Biblio

Swarm robotics, a combination of Swarm intelligence and robotics, is inspired from how the nature swarms, such as flock of birds, swarm of bees, ants, fishes etc. These group behaviours show great flexibility and robustness which enable the robots to perform various tasks like pattern formation, rescue and military operation, space expedition etc. This paper discusses an algorithm for forming patterns, which are English alphabets, by identical robots, in a finite amount of time and also analyses outcome of the algorithm. In order to implement the algorithm, 9 identical circular robots of diameter 15 cm are used, each having a Node MCU module and a rotary encoder attached to one wheel of the robot. The robots are initially placed at the centres of an imaginary 3×3 grid, on a white sheet of paper, of dimensions 250cm × 250 cm. All the robots are connected to the laptop's network via wifi and data send from the laptop is received by the Node MCU modules. This data includes the distance to be moved and the angle to be turned by each robot in order to form the letter. The rotary encoders enable the robot to move specific distances and turn specific angles, with high accuracy, by real time feedback. The algorithm is written in Python and image processing is done using OpenCV. Certain approximations are used in order to implement collision avoidance. Finally after calibration, the word given as input, is formed letter by letter, using these 9 identical robots.

Mobile Ad-hoc Networks are dynamic in nature and do not have fixed infrastructure to govern nodes in the networks. The mission lies ahead in coordinating among such dynamically shifting nodes. The root problem of identifying and isolating misbehaving nodes that refuse to forward packets in multi-hop ad hoc networks is solved by the development of a comprehensive system called Audit-based Misbehavior Detection (AMD) that can efficiently isolates selective and continuous packet droppers. AMD evaluates node behavior on a per-packet basis, without using energy-expensive overhearing techniques or intensive acknowledgment schemes. Moreover, AMD can detect selective dropping attacks even in end-to-end encrypted traffic and can be applied to multi-channel networks. Game theoretical approaches are more suitable in deciding upon the reward mechanisms for which the mobile nodes operate upon. Rewards or penalties have to be decided by ensuring a clean and healthy MANET environment. A non-routine yet surprise alterations are well required in place in deciding suitable and safe reward strategies. This work focuses on integrating a Audit-based Misbehaviour Detection (AMD)scheme and an incentive based reputation scheme with game theoretical approach called Supervisory Game to analyze the selfish behavior of nodes in the MANETs environment. The proposed work GAMD significantly reduces the cost of detecting misbehavior nodes in the network.

While the Internet of Things (IoT) is embraced as important tools for efficiency and productivity, it is becoming an increasingly attractive target for cybercriminals. This work represents the first endeavor to develop practical Puncturable Attribute Based Encryption schemes that are light-weight and applicable in IoTs. In the proposed scheme, the attribute-based encryption is adopted for fine grained access control. The secret keys are puncturable to revoke the decryption capability for selected messages, recipients, or time periods, thus protecting selected important messages even if the current key is compromised. In contrast to conventional forward encryption, a distinguishing merit of the proposed approach is that the recipients can update their keys by themselves without key re-issuing from the key distributor. It does not require frequent communications between IoT devices and the key distribution center, neither does it need deleting components to expunge existing keys to produce a new key. Moreover, we devise a novel approach which efficiently integrates attribute-based key and punctured keys such that the key size is roughly the same as that of the original attribute-based encryption. We prove the correctness of the proposed scheme and its security under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. We also implement the proposed scheme on Raspberry Pi and observe that the computation efficiency of the proposed approach is comparable to the original attribute-based encryption. Both encryption and decryption can be completed within tens of milliseconds.

This work explores attack and attacker profiles using a VoIP-based Honeypot. We implemented a low interaction honeypot environment to identify the behaviors of the attackers and the services most frequently used. We watched honeypot for 180 days and collected 242.812 events related to FTP, SIP, MSSQL, MySQL, SSH, SMB protocols. The results provide an in-depth analysis about both attacks and attackers profile, their tactics and purposes. It also allows understanding user interaction with a vulnerable honeypot environment.

