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Fu, Shichong, Li, Xiaoling, Zhao, Yao.  2022.  Improved Steganography Based on Referential Cover and Non-symmetric Embedding. 2022 IEEE 5th International Conference on Electronics Technology (ICET). :1202–1206.
Minimizing embedding impact model of steganography has good performance for steganalysis detection. By using effective distortion cost function and coding method, steganography under this model becomes the mainstream embedding framework recently. In this paper, to improve the anti-detection performance, a new steganography optimization model by constructing a reference cover is proposed. First, a reference cover is construed by performing a filtering operation on the cover image. Then, by minimizing the residual between the reference cover and the original cover, the optimization function is formulated considering the effect of different modification directions. With correcting the distortion cost of +1 and \_1 modification operations, the stego image obtained by the proposed method is more consistent with the natural image. Finally, by applying the proposed framework to the cost function of the well-known HILL embedding, experimental results show that the anti-detection performance of the proposed method is better than the traditional method.
ISSN: 2768-6515
Kotkar, Aditya, Khadapkar, Shreyas, Gupta, Aniket, Jangale, Smita.  2022.  Multiple layered Security using combination of Cryptography with Rotational, Flipping Steganography and Message Authentication. 2022 IEEE International Conference on Data Science and Information System (ICDSIS). :1–5.
Data or information are being transferred at an enormous pace and hence protecting and securing this transmission of data are very important and have been very challenging. Cryptography and Steganography are the most broadly used techniques for safeguarding data by encryption of data and hiding the existence of data. A multi-layered secure transmission can be achieved by combining Cryptography with Steganography and by adding message authentication ensuring the confidentiality of the message. Different approach towards Steganography implementation is proposed using rotations and flips to prevent detection of encoded messages. Compression of multimedia files is set up for increasing the speed of encoding and consuming less storage space. The HMAC (Hash-based Authentication Code) algorithm is chosen for message authentication and integrity. The performance of the proposed Steganography methods is concluded using Histogram comparative analysis. Simulations have been performed to back the reliability of the proposed method.
Guri, Mordechai.  2022.  ETHERLED: Sending Covert Morse Signals from Air-Gapped Devices via Network Card (NIC) LEDs. 2022 IEEE International Conference on Cyber Security and Resilience (CSR). :163—170.
Highly secure devices are often isolated from the Internet or other public networks due to the confidential information they process. This level of isolation is referred to as an ’air-gap .’In this paper, we present a new technique named ETHERLED, allowing attackers to leak data from air-gapped networked devices such as PCs, printers, network cameras, embedded controllers, and servers. Networked devices have an integrated network interface controller (NIC) that includes status and activity indicator LEDs. We show that malware installed on the device can control the status LEDs by blinking and alternating colors, using documented methods or undocumented firmware commands. Information can be encoded via simple encoding such as Morse code and modulated over these optical signals. An attacker can intercept and decode these signals from tens to hundreds of meters away. We show an evaluation and discuss defensive and preventive countermeasures for this exfiltration attack.
Miao, Weiwei, Jin, Chao, Zeng, Zeng, Bao, Zhejing, Wei, Xiaogang, Zhang, Rui.  2022.  A White-Box SM4 Implementation by Introducing Pseudo States Applied to Edge IoT Agents. 2022 4th Asia Energy and Electrical Engineering Symposium (AEEES). :154–160.
With the widespread application of power Internet of Things (IoT), the edge IoT agents are often threatened by various attacks, among which the white-box attack is the most serious. The white-box implementation of the cryptography algorithm can hide key information even in the white-box attack context by means of obfuscation. However, under the specially designed attack, there is still a risk of the information being recovered within a certain time complexity. In this paper, by introducing pseudo states, a new white-box implementation of SM4 algorithm is proposed. The encryption and decryption processes are implemented in the form of matrices and lookup tables, which are obfuscated by scrambling encodings. The introduction of pseudo states could complicate the obfuscation, leading to the great improvement in the security. The number of pseudo states can be changed according to the requirements of security. Through several quantitative indicators, including diversity, ambiguity, the time complexity required to extract the key and the value space of the key and external encodings, it is proved that the security of the proposed implementation could been enhanced significantly, compared with the existing schemes under similar memory occupation.
