DCGit: Decentralized Internet Hosting for Software Development

The Internet of Things (IoT) is developing as a novel phenomenon that is applied in the growth of several crucial applications. However, these applications continue to function on a centralized storage structure, which leads to several major problems, such as security, privacy, and a single point of failure. In recent years, blockchain (BC) technology has become a pillar for the progression of IoT-based applications. The BC technique is utilized to resolve the security, privacy, and single point of failure (third-part dependency) issues encountered in IoT applications. Conversely, the distributed denial of service (DDoS) attacks on mining pools revealed the existence of vital fault lines amongst the BC-assisted IoT networks. Therefore, the current study designs a hybrid Harris Hawks with sine cosine and a deep learning-based intrusion detection system (H3SC-DLIDS) for a BC-supported IoT environment. The aim of the presented H3SC-DLIDS approach is to recognize the presence of DDoS attacks in the BC-assisted IoT environment. To enable secure communication in the IoT networks, BC technology is used. The proposed H3SC-DLIDS technique designs a H3SC technique by integrating the concepts of Harris Hawks optimization (HHO) and sine cosine algorithm (SCA) for feature selection. For the intrusion detection process, a long short-term memory auto-encoder (LSTM-AE) model is utilized in this study. Finally, the arithmetic optimization algorithm (AOA) is implemented for hyperparameter tuning of the LSTM-AE technique. The proposed H3SC-DLIDS method was experimentally validated using the BoT-IoT database, and the results indicate the superior performance of the proposed H3SC-DLIDS technique over other existing methods, with a maximum accuracy of 99.05%.

On the Internet, web applications are served from a centralized location i.e., server, for higher maintainability. However, in the centralized architecture, if there is an occurrence of server failure or crash, the web applications cannot be serve to the end-users until the server goes live again. In addition, in the existing centralized architecture for web hosting services, integrity of the hosted websites entirely relies on the third-party applications which checks for any possible threats in the system. In order to provide data integrity within the system and to overcome the above-mentioned single point of failure, we proposed the decentralized solution for hosting web applications, which provides more data availability to the end-users and maintains the integrity of the data. The proposed model makes use of the Interplanetary File System (IPFS) for storing and retrieving web applications, which provides high availability and reliability. In addition, the proposed model uses the Blockchain Technology for authenticity and confidentiality. The smart contracts are deploy on the Ethereum Block chain, which aids the service provider to manage the hosting service system. The proposed model also comparatively decreases the time taken to transfer the file over the IPFS using optimal path-finding algorithm. The proposed algorithm has a lesser time complexity when compared to the Bitswap protocol used in IPFS. The use of blockchain with IPFS cumulatively provides better authenticity via Ethereum Smart Contracts, which reduces risk and failure.

The Internet of Things (IoT) is a network of sensors that helps collect data 24/7 without human intervention. However, the network may suffer from problems such as the low battery, heterogeneity, and connectivity issues due to the lack of standards. Even though these problems can cause several performance hiccups, security issues need immediate attention because hackers access vital personal and financial information and then misuse it. These security issues can allow hackers to hijack IoT devices and then use them to establish a Botnet to launch a Distributed Denial of Service (DDoS) attack. Blockchain technology can provide security to IoT devices by providing secure authentication using public keys. Similarly, Smart Contracts (SCs) can improve the performance of the IoT–blockchain network through automation. However, surveyed work shows that the blockchain and SCs do not provide foolproof security; sometimes, attackers defeat these security mechanisms and initiate DDoS attacks. Thus, developers and security software engineers must be aware of different techniques to detect DDoS attacks. In this survey paper, we highlight different techniques to detect DDoS attacks. The novelty of our work is to classify the DDoS detection techniques according to blockchain technology. As a result, researchers can enhance their systems by using blockchain-based support for detecting threats. In addition, we provide general information about the studied systems and their workings. However, we cannot neglect the recent surveys. To that end, we compare the state-of-the-art DDoS surveys based on their data collection techniques and the discussed DDoS attacks on the IoT subsystems. The study of different IoT subsystems tells us that DDoS attacks also impact other computing systems, such as SCs, networking devices, and power grids. Hence, our work briefly describes DDoS attacks and their impacts on the above subsystems and IoT. For instance, due to DDoS attacks, the targeted computing systems suffer delays which cause tremendous financial and utility losses to the subscribers. Hence, we discuss the impacts of DDoS attacks in the context of associated systems. Finally, we discuss Machine-Learning algorithms, performance metrics, and the underlying technology of IoT systems so that the readers can grasp the detection techniques and the attack vectors. Moreover, associated systems such as Software-Defined Networking (SDN) and Field-Programmable Gate Arrays (FPGA) are a source of good security enhancement for IoT Networks. Thus, we include a detailed discussion of future development encompassing all major IoT subsystems.

