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2021-09-21
Vaseer, Gurveen.  2020.  Multi-Attack Detection Using Forensics and Neural Network Based Prevention for Secure MANETs. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1–6.
This paper presents Forensic methods for detection and prevention of multiple attacks along with neural networks like Denial-of-Service (DoS), probe, vampire, and User-to-Root (U2R) attacks, in a Mobile Ad hoc Network (MANET). We accomplish attacker(s) detection and prevention percentage upto 99% in varied node density scenarios 50/100/150.
2021-09-16
Du, Xin, Tang, Songtao, Lu, Zhihui, Wet, Jie, Gai, Keke, Hung, Patrick C.K..  2020.  A Novel Data Placement Strategy for Data-Sharing Scientific Workflows in Heterogeneous Edge-Cloud Computing Environments. 2020 IEEE International Conference on Web Services (ICWS). :498–507.
The deployment of datasets in the heterogeneous edge-cloud computing paradigm has received increasing attention in state-of-the-art research. However, due to their large sizes and the existence of private scientific datasets, finding an optimal data placement strategy that can minimize data transmission as well as improve performance, remains a persistent problem. In this study, the advantages of both edge and cloud computing are combined to construct a data placement model that works for multiple scientific workflows. Apparently, the most difficult research challenge is to provide a data placement strategy to consider shared datasets, both within individual and among multiple workflows, across various geographically distributed environments. According to the constructed model, not only the storage capacity of edge micro-datacenters, but also the data transfer between multiple clouds across regions must be considered. To address this issue, we considered the characteristics of this model and identified the factors that are causing the transmission delay. The authors propose using a discrete particle swarm optimization algorithm with differential evolution (DE-DPSO) to distribute dataset during workflow execution. Based on this, a new data placement strategy named DE-DPSO-DPS is proposed. DE-DPSO-DPS is evaluated using several experiments designed in simulated heterogeneous edge-cloud computing environments. The results demonstrate that our data placement strategy can effectively reduce the data transmission time and achieve superior performance as compared to traditional strategies for data-sharing scientific workflows.
2021-09-08
Gupta, Anushikha, Kalra, Mala.  2020.  Intrusion Detection and Prevention System Using Cuckoo Search Algorithm with ANN in Cloud Computing. 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC). :66–72.
The Security is a vital aspect of cloud service as it comprises of data that belong to multiple users. Cloud service providers are responsible for maintaining data integrity, confidentiality and availability. They must ensure that their infrastructure and data are protected from intruders. In this research work Intrusion Detection System is designed to detect malicious server by using Cuckoo Search (CS) along with Artificial Intelligence. CS is used for feature optimization with the help of fitness function, the server's nature is categorized into two types: normal and attackers. On the basis of extracted features, ANN classify the attackers which affect the networks in cloud environment. The main aim is to distinguish attacker servers that are affected by DoS/DDoS, Black and Gray hole attacks from the genuine servers. Thus, instead of passing data to attacker server, the server passes the data to the genuine servers and hence, the system is protected. To validate the performance of the system, QoS parameters such as PDR (Packet delivery rate), energy consumption rate and total delay before and after prevention algorithm are measured. When compared with existing work, the PDR and the delay have been enhanced by 3.0 %and 21.5 %.
2021-09-07
Gameiro, Luís, Senna, Carlos, Luís, Miguel.  2020.  Context-Based Forwarding for Mobile ICNs. 2020 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
Over the last couple of decades, mobile ad-hoc networks (MANETs) have been at the forefront of research, yet still are afflicted by high network fragmentation, due to their continuous node mobility and geographical dispersion. To address these concerns, a new paradigm was proposed, Information-Centric Networks (ICN), whose focus is the delivery of Content based on names. This article aims to use ICN concepts towards the delivery of both urgent and non-urgent information in urban mobile environments. In order to do so, a context-based forwarding strategy was proposed, with a very clear goal: to take advantage of both packet Names and Data, and node's neighborhood analysis in order to successfully deliver content into the network in the shortest period of time, and without worsening network congestion. The design, implementation and validation of the proposed strategy was performed using the ndnSIM platform along with real mobility traces from communication infrastructure of the Porto city. The results show that the proposed context-based forwarding strategy presents a clear improvement regarding the Data resolution, while maintaining network overhead at a constant.