Xie, Nanjiang, Gong, Zheng, Tang, Yufeng, Wang, Lei, Wen, Yamin.  2022.  Protecting White-Box Block Ciphers with Galois/Counter Mode. 2022 IEEE Conference on Dependable and Secure Computing (DSC). :1–7.
All along, white-box cryptography researchers focus on the design and implementation of certain primitives but less to the practice of the cipher working modes. For example, the Galois/Counter Mode (GCM) requires block ciphers to perform only the encrypting operations, which inevitably facing code-lifting attacks under the white-box security model. In this paper, a code-lifting resisted GCM (which is named WBGCM) is proposed to mitigate this security drawbacks in the white-box context. The basic idea is to combining external encodings with exclusive-or operations in GCM, and therefore two different schemes are designed with external encodings (WBGCM-EE) and maskings (WBGCM-Maksing), respectively. Furthermore, WBGCM is instantiated with Chow et al.'s white-box AES, and the experiments show that the processing speeds of WBGCM-EE and WBGCM-Masking achieves about 5 MBytes/Second with a marginal storage overhead.
Torres-Figueroa, Luis, Mönich, Ullrich J., Voichtleitner, Johannes, Frank, Anna, Andrei, Vlad-Costin, Wiese, Moritz, Boche, Holger.  2021.  Experimental Evaluation of a Modular Coding Scheme for Physical Layer Security. 2021 IEEE Global Communications Conference (GLOBECOM). :1–6.
In this paper we use a seeded modular coding scheme for implementing physical layer security in a wiretap scenario. This modular scheme consists of a traditional coding layer and a security layer. For the traditional coding layer, we use a polar code. We evaluate the performance of the seeded modular coding scheme in an experimental setup with software defined radios and compare these results to simulation results. In order to assess the secrecy level of the scheme, we employ the distinguishing security metric. In our experiments, we compare the distinguishing error rate for different seeds and block lengths.
Ueda, Yuki, Ishio, Takashi, Matsumoto, Kenichi.  2021.  Automatically Customizing Static Analysis Tools to Coding Rules Really Followed by Developers. 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). :541–545.
Automatic Static Analysis Tools (ASATs) detect coding rule violations, including mistakes and bad practices that frequently occur during programming. While ASATs are widely used in both OSS and industry, the developers do not resolve more than 80% of the detected violations. As one of the reasons, most ASATs users do not customize their ASATs to their projects after installation; the ASATs with the default configuration report many rule violations that confuse developers. To reduce the ratio of such uninteresting warning messages, we propose a method to customize ASATs according to the product source code automatically. Our fundamental hypothesis is: A software project has interesting ASAT rules that are consistent over time. Our method takes source code as input and generates an ASAT configuration. In particular, the method enables optional (i.e., disabled by default) rules that detected no violations on the version because developers are likely to follow the rules in future development. Our method also disables violated rules because developers were unlikely to follow them. To evaluate the method, we applied our method to 643 versions of four JavaScript projects. The generated configurations for all four projects increased the ASAT precision. They also increased recall for two projects. The result shows that our method helps developers to focus on their attractive rule violations. Our implementation of the proposed method is available at
Yang, Shaofei, Liu, Longjun, Li, Baoting, Sun, Hongbin, Zheng, Nanning.  2020.  Exploiting Variable Precision Computation Array for Scalable Neural Network Accelerators. 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS). :315–319.
In this paper, we present a flexible Variable Precision Computation Array (VPCA) component for different accelerators, which leverages a sparsification scheme for activations and a low bits serial-parallel combination computation unit for improving the efficiency and resiliency of accelerators. The VPCA can dynamically decompose the width of activation/weights (from 32bit to 3bit in different accelerators) into 2-bits serial computation units while the 2bits computing units can be combined in parallel computing for high throughput. We propose an on-the-fly compressing and calculating strategy SLE-CLC (single lane encoding, cross lane calculation), which could further improve performance of 2-bit parallel computing. The experiments results on image classification datasets show VPCA can outperforms DaDianNao, Stripes, Loom-2bit by 4.67×, 2.42×, 1.52× without other overhead on convolution layers.