a serious nuisance for network security could be a Distributed Denial of Service (DDoS) attack. The advent of the technological era has also brought along the threat of DDoS attacks for a variety of services and applications that use the Internet. Firms can incur huge financial losses even if there is a disruption in services for a fraction of a period. Analogous to a DDoS attack is the Flash Crowd (FC), in which a particular service is assessed by many legitimate users concurrently, which results in the denial of service. Overloading of network resources is a common issue associated with both these events, which impact CPU, available bandwidth, and memory for legitimate users, thereby leading to limited accessibility. Many researchers have put effort to differentiate between these two kinds of traffic, but none could come up with an effective solution. In this study, we propose an adaptive agent-based model, known as an adaptive application layer flooding protection (AALFP) model, for DDoS and FC flooding attacks. The AALFP model is aimed to protect the network application layer (NAL) against such attacks. Importantly, the model distinguishes and separates normal from abnormal traffic, and then blocks illegitimate traffic. Note that, to operate two traffic filters, the agent relies on the following three parameters of normal traffic intensity, traffic attack behaviour, and IP address history log. An example scenario is provided to simulate the model's application.

Abstract: DDoS attacks also known as distributed denial of service (DDoS) attacks have emerged as one of the most serious and fastest-growing threats on the Internet. Denial-of-service (DDoS) attacks are an example of cyber-attacks that target a specific system or network in an attempt to render it inaccessible or unusable for a period of time. As a result improving the detection of diverse types of DDoS cyber threats with better algorithms and higher accuracy while keeping the computational cost under control has become the most significant component of detecting DDoS cyber threats. DDoS (distributed denial-of-service) attack originates from many sources scattered over multiple network locations. DoS attacks are primarily motivated by the desire to significantly degrade the performance or completely consume a certain resource and a process to exploit a machine defect and cause failure of a processing or exhausting the system resources by exploiting a system flaw. Yet another method of assaulting the target system is to flood the network and monopolies it so preventing anyone else from utilizing it. DDoS attack has a high impact on crashing the network resources making the target servers unable to support the valid users.

Today Distributed Denial of Service (DDoS) attacks are causing major threat to perform online business over the Internet. Our previous work proposed an automated model with a new packet marking technique and agent design to counteract DDoS within a single ISP domain. Our approach has many features that are required to minimize the DDoS attacks. For example, our model is invoked only during attack times, identifies the approximate source of attack with a single packet even in case of spoofed source address, identifies different attack signatures for different attacking sources, prevents the attack nearest to the attacking source, has very fast response for any changes in attack traffic pattern, is simple in its implementation and can be incrementally deployed. Though the proposed model has several advantages, prevention of the attack is limited to a single ISP domain. In this paper we extend our model to prevent DDoS attacks in multiple ISP domains by retaining all the advantages achieved in our previous work. We also propose a practical implementation of the extended model with a presently working architecture.

In the realm of the fifth-generation (5G) wireless cellular networks, renowned for their dense connectivity, there lies a substantial facilitation of a myriad of Internet of Things (IoT) applications, which can be supported by the massive machine-type communication (MTC) technique, a fundamental communication framework. In some scenarios, a large number of machine-type communication devices (MTCD) may simultaneously enter the communication coverage of a target base station. However, the current handover mechanism specified by the 3rd Generation Partnership Project (3GPP) Release 16 incurs high signaling overhead within the access and core networks, which may have negative impacts on network efficiency. Additionally, other existing solutions are vulnerable to malicious attacks such as Denial of Service (DoS), Distributed Denial of Service (DDoS) attacks, and the failure of Key Forward Secrecy (KFS). To address this challenge, this paper proposes an efficient and secure handover authentication protocol for a group of MTCDs supported by blockchain technology. This protocol leverages the decentralized nature of blockchain technology and combines it with certificateless aggregate signatures to mutually authenticate the identity of a base station and a group of MTCDs. This approach can reduce signaling overhead and avoid key escrow while significantly lowering the risk associated with single points of failure. Additionally, the protocol protects device anonymity by encrypting device identities with temporary anonymous identity markers with the Elliptic Curve Diffie-Hellman (ECDH) to abandon serial numbers to prevent linkage attacks. The resilience of the proposed protocol against predominant malicious attacks has been rigorously validated through the application of the BAN logic and Scyther tool, underscoring its robust security attributes. Furthermore, compared to the existing solutions, the proposed protocol significantly reduces the authentication cost for a group of MTCDs during handover, while ensuring security, demonstrating commendable efficiency.

