DNA-Based Cryptosystem for Connected Objects and IoT Security

Agriculture, being an important industry, needs the use of contemporary technologies in order to increase production. Wireless sensor networks (WSN) can be used to monitor meteorological factors in an agricultural area in this case. This article offers a safe communication system for WSN where each communication step is encrypted using appropriate cryptographic algorithm. Because a WSN consists of a variety of devices with some constraints, conventional encryption methods are ineffective. MUMAP, an ultra-lightweight mutual authentication protocol, is used in the initial phase of a WSN’s connection, when the sensor nodes’ collected data are transmitted to the base node, to verify that the data have been obtained from valid sources. The sink nodes then transmit all of the data obtained from the sensor nodes to the main station or base station. TWINE, a lightweight symmetric encryption method, is used to secure the data package at this step. Both of these methods are very safe against a variety of cyber-attacks. As a result, this framework guarantees the WSN’s security in two critical communication areas. Because MUMAP and TWINE are both lightweight methods, they may be deployed economically with limited resources.KeywordsLightweight cryptographyWireless sensor networkMutual authenticationCyber-physical systemData security

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Infrastructure monitoring systems, such as bridge, tunnel, railway, and so on, are applications which adopt wireless sensor networks (WSNs). Generally, a typical WSN consists of one sink node and sensor nodes. Each sensor node creates a route between itself and the sink node to send sensing data. If attackers succeed to inject fake data or fake route information during a process to create its route, critical problems may occur. For example, the sink node cannot collect sensing data, sensor nodes cannot receive commands from the sink node, and looped routes might be created. To prevent attackers from injecting fake route information, secure routing protocols with authentication tools, such as digital signatures, have been proposed. In this paper, we focus on ISDSR that is a multi hop secure routing protocol. ISDSR guarantees route information that contains a collection of nodes storing a travel path of the received packet. Sensor nodes need more computational processes to generate signatures and to verify signatures comparing with standard multi hop routing protocols, such as AODV and DSR, by applying secure routing protocols to WSNs. In order to run secure routing protocols on a sensor node, developers have to evaluate performances on low performance devices. How long do calculation times take to generate a signature and to verify a signature? How many length of a generated signature does a packet need? To evaluate these performances on real devices, we implement both the signature algorithm of ISDSR as a multi-signature scheme and an RSA-based signature algorithm as a standard signature scheme on a Raspberry Pi. Then, we conduct experiments to measure round trip times including calculation times between two nodes and packet sizes.

Wireless sensor networks (WSNs) are increasingly being used for data monitoring and collection purposes. Typically, they consist of a large number of sensor nodes that are used remotely to collect data about the activities and conditions of a particular area, for example, temperature, pressure, motion. Each sensor node is usually small, inexpensive, and relatively easy to deploy compared to other sensing methods. For this reason, WSNs are used in a wide range of applications and industries. However, WSNs are vulnerable to different kinds of security threats and attacks. This is primarily because they are very limited in resources like power, storage, bandwidth, and processing power that could have been used in developing their defense. To ensure their security, an effective Intrusion detection system (IDS) need to be in place to detect these attacks even under these constraints. Today, traditional IDS are less effective as these malicious attacks are becoming more intelligent, frequent, and complex. Denial of service (DOS) attack is one of the main types of attacks that threaten WSNs. For this reason, we review related works that focus on detecting DoS attacks in WSN. In addition, we developed and implemented several Deep learning (DL) based IDS. These systems were trained on a specialized dataset for WSNs called WSN-DS in detecting four types of DoS attacks that affects WSNs. They include the Blackhole, Grayhole, Flooding, and Scheduling attacks. Finally, we evaluated and compared the results and we discuss possible future works.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

Sensors have varied constraints, which makes the network challenging for communicating with its peers. In this paper, an extension to the security of physical layer of a predictive sensor network model using the ant system is proposed. The Denial of Service (DoS) attack on sensor networks not only diminishes the network performance but also affects the reliability of the information making detection of a DoS threat is more crucial than recovering from the attack. Hence, in this paper, a novel approach in detecting the DoS attack is introduced and analyzed for a variety of scenarios. The DoS attack is dependent on the vulnerabilities in each layer, with the physical layer being the lowest layer and the first to be attacked by jammers. In this paper, the physical layer DoS attack is analyzed and a defense mechanism is proposed. Classification of the jammer under various attack scenarios is formulated to predict the genunity of the DoS attacks on the sensor nodes using receiver operating characteristics (ROC). This novel approach helps in achieving maximum reliability on DoS claims improving the Quality of Service (QoS) of WSN.