Tiwari, Krishnakant, Gangurde, Sahil J..  2021.  LSB Steganography Using Pixel Locator Sequence with AES. 2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC). :302—307.
Image steganography is a technique of hiding confidential data in the images. We do this by incorporating the LSB(Least Significant Bit) of the image pixels. LSB steganography has been there for a while, and much progress has been made in it. In this paper, we try to increase the security of the LSB steganography process by incorporating a random data distribution method which we call pixel locator sequence (PLS). This method scatters the data to be infused into the image by randomly picking up the pixels and changing their LSB value accordingly. This random distribution makes it difficult for unknowns to look for the data. This PLS file is also encrypted using AES and is key for the data encryption/decryption process between the two parties. This technique is not very space-efficient and involves sending meta-data (PLS), but that trade-off was necessary for the additional security. We evaluated the proposed approach using two criteria: change in image dynamics and robustness against steganalysis attacks. To assess change in image dynamics, we measured the MSE and PSNR values. To find the robustness of the proposed method, we used the tool StegExpose which uses the stego image produced from the proposed algorithm and analyzes them using the major steganalysis attacks such as Primary Sets, Chi-Square, Sample Pairs, and RS Analysis. Finally, we show that this method has good security metrics for best known LSB steganography detection tools and techniques.
Jin, Chao, Zeng, Zeng, Miao, Weiwei, Bao, Zhejing, Zhang, Rui.  2021.  A Nonlinear White-Box SM4 Implementation Applied to Edge IoT Agents. 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2). :3358–3363.
With the rapid development of power Internet of Things (IoT), the ubiquitous edge agents are frequently exposed in a risky environment, where the white-box attacker could steal all the internal information by full observation of dynamic execution of the cryptographic software. In this situation, a new table-based white-box cryptography implementation of SM4 algorithm is proposed to prevent the attacker from extracting the secret key, which hides the encryption and decryption process in obfuscated lookup tables. Aiming to improve the diversity and ambiguity of the lookup tables as well as resist different types of white-box attacks, the random bijective nonlinear mappings are applied as scrambling encodings of the lookup tables. Moreover, in order to make our implementation more practical in the resource-constrained edge IoT agent, elaborate design is proposed to make some tables reusability, leading to less memory occupation while guaranteeing the security. The validity and security of the proposed implementation will be illustrated through several evaluation indicators.
Song, Xiumin, Liu, Bo, Zhang, Hongxin, Mao, Yaya, Ren, Jianxin, Chen, Shuaidong, Xu, Hui, Zhang, Jingyi, Jiang, Lei, Zhao, Jianye et al..  2020.  Security Enhancing and Probability Shaping Coordinated Optimization for CAP-PON in Physical Layer. 2020 Asia Communications and Photonics Conference (ACP) and International Conference on Information Photonics and Optical Communications (IPOC). :1–3.
A secure-enhanced scheme based on deoxyribonucleic acid (DNA) encoding encryption and probabilistic shaping (PS) is proposed. Experimental results verify the superiority of our proposed scheme in the achievement of security and power gain. © 2020 The Author(s).
He, Bingjun, Chen, Jianfeng.  2021.  Named Entity Recognition Method in Network Security Domain Based on BERT-BiLSTM-CRF. 2021 IEEE 21st International Conference on Communication Technology (ICCT). :508–512.
With the increase of the number of network threats, the knowledge graph is an effective method to quickly analyze the network threats from the mass of network security texts. Named entity recognition in network security domain is an important task to construct knowledge graph. Aiming at the problem that key Chinese entity information in network security related text is difficult to identify, a named entity recognition model in network security domain based on BERT-BiLSTM-CRF is proposed to identify key named entities in network security related text. This model adopts the BERT pre-training model to obtain the word vectors of the preceding and subsequent text information, and the obtained word vectors will be input to the subsequent BiLSTM module and CRF module for encoding and sorting. The test results show that this model has a good effect on the data set of network security domain. The recognition effect of this model is better than that of LSTM-CRF, BERT-LSTM-CRF, BERT-CRF and other models, and the F1=93.81%.
Hutto, Kevin, Mooney, Vincent J..  2021.  Sensing with Random Encoding for Enhanced Security in Embedded Systems. 2021 10th Mediterranean Conference on Embedded Computing (MECO). :1–6.
