianhao, Zhu, Konglin, Zhang, Lin.  2019.  CPSS: CP-ABE based Platoon Secure Sensing Scheme against Cyber-Attacks. 2019 IEEE Intelligent Transportation Systems Conference (ITSC). :3218—3223.

Platoon is one of cooperative driving applications where a set of vehicles can collaboratively sense each other for driving safety and traffic efficiency. However, platoon without security insurance makes the cooperative vehicles vulnerable to cyber-attacks, which may cause life-threatening accidents. In this paper, we introduce malicious attacks in platoon maneuvers. To defend against these attacks, we propose a Cyphertext-Policy Attribute-Based Encryption (CP-ABE) based Platoon Secure Sensing scheme, named CPSS. In the CPSS, platoon key is encapsulated in the access control structure in the key distribution process, so that interference messages sending by attackers without the platoon key could be ignored. Therefore, the sensing data which contains speed and position information can be protected. In this way, speed and distance fluctuations caused by attacks can be mitigated even eliminated thereby avoiding the collisions and ensuring the overall platoon stability. Time complexity analysis shows that the CPSS is more efficient than that of the polynomial time solutions. Finally, to evaluate capabilities of the CPSS, we integrate a LTE-V2X with platoon maneuvers based on Veins platform. The evaluation results show that the CPSS outperforms the baseline algorithm by 25% in terms of distance variations.

Bai, Kunpeng, Wu, Chuankun, Zhang, Zhenfeng.  2018.  Protect white-box AES to resist table composition attacks. IET Information Security. 12:305–313.
White-box cryptography protects cryptographic software in a white-box attack context (WBAC), where the dynamic execution of the cryptographic software is under full control of an adversary. Protecting AES in the white-box setting attracted many scientists and engineers, and several solutions emerged. However, almost all these solutions have been badly broken by various efficient white-box attacks, which target compositions of key-embedding lookup tables. In 2014, Luo, Lai, and You proposed a new WBAC-oriented AES implementation, and claimed that their implementation is secure against both Billet et al.'s attack and De Mulder et al.'s attack. In this study, based on the existing table-composition-targeting cryptanalysis techniques, the authors show that the secret key of the Luo-Lai-You (LLY) implementation can be recovered with a time complexity of about 244. Furthermore, the authors propose a new white-box AES implementation based on table lookups, which is shown to be resistant against the existing table-composition-targeting white-box attacks. The authors, key-embedding tables are obfuscated with large affine mappings, which cannot be cancelled out by table compositions of the existing cryptanalysis techniques. Although their implementation requires twice as much memory as the LLY WBAES to store the tables, its speed is about 63 times of the latter.
Komargodski, Ilan, Naor, Moni, Yogev, Eylon.  2017.  White-Box vs. Black-Box Complexity of Search Problems: Ramsey and Graph Property Testing. 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS). :622–632.
Ramsey theory assures us that in any graph there is a clique or independent set of a certain size, roughly logarithmic in the graph size. But how difficult is it to find the clique or independent set? If the graph is given explicitly, then it is possible to do so while examining a linear number of edges. If the graph is given by a black-box, where to figure out whether a certain edge exists the box should be queried, then a large number of queries must be issued. But what if one is given a program or circuit for computing the existence of an edge? This problem was raised by Buss and Goldberg and Papadimitriou in the context of TFNP, search problems with a guaranteed solution. We examine the relationship between black-box complexity and white-box complexity for search problems with guaranteed solution such as the above Ramsey problem. We show that under the assumption that collision resistant hash function exist (which follows from the hardness of problems such as factoring, discrete-log and learning with errors) the white-box Ramsey problem is hard and this is true even if one is looking for a much smaller clique or independent set than the theorem guarantees. In general, one cannot hope to translate all black-box hardness for TFNP into white-box hardness: we show this by adapting results concerning the random oracle methodology and the impossibility of instantiating it. Another model we consider is the succinct black-box, where there is a known upper bound on the size of the black-box (but no limit on the computation time). In this case we show that for all TFNP problems there is an upper bound on the number of queries proportional to the description size of the box times the solution size. On the other hand, for promise problems this is not the case. Finally, we consider the complexity of graph property testing in the white-box model. We show a property which is hard to test even when one is given the program for computing the graph. The hard property is whether the graph is a two-source extractor.
Cai, Zhipeng, Miao, Dongjing, Li, Yingshu.  2019.  Deletion Propagation for Multiple Key Preserving Conjunctive Queries: Approximations and Complexity. 2019 IEEE 35th International Conference on Data Engineering (ICDE). :506—517.

This paper studies the deletion propagation problem in terms of minimizing view side-effect. It is a problem funda-mental to data lineage and quality management which could be a key step in analyzing view propagation and repairing data. The investigated problem is a variant of the standard deletion propagation problem, where given a source database D, a set of key preserving conjunctive queries Q, and the set of views V obtained by the queries in Q, we try to identify a set T of tuples from D whose elimination prevents all the tuples in a given set of deletions on views △V while preserving any other results. The complexity of this problem has been well studied for the case with only a single query. Dichotomies, even trichotomies, for different settings are developed. However, no results on multiple queries are given which is a more realistic case. We study the complexity and approximations of optimizing the side-effect on the views, i.e., find T to minimize the additional damage on V after removing all the tuples of △V. We focus on the class of key-preserving conjunctive queries which is a dichotomy for the single query case. It is surprising to find that except the single query case, this problem is NP-hard to approximate within any constant even for a non-trivial set of multiple project-free conjunctive queries in terms of view side-effect. The proposed algorithm shows that it can be approximated within a bound depending on the number of tuples of both V and △V. We identify a class of polynomial tractable inputs, and provide a dynamic programming algorithm to solve the problem. Besides data lineage, study on this problem could also provide important foundations for the computational issues in data repairing. Furthermore, we introduce some related applications of this problem, especially for query feedback based data cleaning.