Smart connected consumer devices employing IoT as the backbone are becoming a part of our day-to-day life. These products are fascinating to everyone but bear a dark side of becoming a threat to consumers and vendors. Users and smart devices manufacturers are losing finances as well as confidential data to the adversary, mainly due to employing insecure authentication methods. There are several reported incidences of such security breaches in IoT-enabled systems. The IoT industry finds it difficult to catch up with fast developments and innovations in lightweight protocols, hardware devices, and authentication mechanisms proposed explicitly for IoT-based products. Furthermore, they are reluctant to embed the evolutions, fearing that consumers may not find the new product budget-friendly. Smart cities, smart homes, smart cars and smart grids are gaining attention from various sections of society with no knowledge of the vulnerabilities of these revolutionary systems. The chapter considers IoT systems from the perspectives of a consumer, a vendor, and a researcher to figure out the present scenario, and give future directions to the authentication-related security issues in IoT subsystems. The device-to-user authentication while accessing connected consumer devices is the area in IoT systems that needs serious attention from academia, the biometric community, and the biometric industry. Also, automated payment systems implemented in smart consumer products are at risk of threats from malicious attackers. Even though there are alliances to brainstorm the specific problem and standardization of protocols for IoT infrastructure, there is slow growth in incorporating the most secure and cost-effective solution to security issues in IoT. We must understand the vulnerabilities and loopholes in IoT infrastructure and correctly design mitigation techniques to build a robust system. The chapter provides a precise investigation of the current scenario to integrate biometric authentication in IoT applications and systems along with the required techniques to mitigate software and hardware-level vulnerabilities in these systems. The study classifies IoT systems and applications into seven categories. The chapter reviews the current research outcomes in this direction and pinpoints their pros and cons while implementing them into future IoT products. It is also required to decide the best biometric modality and implementation mechanisms that are convenient and pocket friendly to the consumers. In addition, the chapter also discusses various biometric traits from the IoT perspective and suggests the best modalities for such systems.

In today’s world, one of the most severe attacks that wireless sensor networks (WSNs) face is a Black-Hole (BH) attack which is a type of Denial of Service (DoS) attack. This attack blocks data and injects infected programs into a set of sensors in a group to capture packets before reached to the target. Therefore, raw data in the BH region is thwarted and is unable to reach its destination. The network is susceptible to various types of attacks as it is accessible to all types of users and minimizing the energy depletion without compromising the network lifetime is an NP-hard problem. Even though numerous protocols came into effect to overcome the BH attack and to enhance the security of packet delivery in WSNs, Simulated Annealing Black-hole attack Detection (SABD) based Enhanced Gravitational Search Algorithm (EGSA) is yet another implemented strategy to reduce the BH attacks. EGSA-SABD detects and isolates the BH infectors in WSNs. Initially, sensor nodes are hierarchically clustered using similar residual energy to reduce energy consumption. Then, the BH attack possibility in a deployed node is evaluated to find the existence of BH nodes in the region. In the end, EGSA-SABD is employed to detect and quarantine BH attackers in WSNs. The performance of EGSA-SABD is evaluated with certain metrics such as BH attack detection probability rate (BHatt_Prate), energy consumption (Ec), Duration of BH attack detection (Attduration), Packet delivery ratio (Pdr). Based on the experimental observations, the EGSA-SABD outperforms the BHatt_Prate by 13% and also reduces the energy consumption by 21%.

Code dissemination is one of the important services of wireless sensor networks (WSNs). Securing the process of code dissemination is essential in some certain WSNs applications, state-of-the-art secure code dissemination protocols for WSNs aim for the efficient source authentication and integrity verification of code image, however, due to the resource constrains of WSNs and the epidemic behavior of the code dissemination system, existing secure code dissemination protocols are vulnerable to Denial of Service (DoS) attacks when sensor nodes can be compromised (insider DoS attacks). In this paper, we identify five different basic types of DoS attacks exploiting the epidemic propagation strategies used by Deluge. They are (1) Higher-version Advertisement attack, (2) False Request attack, (3) Larger-numbered Page attack, (4) Lower-version Adv attack, and (5) Same-version Adv attack. Simulation shows these susceptibilities caused by above insider DoS attacks. Some simple models are also proposed which promote understanding the problem of insider DoS attacks and attempt to quantify the severity of these attacks in the course of code dissemination in WSNs.

Technology is transforming rapidly. Security during data transmission is an increasingly critical and essential factor for the integrity and confidentiality of data in the financial domain, such as e-commerce transactions and bank transactions, etc. We cannot overestimate the importance of encryption/decryption of information in the digital economy. The need to strengthen and secure the digital economy is urgent. Cryptography maintains the security and integrity of data kept on computers and data communicated over the internet using encryption/decryption. A new concept in cryptography named DNA cryptography has attracted the interest of information security professionals. The DNA cryptography method hides data using a DNA sequence, with DNA encryption converting binary data into the DNA sequence. Deoxy Ribonucleic Acid (DNA) is a long polymer strand having nitrogen bases adenine (A), thymine (T), cytosine (C), and guanine (G), which play an important role in plain text encoding and decoding. DNA has high storage capacity, fast processing, and high computation capacity, and is more secure than other cryptography algorithms. DNA cryptography supports both symmetric and asymmetric cryptography. DNA cryptography can encrypt numeric values, English language and unicast. The main aim of this paper is to explain different aspects of DNA cryptography and how it works. We also compare different DNA algorithms/methods proposed in a previous paper, and implement DNA cryptography using one-time pad (OTP) and amino acid sequence using java language. OTP is used for symmetric key generation and the DNA sequence is converted to an amino acid sequence to create confusion.