Embedded systems in physically insecure environments are subject to additional security risk via capture by an adversary. A captured microchip device can be reverse engineered to recover internal buffer data that would otherwise be inaccessible through standard IO mechanisms. We consider an adversary who has sufficient ability to gain all internal bits and logic from a device at the time of capture as an unsolved threat. In this paper we present a novel sensing architecture that enhances embedded system security by randomly encoding sensed values. We randomly encode data at the time of sensing to minimize the amount of plaintext data present on a device in buffer memory. We encode using techniques that are unintelligible to an adversary even with full internal bit knowledge. The encoding is decipherable by a trusted home server, and we have provided an architecture to perform this decoding. Our experimental results show the proposed architecture meets timing requirements needed to perform communications with a satellite utilizing short-burst data, such as in remote sensing telemetry and tracking applications.
Höglund, Joel, Raza, Shahid.  2021.  LICE: Lightweight certificate enrollment for IoT using application layer security. 2021 IEEE Conference on Communications and Network Security (CNS). :19–28.
To bring Internet-grade security to billions of IoT devices and make them first-class Internet citizens, IoT devices must move away from pre-shared keys to digital certificates. Public Key Infrastructure, PKI, the digital certificate management solution on the Internet, is inevitable to bring certificate-based security to IoT. Recent research efforts has shown the feasibility of PKI for IoT using Internet security protocols. New and proposed standards enable IoT devices to implement more lightweight solutions for application layer security, offering real end-to-end security also in the presence of proxies.In this paper we present LICE, an application layer enrollment protocol for IoT, an important missing piece before certificate-based security can be used with new IoT standards such as OSCORE and EDHOC. Using LICE, enrollment operations can complete by consuming less than 800 bytes of data, less than a third of the corresponding operations using state-of-art EST-coaps over DTLS. To show the feasibility of our solution, we implement and evaluate the protocol on real IoT hardware in a lossy low-power radio network environment.
Kabulov, Anvar, Saymanov, Islambek, Yarashov, Inomjon, Muxammadiev, Firdavs.  2021.  Algorithmic method of security of the Internet of Things based on steganographic coding. 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS). :1–5.
In the Internet of Things, it is more important than ever to effectively address the problem of secure transmission based on steganographic substitution by synthesizing digital sensor data. In this case, the degree to which the grayscale message is obscured is a necessary issue. To ensure information security in IoT systems, various methods are used and information security problems are solved to one degree or another. The article proposes a method and algorithm for a computer image in grayscale, in which the value of each pixel is one sample, representing the amount of light, carrying only information about the intensity. The proposed method in grayscale using steganographic coding provides a secure implementation of data transmission in the IoT system. Study results were analyzed using PSNR (Peak Signal to Noise Ratio).
Kaur, Satwinder, Kuttan, Deepak B, Mittal, Nitin.  2021.  An Energy-saving Approach for Error control Codes in Wireless Sensor Networks. 2021 2nd International Conference on Smart Electronics and Communication (ICOSEC). :313—316.
Wireless Sensor Networks (WSNs) have limited energy resource which requires authentic data transmission at a minimum cost. The major challenge is to deploy WSN with limited energy and lifetime of nodes while taking care of secure data communication. The transmission of data from the wireless channels may cause many losses such as fading, noise, bit error rate increases as well as deplete the energy resource from the nodes. To reduce the adverse effects of losses and to save power usage, error control coding (ECC) techniques are widely used and it also brings coding gain. Since WSN have limited energy resource so the selection of ECC is very difficult as both power consumption, as well as BER, has also taken into consideration. This research paper reviews different types of models, their applications, limitations of the sensor networks, and what are different types of future works going to overcome the limitations.
Wadekar, Isha.  2021.  Artificial Conversational Agent using Robust Adversarial Reinforcement Learning. 2021 International Conference on Computer Communication and Informatics (ICCCI). :1–7.