Tirupathi, Chittibabu, Hamdaoui, Bechir, Rayes, Ammar.  2020.  HybridCache: AI-Assisted Cloud-RAN Caching with Reduced In-Network Content Redundancy. GLOBECOM 2020 - 2020 IEEE Global Communications Conference. :1–6.
The ever-increasing growth of urban populations coupled with recent mobile data usage trends has led to an unprecedented increase in wireless devices, services and applications, with varying quality of service needs in terms of latency, data rate, and connectivity. To cope with these rising demands and challenges, next-generation wireless networks have resorted to cloud radio access network (Cloud-RAN) technology as a way of reducing latency and network traffic. A concrete example of this is New York City's LinkNYC network infrastructure, which replaces the city's payphones with kiosk-like structures, called Links, to provide fast and free public Wi-Fi access to city users. When enabled with data storage capability, these Links can, for example, play the role of edge cloud devices to allow in-network content caching so that access latency and network traffic are reduced. In this paper, we propose HybridCache, a hybrid proactive and reactive in-network caching scheme that reduces content access latency and network traffic congestion substantially. It does so by first grouping edge cloud devices in clusters to minimize intra-cluster content access latency and then enabling cooperative-proactively and reactively-caching using LSTM-based prediction to minimize in-network content redundancy. Using the LinkNYC network as the backbone infrastructure for evaluation, we show that HybridCache reduces the number of hops that content needs to traverse and increases cache hit rates, thereby reducing both network traffic and content access latency.
Faqir, Nada, En-Nahnahi, Noureddine, Boumhidi, Jaouad.  2020.  Deep Q-learning Approach for Congestion Problem In Smart Cities. 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS). :1–6.
Traffic congestion is a critical problem in urban area. In this study, our objective is the control of traffic lights in an urban environment, in order to avoid traffic jams and optimize vehicle traffic; we aim to minimize the total waiting time. Our system is based on a new paradigm, which is deep reinforcement learning; it can automatically learn all the useful characteristics of traffic data and develop a strategy optimizing adaptive traffic light control. Our system is coupled to a microscopic simulator based on agents (Simulation of Urban MObility - SUMO) providing a synthetic but realistic environment in which the exploration of the results of potential regulatory actions can be carried out.
Zhang, Xinghai, Zhuang, Zhen, Liu, Genggeng, Huang, Xing, Liu, Wen-Hao, Guo, Wenzhong, Wang, Ting-Chi.  2020.  MiniDelay: Multi-Strategy Timing-Aware Layer Assignment for Advanced Technology Nodes. 2020 Design, Automation Test in Europe Conference Exhibition (DATE). :586–591.
Layer assignment, a major step in global routing of integrated circuits, is usually performed to assign segments of nets to multiple layers. Besides the traditional optimization goals such as overflow and via count, interconnect delay plays an important role in determining chip performance and has been attracting much attention in recent years. Accordingly, in this paper, we propose MiniDelay, a timing-aware layer assignment algorithm to minimize delay for advanced technology nodes, taking both wire congestion and coupling effect into account. MiniDelay consists of the following three key techniques: 1) a non-default-rule routing technique is adopted to reduce the delay of timing critical nets, 2) an effective congestion assessment method is proposed to optimize delay of nets and via count simultaneously, and 3) a net scalpel technique is proposed to further reduce the maximum delay of nets, so that the chip performance can be improved in a global manner. Experimental results on multiple benchmarks confirm that the proposed algorithm leads to lower delay and few vias, while achieving the best solution quality among the existing algorithms with the shortest runtime.