<span lang='EN-AU'>This paper proposes the new method for improving the accuracy of detection of DDoS attacks on the SDN by utilizing control plane using Six-Sigma method. Software-Defined Networking (SDN) is a centralized network control system. This system offers flexibility on receiving, processing and forwarding packets between subnetworks. The centralized system of SDN, which separates control plane and data plan, has an immense number of advantages, but it also has the risk of becoming a single point of network failure. Distributed Denial of Service (DDoS) attack is the major issues faced in the security aspect of SDN. This attack can make network resources unreachable by the real packets. The widely known method has been implemented on SDN for avoiding a DDoS attack is Three-Sigma method. Three-Sigma method uses a threshold value to determine the existence of a DDoS attack. However, this method has drawbacks regarding accuracy in determining the DDoS attack. The main contribution of this paper is utilizing central control plane of SDN for improving accuracy on detecting the DDoS attack. Several experiments performed for proving the concept. The result shows the new method can improve the accuracy of detection of a DDoS attack, either in constant or fluctuating traffic, by reducing the false positive. The performance is about 50% more accurate than the previous method.</span>

Modern methods of analyzing and protecting network infrastructure against DDoS (Distributed Denial of Service) attacks are discussed. A DDoS detection model has been developed using statistical techniques, which highlights the main stages of the attacks and key characteristics of network traffic that are crucial for detecting an attack. Potential and attack power are introduced as main concepts in assessing DDoS activity. To identify the type of attack, it is suggested to increase the sensitivity of the model by identifying key characteristics that distinguish between different attack stages. The features of various DDoS attack types, such as UDP Flood, UDP Reflection/Amplification, and TCP SYN Flood, are considered. A framework for modeling DDoS network attacks has been created. DDoS attacks including UDP Flood, UDP Reflection/Amplification and TCP SYN Flood were simulated using traffic data collected via the NetFlow protocol. The proposed attack characteristics, including speed, flow volume, and flow rate, allowed us to evaluate the attack's power and consider how to change the key characteristics of network traffic.

Nowadays, cloud-based storage systems play a vital role in IoT data storage, processing, and sharing. Despite its contribution, the current cloud-based architecture may cause severe data leakage or jeopardize user privacy. Meanwhile, the cloud-based architecture heavily relies on a trusted third-party auditor (TPA) and runs in a centralized control manner. However, the TPA may not be a completely trustworthy entity, and a single point of failure might cause the centralized system to collapse. Fortunately, with the advent of blockchain technology, the decentralized storage model has gained popularity. A decentralized storage system successfully eradicates the rule of TPA, solves the problem of a single point of failure, and has many advantages over a centralized control architecture, such as low storage prices and high throughput. This study offers a blockchain-based decentralized distributed storage and sharing scheme that provides end-to-end encryption and fine-grained access control. In our proposed IoTChain model, fine-grained permission is based on attribute-based access control (A-BAC) policy by employing the Ethereum blockchain as an auditable access control layer. Smart contracts are tailored for the IoTChain model, which combines the Ethereum blockchain and the interplanetary file system (IPFS). We used an advanced encryption standard (AES) for encryption and the elliptic curve Diffie-Hellman key exchange protocol for secret key sharing between data owners and users. Also, the proof-of-work (PoW) consensus mechanism is replaced with a proof-of-authority (PoA) to minimize system transaction cost and boost system throughput. Additionally, our solution has been tested on the Ethereum official test network Rinkeby, and the results demonstrate that our approach is realistic and economical on the IoT data.