Reinforcement learning (R.L.) is an effective and practical means for resolving problems where the broker possesses no information or knowledge about the environment. The agent acquires knowledge that is conditioned on two components: trial-and-error and rewards. An R.L. agent determines an effective approach by interacting directly with the setting and acquiring information regarding the circumstances. However, many modern R.L.-based strategies neglect to theorise considering there is an enormous rift within the simulation and the physical world due to which policy-learning tactics displease that stretches from simulation to physical world Even if design learning is achieved in the physical world, the knowledge inadequacy leads to failed generalization policies from suiting to test circumstances. The intention of robust adversarial reinforcement learning(RARL) is where an agent is instructed to perform in the presence of a destabilizing opponent(adversary agent) that connects impedance to the system. The combined trained adversary is reinforced so that the actual agent i.e. the protagonist is equipped rigorously.
Liang, Kai, Wu, Youlong.  2021.  Two-layer Coded Gradient Aggregation with Straggling Communication Links. 2020 IEEE Information Theory Workshop (ITW). :1—5.
In many distributed learning setups such as federated learning, client nodes at the edge use individually collected data to compute the local gradients and send them to a central master server, and the master aggregates the received gradients and broadcasts the aggregation to all clients with which the clients can update the global model. As straggling communication links could severely affect the performance of distributed learning system, Prakash et al. proposed to utilize helper nodes and coding strategy to achieve resiliency against straggling client-to-helpers links. In this paper, we propose two coding schemes: repetition coding (RC) and MDS coding both of which enable the clients to update the global model in the presence of only helpers but without the master. Moreover, we characterize the uplink and downlink communication loads, and prove the tightness of uplink communication load. Theoretical tradeoff between uplink and downlink communication loads is established indicating that larger uplink communication load could reduce downlink communication load. Compared to Prakash's schemes which require a master to connect with helpers though noiseless links, our scheme can even reduce the communication load in the absence of master when the number of clients and helpers is relatively large compared to the number of straggling links.
Medeiros, Ibéria, Neves, Nuno.  2020.  Impact of Coding Styles on Behaviours of Static Analysis Tools for Web Applications. 2020 50th Annual IEEE-IFIP International Conference on Dependable Systems and Networks-Supplemental Volume (DSN-S). :55–56.

Web applications have become an essential resource to access the services of diverse subjects (e.g., financial, healthcare) available on the Internet. Despite the efforts that have been made on its security, namely on the investigation of better techniques to detect vulnerabilities on its source code, the number of vulnerabilities exploited has not decreased. Static analysis tools (SATs) are often used to test the security of applications since their outcomes can help developers in the correction of the bugs they found. The conducted investigation made over SATs stated they often generate errors (false positives (FP) and false negatives (FN)), whose cause is recurrently associated with very diverse coding styles, i.e., similar functionality is implemented in distinct manners, and programming practices that create ambiguity, such as the reuse and share of variables. Based on a common practice of using multiple forms in a same webpage and its processing in a single file, we defined a use case for user login and register with six coding styles scenarios for processing their data, and evaluated the behaviour of three SATs (phpSAFE, RIPS and WAP) with them to verify and understand why SATs produce FP and FN.

Stegemann-Philipps, Christian, Butz, Martin V..  2021.  Learn It First: Grounding Language in Compositional Event-Predictive Encodings. 2021 IEEE International Conference on Development and Learning (ICDL). :1–6.
While language learning in infants and toddlers progresses somewhat seamlessly, in artificial systems the grounding of language in knowledge structures that are learned from sensorimotor experiences remains a hard challenge. Here we introduce LEARNA, which learns event-characterizing abstractions to resolve natural language ambiguity. LEARNA develops knowledge structures from simulated sensorimotor experiences. Given a possibly ambiguous descriptive utterance, the learned knowledge structures enable LEARNA to infer environmental scenes, and events unfolding within, which essentially constitute plausible imaginations of the utterance’s content. Similar event-predictive structures may help in developing artificial systems that can generate and comprehend descriptions of scenes and events.
Tahirovic, Alma Ademovic, Angeli, David, Strbac, Goran.  2021.  A Complex Network Approach to Power System Vulnerability Analysis based on Rebalance Based Flow Centrality. 2021 IEEE Power & Energy Society General Meeting (PESGM). :01—05.