2021-08-17
Hussien, Zainab Waleed, Qawasmeh, Doaa Sami, Shurman, Mohammad.  2020.  MSCLP: Multi-Sinks Cluster-Based Location Privacy Protection scheme in WSNs for IoT. 2020 32nd International Conference on Microelectronics (ICM). :1—4.
One of the most important information in Wireless Sensor Networks (WSNs) is the location of each sensor node. This kind of information is very attractive to attackers for real position exposure of nodes making the whole network vulnerable to different kinds of attacks. According to WSNs privacy, there are two types of threats affect the network: Contextual and Content privacy. In this work, we study contextual privacy, where an eavesdropper tries to find the location of the source or sink node. We propose a Multi-Sinks Cluster-Based Location Privacy Protection (MSCLP) scheme in WSNs that divides the WSN into clusters, each cluster managed by one cluster head (CH). Each CH sends random fake packets in a loop then sends the real packet to the neighbor's CHs using a dynamic routing method to confuse the attacker from tracing back the real packet to reveal the actual location of the source node, we are taking in our consideration two important metrics: the energy consumption, and the delay.
Tang, Jie, Xu, Aidong, Jiang, Yixin, Zhang, Yunan, Wen, Hong, Zhang, Tengyue.  2020.  Secret Key Attaches in MIMO IoT Communications by Using Self-injection Artificial Noise. 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). :225–229.
Internet of Things (IoT) enable information transmission and sharing among massive IoT devices. However, the key establishment and management in IoT become more challenging due to the low latency requirements and resource constrained IoT devices. In this work, we propose a practical physical layer based secret key sharing scheme for MIMO (multiple-input-multiple-output) IoT devices to reduce the communication delay caused by key establishment of MIMO IoT devices. This is because the proposed scheme attachs secret key sharing with communication simultaneously. It is achieved by the proposed MIMO self-injection AN (SAN) tranmsission, which is designed to deliberately maximum the receive SNR (signal to noise ratio) at different antenna of the legitimate IoT device, based on the value of secret key sharing to him. The simulation results verified the validity and security of the proposed scheme.
Monakhov, Yuri, Kuznetsova, Anna, Monakhov, Mikhail, Telny, Andrey, Bednyatsky, Ilya.  2020.  Performance Evaluation of the Modified HTB Algorithm. 2020 Dynamics of Systems, Mechanisms and Machines (Dynamics). :1—5.
In this article, authors present the results of testing the modified HTB traffic control algorithm in an experimental setup. The algorithm is implemented as a Linux kernel module. An analysis of the experimental results revealed the effect of uneven packet loss in priority classes. In the second part of the article, the authors propose a solution to this problem by applying a distribution scheme for the excess of tokens, according to which excess class tokens are given to the leaf with the highest priority. The new modification of the algorithm was simulated in the AnyLogic environment. The results of an experimental study demonstrated that dividing the excess tokens of the parent class between daughter classes is less effective in terms of network performance than allocating the excess tokens to a high-priority class during the competition for tokens between classes. In general, a modification of the HTB algorithm that implements the proposed token surplus distribution scheme yields more consistent delay times for the high-priority class.
2021-08-11
Brooks, Richard, Wang, Kuang-Ching, Oakley, Jon, Tusing, Nathan.  2020.  Global Internet Traffic Routing and Privacy. 2020 International Scientific and Technical Conference Modern Computer Network Technologies (MoNeTeC). :1—7.