Paliath, Vivin, Shakarian, Paulo.  2019.  Reasoning about Sequential Cyberattacks. 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). :855–862.
Cyber adversaries employ a variety of malware and exploits to attack computer systems, usually via sequential or “chained” attacks, that take advantage of vulnerability dependencies. In this paper, we introduce a formalism to model such attacks. We show that the determination of the set of capabilities gained by an attacker, which also translates to extent to which the system is compromised, corresponds with the convergence of a simple fixed-point operator. We then address the problem of determining the optimal/most-dangerous strategy for a cyber-adversary with respect to this model and find it to be an NP-Complete problem. To address this complexity we utilize an A*-based approach with an admissible heuristic, that incorporates the result of the fixed-point operator and uses memoization for greater efficiency. We provide an implementation and show through a suite of experiments, using both simulated and actual vulnerability data, that this method performs well in practice for identifying adversarial courses of action in this domain. On average, we found that our techniques decrease runtime by 82%.
Babenko, Mikhail, Redvanov, Aziz Salimovich, Deryabin, Maxim, Chervyakov, Nikolay, Nazarov, Anton, Al-Galda, Safwat Chiad, Vashchenko, Irina, Dvoryaninova, Inna, Nepretimova, Elena.  2019.  Efficient Implementation of Cryptography on Points of an Elliptic Curve in Residue Number System. 2019 International Conference on Engineering and Telecommunication (EnT). :1—5.

The article explores the question of the effective implementation of arithmetic operations with points of an elliptic curve given over a prime field. Given that the basic arithmetic operations with points of an elliptic curve are the operations of adding points and doubling points, we study the question of implementing the arithmetic operations of adding and doubling points in various coordinate systems using the weighted number system and using the Residue Number System (RNS). We have shown that using the fourmodule RNS allows you to get an average gain for the operation of adding points of the elliptic curve of 8.67% and for the operation of doubling the points of the elliptic curve of 8.32% compared to the implementation using the operation of modular multiplication with special moduli from NIST FIPS 186.

Sahabandu, Dinuka, Moothedath, Shana, Bushnell, Linda, Poovendran, Radha, Aller, Joey, Lee, Wenke, Clark, Andrew.  2019.  A Game Theoretic Approach for Dynamic Information Flow Tracking with Conditional Branching. 2019 American Control Conference (ACC). :2289–2296.
In this paper, we study system security against Advanced Persistent Threats (APTs). APTs are stealthy and persistent but APTs interact with system and introduce information flows in the system as data-flow and control-flow commands. Dynamic Information Flow Tracking (DIFT) is a promising detection mechanism against APTs which taints suspicious input sources in the system and performs online security analysis when a tainted information is used in unauthorized manner. Our objective in this paper is to model DIFT that handle data-flow and conditional branches in the program that arise from control-flow commands. We use game theoretic framework and provide the first analytical model of DIFT with data-flow and conditional-branch tracking. Our game model which is an undiscounted infinite-horizon stochastic game captures the interaction between APTs and DIFT and the notion of conditional branching. We prove that the best response of the APT is a maximal reachability probability problem and provide a polynomial-time algorithm to find the best response by solving a linear optimization problem. We formulate the best response of the defense as a linear optimization problem and show that an optimal solution to the linear program returns a deterministic optimal policy for the defense. Since finding Nash equilibrium for infinite-horizon undiscounted stochastic games is computationally difficult, we present a nonlinear programming based polynomial-time algorithm to find an E-Nash equilibrium. Finally, we perform experimental analysis of our algorithm on real-world data for NetRecon attack augmented with conditional branching.
Fang, Bo, Hua, Zhongyun, Huang, Hejiao.  2019.  Locality-Sensitive Hashing Scheme Based on Heap Sort of Hash Bucket. 2019 14th International Conference on Computer Science Education (ICCSE). :5–10.
Nearest neighbor search (NNS) is one of the current popular research directions, which widely used in machine learning, pattern recognition, image detection and so on. In the low dimension data, based on tree search method can get good results. But when the data dimension goes up, that will produce a curse of dimensional. The proposed Locality-Sensitive Hashing algorithm (LSH) greatly improves the efficiency of nearest neighbor query for high dimensional data. But the algorithm relies on the building a large number of hash table, which makes the space complexity very high. C2LSH based on dynamic collision improves the disadvantage of LSH, but its disadvantage is that it needs to detect the collision times of a large number of data points which Increased query time. Therefore, Based on LSH algorithm, later researchers put forward many improved algorithms, but still not ideal.In this paper, we put forward Locality-Sensitive Hashing Scheme Based on Heap Sort of Hash Bucket (HSLSH) algorithm aiming at the shortcomings of LSH and C2LSH. Its main idea is to take advantage of the efficiency of heapsort in massive data sorting to improve the efficiency of nearest neighbor query. It only needs to rely on a small number of hash functions can not only overcome the shortcoming of LSH need to build a large number of hash table, and avoids defects of C2LSH. Experiments show that our algorithm is more than 20% better than C2LSH in query accuracy and 40% percent lower in query time.