The study of networks is an extensively investigated field of research, with networks and network structure often encoding relationships describing certain systems or processes. Critical infrastructure is understood as being a structure whose failure or damage has considerable impact on safety, security and wellbeing of society, with power systems considered a classic example. The work presented in this paper builds on the long-lasting foundations of network and complex network theory, proposing an extension in form of rebalance based flow centrality for structural vulnerability assessment and critical component identification in adaptive network topologies. The proposed measure is applied to power system vulnerability analysis, with performance demonstrated on the IEEE 30-, 57- and 118-bus test system, outperforming relevant methods from the state-of-the-art. The proposed framework is deterministic (guaranteed), analytically obtained (interpretable) and generalizes well with changing network parameters, providing a complementary tool to power system vulnerability analysis and planning.
Obert, James, Loffredo, Tim.  2021.  Efficient Binary Static Code Data Flow Analysis Using Unsupervised Learning. 2021 4th International Conference on Artificial Intelligence for Industries (AI4I). :89—90.
The ever increasing need to ensure that code is reliably, efficiently and safely constructed has fueled the evolution of popular static binary code analysis tools. In identifying potential coding flaws in binaries, tools such as IDA Pro are used to disassemble the binaries into an opcode/assembly language format in support of manual static code analysis. Because of the highly manual and resource intensive nature involved with analyzing large binaries, the probability of overlooking potential coding irregularities and inefficiencies is quite high. In this paper, a light-weight, unsupervised data flow methodology is described which uses highly-correlated data flow graph (CDFGs) to identify coding irregularities such that analysis time and required computing resources are minimized. Such analysis accuracy and efficiency gains are achieved by using a combination of graph analysis and unsupervised machine learning techniques which allows an analyst to focus on the most statistically significant flow patterns while performing binary static code analysis.
Nagata, Daiya, Hayashi, Yu-ichi, Mizuki, Takaaki, Sone, Hideaki.  2021.  QR Bar-Code Designed Resistant against EM Information Leakage. 2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS). :1–4.
A threat of eavesdropping display screen image of information device is caused by unintended EM leakage emanation. QR bar-code is capable of error correction, and its information is possibly read from a damaged screen image from EM leakage. A new design of QR bar-code proposed in this paper uses selected colors in consideration of correlation between the EM wave leakage and display color. Proposed design of QR bar-code keeps error correction of displayed image, and makes it difficult to read information on the eavesdropped image.
Sakk, Eric, Wang, Shuangbao Paul.  2021.  Code Structures for Quantum Encryption and Decryption. 2021 IEEE 5th International Conference on Cryptography, Security and Privacy (CSP). :7—11.
The paradigm of quantum computation has led to the development of new algorithms as well variations on existing algorithms. In particular, novel cryptographic techniques based upon quantum computation are of great interest. Many classical encryption techniques naturally translate into the quantum paradigm because of their well-structured factorizations and the fact that they can be phased in the form of unitary operators. In this work, we demonstrate a quantum approach to data encryption and decryption based upon the McEliece cryptosystem using Reed-Muller codes. This example is of particular interest given that post-quantum analyses have highlighted this system as being robust against quantum attacks. Finally, in anticipation of quantum computation operating over binary fields, we discuss alternative operator factorizations for the proposed cryptosystem.
Harrison, Willie K., Shoushtari, Morteza.  2021.  On Caching with Finite Blocklength Coding for Secrecy over the Binary Erasure Wiretap Channel. 2021 Wireless Telecommunications Symposium (WTS). :1–6.
In this paper, we show that caching can aid in achieving secure communications by considering a wiretap scenario where the transmitter and legitimate receiver share access to a secure cache, and an eavesdropper is able to tap transmissions over a binary erasure wiretap channel during the delivery phase of a caching protocol. The scenario under consideration gives rise to a new channel model for wiretap coding that allows the transmitter to effectively choose a subset of bits to erase at the eavesdropper by caching the bits ahead of time. The eavesdropper observes the remainder of the coded bits through the wiretap channel for the general case. In the wiretap type-II scenario, the eavesdropper is able to choose a set of revealed bits only from the subset of bits not cached. We present a coding approach that allows efficient use of the cache to realize a caching gain in the network, and show how to use the cache to optimize the information theoretic security in the choice of a finite blocklength code and the choice of the cached bit set. To our knowledge, this is the first work on explicit algorithms for secrecy coding in any type of caching network.