The objective of the Honeypot security system is a mechanism to identify the unauthorized users and intruders in the network. The enterprise level security can be possible via high scalability. The whole theme behind this research is an Intrusion Detection System and Intrusion Prevention system factors accomplished through honeypot and honey trap methodology. Dynamic Configuration of honey pot is the milestone for this mechanism. Eight different methodologies were deployed to catch the Intruders who utilizing the unsecured network through the unused IP address. The method adapted here to identify and trap through honeypot mechanism activity. The result obtained is, intruders find difficulty in gaining information from the network, which helps a lot of the industries. Honeypot can utilize the real OS and partially through high interaction and low interaction respectively. The research work concludes the network activity and traffic can also be tracked through honeypot. This provides added security to the secured network. Detection, prevention and response are the categories available, and moreover, it detects and confuses the hackers.

Modern software development and deployment practices encourage complexity and bloat while unintentionally sacrificing efficiency and security. A major driver in this is the overwhelming emphasis on programmers' productivity. The constant demands to speed up development while reducing costs have forced a series of individual decisions and approaches throughout software engineering history that have led to this point. The current state-of-the-practice in the field is a patchwork of architectures and frameworks, packed full of features in order to appeal to: the greatest number of people, obscure use cases, maximal code reuse, and minimal developer effort. The Office of Naval Research (ONR) Total Platform Cyber Protection (TPCP) program seeks to de-bloat software binaries late in the life-cycle with little or no access to the source code or the development process.

Attack graph approach is a common tool for the analysis of network security. However, analysis of attack graphs could be complicated and difficult depending on the attack graph size. This paper presents an approximate analysis approach for attack graphs based on Q-learning. First, we employ multi-host multi-stage vulnerability analysis (MulVAL) to generate an attack graph for a given network topology. Then we refine the attack graph and generate a simplified graph called a transition graph. Next, we use a Q-learning model to find possible attack routes that an attacker could use to compromise the security of the network. Finally, we evaluate the approach by applying it to a typical IT network scenario with specific services, network configurations, and vulnerabilities.

Nowadays, Vehicular ad hoc network confronts many challenges in terms of security and privacy, due to the fact that data transmitted are diffused in an open access environment. However, highest of drivers want to maintain their information discreet and protected, and they do not want to share their confidential information. So, the private information of drivers who are distributed in this network must be protected against various threats that may damage their privacy. That is why, confidentiality, integrity and availability are the important security requirements in VANET. This paper focus on security threat in vehicle network especially on the availability of this network. Then we regard the rational attacker who decides to lead an attack based on its adversary's strategy to maximize its own attack interests. Our aim is to provide reliability and privacy of VANET system, by preventing attackers from violating and endangering the network. to ensure this objective, we adopt a tree structure called attack tree to model the attacker's potential attack strategies. Also, we join the countermeasures to the attack tree in order to build attack-defense tree for defending these attacks.

Now a days, Cloud computing has brought a unbelievable change in companies, organizations, firm and institutions etc. IT industries is advantage with low investment in infrastructure and maintenance with the growth of cloud computing. The Virtualization technique is examine as the big thing in cloud computing. Even though, cloud computing has more benefits; the disadvantage of the cloud computing environment is ensuring security. Security means, the Cloud Service Provider to ensure the basic integrity, availability, privacy, confidentiality, authentication and authorization in data storage, virtual machine security etc. In this paper, we presented a Local outlier factors mechanism, which may be helpful for the detection of Distributed Denial of Service attack in a cloud computing environment. As DDoS attack becomes strong with the passing of time, and then the attack may be reduced, if it is detected at first. So we fully focused on detecting DDoS attack to secure the cloud environment. In addition, our scheme is able to identify their possible sources, giving important clues for cloud computing administrators to spot the outliers. By using WEKA (Waikato Environment for Knowledge Analysis) we have analyzed our scheme with other clustering algorithm on the basis of higher detection rates and lower false alarm rate. DR-LOF would serve as a better DDoS detection tool, which helps to improve security framework in cloud computing.

With the development of Internet technology, software vulnerabilities have become a major threat to current computer security. In this work, we propose the vulnerability detection for source code using Contextual LSTM. Compared with CNN and LSTM, we evaluated the CLSTM on 23185 programs, which are collected from SARD. We extracted the features through the program slicing. Based on the features, we used the natural language processing to analysis programs with source code. The experimental results demonstrate that CLSTM has the best performance for vulnerability detection, reaching the accuracy of 96.711% and the F1 score of 0.96984.