Current Internet Protocol routing provides minimal privacy, which enables multiple exploits. The main issue is that the source and destination addresses of all packets appear in plain text. This enables numerous attacks, including surveillance, man-in-the-middle (MITM), and denial of service (DoS). The talk explains how these attacks work in the current network. Endpoints often believe that use of Network Address Translation (NAT), and Dynamic Host Configuration Protocol (DHCP) can minimize the loss of privacy.We will explain how the regularity of human behavior can be used to overcome these countermeasures. Once packets leave the local autonomous system (AS), they are routed through the network by the Border Gateway Protocol (BGP). The talk will discuss the unreliability of BGP and current attacks on the routing protocol. This will include an introduction to BGP injects and the PEERING testbed for BGP experimentation. One experiment we have performed uses statistical methods (CUSUM and F-test) to detect BGP injection events. We describe work we performed that applies BGP injects to Internet Protocol (IP) address randomization to replace fixed IP addresses in headers with randomized addresses. We explain the similarities and differences of this approach with virtual private networks (VPNs). Analysis of this work shows that BGP reliance on autonomous system (AS) numbers removes privacy from the concept, even though it would disable the current generation of MITM and DoS attacks. We end by presenting a compromise approach that creates software-defined data exchanges (SDX), which mix traffic randomization with VPN concepts. We contrast this approach with the Tor overlay network and provide some performance data.
2021-08-02
Thapar, Shruti, Sharma, Sudhir Kumar.  2020.  Direct Trust-based Detection Algorithm for Preventing Jellyfish Attack in MANET. 2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA). :749–753.
The dynamic and adaptable characteristics of mobile ad hoc networks have made it a significant field for deploying various applications in wireless sensor networks. Increasing popularity of the portable devices is the main reason for the development of mobile ad hoc networks. Furthermore, the network does not require a fixed architecture and it is easy to deploy. This type of network is highly vulnerable to cyber-attacks as the nodes communicate with each other through a Wireless medium. The most critical attack in ad hoc network is jellyfish attack. In this research we have proposed a Direct Trust-based Detection Algorithm to detect and prevent jellyfish attack in MANET.
2021-07-08
Chandavarkar, B. R., Gadagkar, Akhilraj V..  2020.  Mitigating Localization and Neighbour Spoofing Attacks in Underwater Sensor Networks. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). :1—5.
The location information of a node is one of the essential attributes used in most underwater communication routing algorithms to identify a candidate forwarding node by any of the sources. The exact location information of a node exchanged with its neighbours' in plain text and the absence of node authentication results in some of the attacks such as Sybil attack, Blackhole attack, and Wormhole attack. Moreover, the severe consequence of these attacks is Denial of Service (DoS), poor network performance, reduced network lifetime, etc. This paper proposes an anti-Spoof (a-Spoof) algorithm for mitigating localization and neighbour spoofing attacks in UASN. a-Spoof uses three pre-shared symmetric keys to share the location. Additionally, location integrity provided through the hash function. Further, the performance of a-Spoof demonstrated through its implementation in UnetStack with reference to end-to-end packet delay and the number of hops.
2021-06-28
Latha Ch., Mary, Bazil Raj, A.A., Abhikshit, L..  2020.  Design and Implementation of a Secure Physical Unclonable Function In FPGA. 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). :1083–1089.
A Field Programmable Gate Array (FPGA) is a digital Integrated Circuit made up of interconnected functional blocks, which can be programmed by the end-user to perform required logic functions. As FPGAs are re-programmable, partially re-configurable and have lowertime to market, FPGA has become a vital component in the field of electronics. FPGAs are undergoing many security issues as the adversaries are trying to make profits by replicating the original design, without any investment. The major security issues are cloning, counterfeiting, reverse engineering, Physical tampering, and insertion of malicious components, etc. So, there is a need for security of FPGAs. A Secret key must be embedded in an IC, to provide identification and authentication to it. Physical Unclonable Functions (PUFs) can provide these secret keys, by using the physical properties of the chip. These physical properties are not reproducible even by the manufacturer. Hence the responses produced by the PUF are unique for every individual chip. The method of generating unique binary signatures helps in cryptographic key generation, digital rights management, Intellectual Property (IP) protection, IC counterfeit prevention, and device authentication. The PUFs are very promising in signature generation in the field of hardware security. In this paper, the secret binary responses is generated with the help of a delay based Ring Oscillator PUF, which does not use a clock circuit in its architecture.
P N, Renjith, K, Ramesh.  2020.  Trust based Security framework for IoT data. 2020 4th International Conference on Computer, Communication and Signal Processing (ICCCSP). :1–5.