In recent times, the medical image processing solves several clinical issues by inspecting the visual images, which are generated in the clinical health care units. The main objective of the research is to gain valuable information from the images for better clinical diagnosis. In the biomedical engineering domain, the medical image analysis is an emerging research topic. In the recent decades, the use of medical images is highly growing, which are acquired from different image modalities; so, there is a necessity for data compression for transmission, storage, and management of digital medical image datasets. Hence, the machine learning methods are effective for medical image analysis, where the deep learning models are used in the machine learning tools for automatically learning the feature vectors from the huge medical datasets. The automated deep learning models are effective compared to the conventional handcrafted features. In addition to this, a wireless sensor network (WSN) is used to create a primary health care scheme, which brings patient data together and expands the medical conveniences, whereas the WSN design must comprise of sensor nodes, because it consumes less power and resources at a relatively low cost; so, it is essential for implementing the Raspberry Pi-based WSN nodes. The sensor nodes are important for limited battery capacity and to transmit the vast amount of medical data. The proposed work is broadly classified into two categories such as (i) the medical image compression algorithm is developed using the deep learning model based on autoencoders and restricted Boltzmann machines (RBM) and (ii) implementation of the WSN sensors nodes with Raspberry Pi and Messaging Queue Telemetry Transport (MQTT) Internet of Things (IoT) protocol for secure transmission of the medical images. The experimental results are evaluated using the standard performance metrics like peak signal to noise ratio (PSNR) and presented a Real-Time Linux (RTL) implementation of the design. The proposed model showed 10 dB to 15 dB improvement in the PSNR value, while transmitting the medical images, which is better compared to the existing model.

To measure the degree of basic service of wireless sensor network (WSN) with denial of service (DoS) attacks, it is necessary to evaluate survivability of WSN. This paper presents new method based on services and Markov Chain. It distinguishes services, analyzes influence of services under DoS attacks, gets the formula of survivability. Probability of states is obtained by markov chain, then the quantitve survivability is getted in different states. Simulations prove that DoS attacks obviously decrease the survivability of WSN, but adding node energy and improving node density in certain range can reduce the influence of DoS attacks.

The miniaturization of sensors, the increasingly low cost, the wide range of types of sensors available as well as the wireless communication medium used, allow sensor networks to develop in several fields of application. Sensor networks can be very useful in many applications when it comes to collecting and processing information from the environment. In addition, today these micro devices are among the main components of the Internet of Things (IoT) paradigm. Several constraints block the proper functioning of the wireless sensor network. These limitations motivate a large part of research problems in the field of wireless sensor networks (WSNs), in particular the energy and security constraints that are a fundamental problem. In sensor networks, it is essential that each sensor node and base station can verify that the data received was sent by a trusted sender and not by an adversary who tricked legitimate nodes into accepting fake data. False data can change the way a network might be predicted. Data integrity should be maintained. The data must not change and the precise data must reach the end of the user. In this paper, we tackle security problems in WSN. And we focus on protection against so-called “denial of service” attacks. So the aim of the work presented is therefore to propose a set of effective detection and reaction methods to denial of service attacks, while saving or distributing the energy consumption of the sensors as well as possible to extend the network's operating time as much as possible.

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism

IoT or The Internet of Things is the latest modern-day technology that is currently transforming the society in which we live in. Various opportunities in IoT have increased the demand for the need of IoT enabled technologies to a great extent. Bluetooth Low Energy (BLE) is one such technology which helped advance the scope of IoT enabled technologies in smart cities and various other corporate organizations. Asset tracking, person location tracking are some of the key use cases of the BLE technology. Hence integration of BLE technology has helped IoT to reach its technological advancement to a next level. With the advancements in technology, many researches in services like indoor localization had been carried out. Indoor localization is that ability of technology to actually find the exact location of a person or device existing in an indoor setting. So this technology feature have been accepted and put into use in sectors like industries, building management, health sectors and so on. Hence this technology is now integrated into latest smart cities so as to maximize the utilization of the technology to the fullest. Security is one major concern with the emergence of a technology. Many algorithms or protocols help to curb the security threats on a major scale. In this paper we had also discuss on some security issues faced in IoT system to know how effectively and carefully one should implement and design an IoT system to ensure that there are no security flaws. This paper focuses on applications of IoT and BLE technologies with some of its security threats like Denial of Service (DoS) attacks with a proposal for improvement in boarding passes issued to passengers in airports that enable passenger tracking possible in airports around the world. Section I consists of the introduction which describes the brief idea on the paper followed by Section II which is the literature review which consists of applications, security and other various aspects of IoT and BLE systems. Section III is a proposal for improved boarding pass system and in the end is Section IV which concludes the paper with a detailed conclusion.