In autonomous distributed environments such as peer to peer file sharing system, some egoistic nodes could possibly collapse the system. Thus to meet the various users requirement in a distributed peer to peer networks, an incentive mechanisms is used based on blockchain technology. In this paper, we propose a new method on how to increase the efficiency of the P2P file sharing system through IPFS and blockchain, which includes trustworthiness and proximity awareness during the process of file transfer. We also present the issues faced by the blockchain technology and how to overcome such issues through IPFS. Peer-to-peer (P2P) based Interplanetary File System (IPFS) is a technology of sharing resources or files in a distributed system, which contains a cluster of hashed files in each node of the system. A user who wants to retrieve any of these hashed files can simply call the hash of the file it wants. The high-throughput problem of an individual IPFS user is to establish the role of content service providers, thus IPFS uses the concept of Filecoin that offers storage on a distributed network of local providers. This Filecoin provider’s i.e., the miners who cooperate for successful transfer of resources are rewarded for their services. The service provided during the process of file transfer and the security strength and some of the incentives based on IPFS are discussed in this paper.

Driven by information technology, data trading promotes cross-industry collaboration and uncovers value by integrating multi-source data, yet it requires encryption and access controls to address increasing data security challenges. Existing schemes largely rely on attribute-based unilateral access control to protect data, facing challenges such as data source authenticity and requester autonomy. Bilateral access control requires data providers and requesters to define access policies, allowing decryption only when both policies match, often facilitated by cryptographic primitives such as matchmaking encryption (ME). However, the current bilateral schemes still face challenges of sensitive data leakage, unauthorized data access, and single points of failure. To date, no existing scheme has addressed these issues simultaneously. In this paper, we propose a blockchain-based, sanitizable and bilateral access control scheme with privacy-preserving (SBAC-PP) for data trading. Specifically, by extending ME via hash functions and policy-hidden identifiers to achieve a bilateral access control with privacy-preserving. Secondly, by combining access control encryption (ACE), we design a ciphertext sanitization mechanism to prevent unauthorized data access. Furthermore, by integrating SBAC-PP with blockchain (BC) and the interplanetary file system (IPFS), we use smart contracts for trusted matching and pre-decryption, and store encrypted data in IPFS, thereby achieving decentralized data management to avoid single points of failure. Finally, we analyze the security of SBAC-PP and evaluate its performance to demonstrate its efficiency and practicality.

A Software-defined network paradigm provides flexibility and programmability to deal with the growing users of future networks. As a result of the centralized control attribute, it could be regarded as a single point of failure that is vulnerable to various forms of attacks, such as Distributed denial of service (DDOS) attacks. This study attempts to show a mathematical representation of DDOS attacks in SDN, together with how some five-tuple features contribute to the attacks. The studied features were used to detect DDOS using a random forest classifier. The result shows 96.3% detection accuracy and 96.45% precision.

In the last decade patient management systems or eHealth has gained huge attraction with researchers. eHealth spans from the remote access of medical records to actual data exchange of remote patient's data of their body sensors. In this paper we propose a decentralized application model that uses Ethereum private Blockchain, Inter-Planetary File System (IPFS), and associated web technologies that aim to help healthcare providers, policymakers, and research organizations in Nepal. It presents the outcome of a survey conducted among the general public and a focus group discussion with medical doctors in relation to their current practices and limitations in storing and sharing patients' medical histories for examinations or treatments. The paper concludes with why blockchain technologies can be a better option for public and private healthcare institutions as well as medical practitioners to store and share patient records to deliver timely and quality healthcare services in a resource-poor country like Nepal.

Blockchain technology is receiving increased attention over the past few years. Blockchain is essentially a decentralized, distributed digital ledger in which data is organized into blocks. The data stored in Blockchain is secured using cryptographic properties. Storage is the main concern when the volume of transactions increases. Handling data in huge amount may lead to increased overheads as data can only be appended to it, and the previous data cannot be deleted. So, it led to the development of the InterPlanetary File System (IPFS). IPFS is a distributed database with peer-to-peer file system and uses content-addressable hash value which is used to verify the data. Using IPFS, one can upload the data in the form of text, images as well as videos. While uploading the data in IPFS, the protocol returns a unique hash value for the data via gateway. This hash value is securely stored in Blockchain. Based on the hash value, the data can be retrieved. In IPFS, data is distributed among the network participants locally. The proposed work combines both IPFS and Blockchain technologies. This scheme uses IPFS for storing large volume of data, removes duplication, share files, and hosts them. The proposed work minimizes the central server storage space, improves data security by using unique content-addressable hashes for data verification and also reduces computing power.