With an incredible growth in MEMS and Internet, IoT has developed to an inevitable invention and resource for human needs. IoT reframes the communication and created a new way of machine to machine communication. IoT utilizes smart sensor to monitor and track environmental changes in any area of interest. The high volume of sensed information is processed, formulated and presented to the user for decision making. In this paper a model is designed to perform trust evaluation and data aggregation with confidential transmission of secured information in to the network and enables higher secure and reliable data transmission for effective analysis and decision making. The Sensors in IoT devices, senses the same information and forwards redundant data in to the network. This results in higher network congestion and causes transmission overhead. This could be control by introducing data aggregation. A gateway sensor node can act as aggregator and a forward unique information to the base station. However, when the network is adulterated with malicious node, these malicious nodes tend to injects false data in to the network. In this paper, a trust based malicious node detection technique has been introduced to isolate the malicious node from forwarding false information into the network. Simulation results proves the proposed protocol can be used to reduce malicious attack with increased throughput and performance.
2021-06-01
Xu, Meng, Kashyap, Sanidhya, Zhao, Hanqing, Kim, Taesoo.  2020.  Krace: Data Race Fuzzing for Kernel File Systems. 2020 IEEE Symposium on Security and Privacy (SP). :1643—1660.
Data races occur when two threads fail to use proper synchronization when accessing shared data. In kernel file systems, which are highly concurrent by design, data races are common mistakes and often wreak havoc on the users, causing inconsistent states or data losses. Prior fuzzing practices on file systems have been effective in uncovering hundreds of bugs, but they mostly focus on the sequential aspect of file system execution and do not comprehensively explore the concurrency dimension and hence, forgo the opportunity to catch data races.In this paper, we bring coverage-guided fuzzing to the concurrency dimension with three new constructs: 1) a new coverage tracking metric, alias coverage, specially designed to capture the exploration progress in the concurrency dimension; 2) an evolution algorithm for generating, mutating, and merging multi-threaded syscall sequences as inputs for concurrency fuzzing; and 3) a comprehensive lockset and happens-before modeling for kernel synchronization primitives for precise data race detection. These components are integrated into Krace, an end-to-end fuzzing framework that has discovered 23 data races in ext4, btrfs, and the VFS layer so far, and 9 are confirmed to be harmful.
2021-05-25
Cai, Feiyang, Li, Jiani, Koutsoukos, Xenofon.  2020.  Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression. 2020 IEEE Security and Privacy Workshops (SPW). :208–214.

Learning-enabled components (LECs) are widely used in cyber-physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level of autonomy. However, it has been shown that LECs such as deep neural networks (DNN) are not robust and adversarial examples can cause the model to make a false prediction. The paper considers the problem of efficiently detecting adversarial examples in LECs used for regression in CPS. The proposed approach is based on inductive conformal prediction and uses a regression model based on variational autoencoder. The architecture allows to take into consideration both the input and the neural network prediction for detecting adversarial, and more generally, out-of-distribution examples. We demonstrate the method using an advanced emergency braking system implemented in an open source simulator for self-driving cars where a DNN is used to estimate the distance to an obstacle. The simulation results show that the method can effectively detect adversarial examples with a short detection delay.

Zhu, Hong, Xia, Bing, Zhou, Dongxu, Zhang, Ming, Ma, Zhoujun.  2020.  Research on Integrated Model and Interactive Influence of Energy Internet Cyber Physical System. 2020 IEEE Sustainable Power and Energy Conference (iSPEC). :1667–1671.

Energy Internet is a typical cyber-physical system (CPS), in which the disturbance on cyber part may result in the operation risks on the physical part. In order to perform CPS assessment and research the interactive influence between cyber part and physical part, an integrated energy internet CPS model which adopts information flow matrix, energy control flow matrix and information energy hybrid flow matrix is proposed in this paper. The proposed model has a higher computational efficacy compared with simulation based approaches. Then, based on the proposed model, the influence of cyber disturbances such as data dislocation, data delay and data error on the physical part are studied. Finally, a 3 MW PET based energy internet CPS is built using PSCAD/EMTDC software. The simulation results prove the validity of the proposed model and the correctness of the interactive influence analysis.

2021-05-18
Intharawijitr, Krittin, Harvey, Paul, Imai, Pierre.  2020.  A Feasibility Study of Cache in Smart Edge Router for Web-Access Accelerator. 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC). :360–365.
Regardless of the setting, edge computing has drawn much attention from both the academic and industrial communities. For edge computing, content delivery networks are both a concrete and production deployable use case. While viable at the WAN or telco edge scale, it is unclear if this extends to others, such as in home WiFi routers, as has been assumed by some. In this work-in-progress, we present an initial study on the viability of using smart edge WiFi routers as a caching location. We describe the simulator we created to test this, as well as the analysis of the results obtained. We use 1 day of e-commerce web log traffic from a public data set, as well as a sampled subset of our own site - part of an ecosystem of over 111 million users. We show that in the best case scenario, smart edge routers are inappropriate for e-commerce web caching.
Hasslinger, Gerhard, Ntougias, Konstantinos, Hasslinger, Frank, Hohlfeld, Oliver.  2020.  General Knapsack Bounds of Web Caching Performance Regarding the Properties of each Cacheable Object. 2020 IFIP Networking Conference (Networking). :821–826.
Caching strategies have been evaluated and compared in many studies, most often via simulation, but also in analytic methods. Knapsack solutions provide a general analytical approach for upper bounds on web caching performance. They assume objects of maximum (value/size) ratio being selected as cache content, with flexibility to define the caching value. Therefore the popularity, cost, size, time-to-live restrictions etc. per object can be included an overall caching goal, e.g., for reducing delay and/or transport path length in content delivery. The independent request model (IRM) leads to basic knapsack bounds for static optimum cache content. We show that a 2-dimensional (2D-)knapsack solution covers arbitrary request pattern, which selects dynamically changing content yielding maximum caching value for any predefined request sequence. Moreover, Belady's optimum strategy for clairvoyant caching is identified as a special case of our 2D-knapsack solution when all objects are unique. We also summarize a comprehensive picture of the demands and efficiency criteria for web caching, including updating speed and overheads. Our evaluations confirm significant performance gaps from LRU to advanced GreedyDual and score-based web caching methods and to the knapsack bounds.
2021-04-27
Tahsini, A., Dunstatter, N., Guirguis, M., Ahmed, C. M..  2020.  DeepBLOC: A Framework for Securing CPS through Deep Reinforcement Learning on Stochastic Games. 2020 IEEE Conference on Communications and Network Security (CNS). :1–9.

One important aspect in protecting Cyber Physical System (CPS) is ensuring that the proper control and measurement signals are propagated within the control loop. The CPS research community has been developing a large set of check blocks that can be integrated within the control loop to check signals against various types of attacks (e.g., false data injection attacks). Unfortunately, it is not possible to integrate all these “checks” within the control loop as the overhead introduced when checking signals may violate the delay constraints of the control loop. Moreover, these blocks do not completely operate in isolation of each other as dependencies exist among them in terms of their effectiveness against detecting a subset of attacks. Thus, it becomes a challenging and complex problem to assign the proper checks, especially with the presence of a rational adversary who can observe the check blocks assigned and optimizes her own attack strategies accordingly. This paper tackles the inherent state-action space explosion that arises in securing CPS through developing DeepBLOC (DB)-a framework in which Deep Reinforcement Learning algorithms are utilized to provide optimal/sub-optimal assignments of check blocks to signals. The framework models stochastic games between the adversary and the CPS defender and derives mixed strategies for assigning check blocks to ensure the integrity of the propagated signals while abiding to the real-time constraints dictated by the control loop. Through extensive simulation experiments and a real implementation on a water purification system, we show that DB achieves assignment strategies that outperform other strategies and heuristics.

2021-04-08
Yamaguchi, A., Mizuno, O..  2020.  Reducing Processing Delay and Node Load Using Push-Based Information-Centric Networking. 2020 3rd World Symposium on Communication Engineering (WSCE). :59–63.
Information-Centric Networking (ICN) is attracting attention as a content distribution method against increasing network traffic. Content distribution in ICN adopts a pull-type communication method that returns data to Interest. However, in this case, the push-type communication method is advantageous. Therefore, the authors have proposed a method in which a server pushes content to reduce the node load in an environment where a large amount of Interest to specific content occurs in a short time. In this paper, we analyze the packet processing delay time with and without the proposed method in an environment where a router processes a large number of packets using a simulator. Simulation results show that the proposed method can reduce packet processing delay time and node load.
Deng, L., Luo, J., Zhou, J., Wang, J..  2020.  Identity-based Secret Sharing Access Control Framework for Information-Centric Networking. 2020 IEEE/CIC International Conference on Communications in China (ICCC). :507–511.
Information-centric networking (ICN) has played an increasingly important role in the next generation network design. However, to make better use of request-response communication mode in the ICN network, revoke user privileges more efficiently and protect user privacy more safely, an effective access control mechanism is needed. In this paper, we propose IBSS (identity-based secret sharing), which achieves efficient content distribution by using improved Shamir's secret sharing method. At the same time, collusion attacks are avoided by associating polynomials' degree with the number of users. When authenticating user identity and transmitting content, IBE and IBS are introduced to achieve more efficient and secure identity encryption. From the experimental results, the scheme only introduces an acceptable delay in file retrieval, and it can request follow-up content very efficiently.
2021-03-30
Baybulatov, A. A., Promyslov, V. G..  2020.  On a Deterministic Approach to Solving Industrial Control System Problems. 2020 International Russian Automation Conference (RusAutoCon). :115—120.

Since remote ages, queues and delays have been a rather exasperating reality of human daily life. Today, they pursue us everywhere: in technical, social, socio-technical, and even control systems, dramatically deteriorating their performance. In this variety, it is the computer systems that are sure to cause the growing anxiety in our digital era. Although for our everyday Internet surfing, experiencing long-lasting and annoying delays is an unpleasant but not dangerous situation, for industrial control systems, especially those dealing with critical infrastructures, such behavior is unacceptable. The article presents a deterministic approach to solving some digital control system problems associated with delays and backlogs. Being based on Network calculus, in contrast to statistical methods of Queuing theory, it provides worst-case results, which are eminently desirable for critical infrastructures. The article covers the basics of a theory of deterministic queuing systems Network calculus, its evolution regarding the relationship between backlog bound and delay, and a technique for handling empirical data. The problems being solved by the deterministic approach: standard calculation of network performance measures, estimation of database maximum updating time, and cybersecurity assessment including such issues as the CIA triad representation, operational technology influence, and availability understanding focusing on its correlation with a delay are thoroughly discussed as well.

2021-03-29
Shaout, A., Schmidt, N..  2020.  Keystroke Identifier Using Fuzzy Logic to Increase Password Security. 2020 21st International Arab Conference on Information Technology (ACIT). :1—8.

Cybersecurity is a major issue today. It is predicted that cybercrime will cost the world \$6 trillion annually by 2021. It is important to make logins secure as well as to make advances in security in order to catch cybercriminals. This paper will design and create a device that will use Fuzzy logic to identify a person by the rhythm and frequency of their typing. The device will take data from a user from a normal password entry session. This data will be used to make a Fuzzy system that will be able to identify the user by their typing speed. An application of this project could be used to make a more secure log-in system for a user. The log-in system would not only check that the correct password was entered but also that the rhythm of how the password was typed matched the user. Another application of this system could be used to help catch cybercriminals. A cybercriminal may have a certain rhythm at which they type at and this could be used like a fingerprint to help officials locate cybercriminals.