To be applicable to high user request workloads, web caching strategies benefit from low implementation and update effort. In this regard, the Least Recently Used (LRU) replacement principle is a simple and widely-used method. Despite its popularity, LRU has deficits in the achieved hit rate performance and cannot consider transport and network optimization criteria for selecting content to be cached. As a result, many alternatives have been proposed in the literature, which improve the cache performance at the cost of higher complexity. In this work, we evaluate the implementation complexity and runtime performance of LRU, Least Frequently Used (LFU), and score based strategies in the class of fast O(1) updates with constant effort per request. We implement Window LFU (W-LFU) within this class and show that O(1) update effort can be achieved. We further compare fast update schemes of Score Gated LRU and new Score Gated Polling (SGP). SGP is simpler than LRU and provides full flexibility for arbitrary score assessment per data object as information basis for performance optimization regarding network cost and quality measures.

This paper addresses the problem of querying Knowledge bases (KBs) that store semantic big data. For efficiently querying data the most important factor is cache replacement policy, which determines the overall query response. As cache is limited in size, less frequently accessed data should be removed to provide more space to hot triples (frequently accessed). So, to achieve a similar performance to RDBMS, we proposed an Adaptive Cache Replacement (ACR) policy that predict the hot triples from query log. Moreover, performance bottleneck of triplestore, makes realworld application difficult. To achieve a closer performance similar to RDBMS, we have proposed an Adaptive Cache Replacement (ACR) policy that predict the hot triples from query log. Our proposed algorithm effectively replaces cache with high accuracy. To implement cache replacement policy, we have applied exponential smoothing, a forecast method, to collect most frequently accessed triples. The evaluation result shows that the proposed scheme outperforms the existing cache replacement policies, such as LRU (least recently used) and LFU (least frequently used), in terms of higher hit rates and less time overhead.

Internet of things has become a subject of interest across a different industry domain. It includes 6LoWPAN (Low-Power Wireless Personal Area Network) which is used for a variety of application including home automation, sensor networks, manufacturing and industry application etc. However, gathering such a huge amount of data from such a different domain causes a problem of traffic congestion, high reliability, high energy efficiency etc. In order to address such problems, content based routing (CBR) technique is proposed, where routing paths are decided according to the type of content. By routing the correlated data to hop nodes for processing, a higher data aggregation ratio can be obtained, which in turns reducing the traffic congestion and minimizes the energy consumption. CBR is implemented on top of existing RPL (Routing Protocol for Low Power and Lossy network) and implemented in contiki operating system using cooja simulator. The analysis are carried out on the basis average power consumption, packet delivery ratio etc.

Cloud nowaday has become the backbone of the IT infrastructure. Whole of the infrastructure is now being shifted to the clouds, and as the cloud involves all of the networking schemes and the OS images, it inherits all of the vulnerabilities too. And hence securing them is one of our very prior concerns. Malwares are one of the many other problems that have ever growing and hence need to be eradicated from the system. The history of mal wares go long back in time since the advent of computers and hence a lot of techniques has also been already devised to tackle with the problem in some or other way. But most of them fall short in some or other way or are just too heavy to execute on a simple user machine. Our approach devises a 3 - phase exhaustive technique which confirms the detection of any kind of malwares from the host. It also works for the zero-day attacks that are really difficult to cover most times and can be of really high-risk at times. We have thought of a solution to keep the things light weight for the user.

Edge computing can potentially play a crucial role in enabling user authentication and monitoring through context-aware biometrics in military/battlefield applications. For example, in Internet of Military Things (IoMT) or Internet of Battlefield Things (IoBT),an increasing number of ubiquitous sensing and computing devices worn by military personnel and embedded within military equipment (combat suit, instrumented helmets, weapon systems, etc.) are capable of acquiring a variety of static and dynamic biometrics (e.g., face, iris, periocular, fingerprints, heart-rate, gait, gestures, and facial expressions). Such devices may also be capable of collecting operational context data. These data collectively can be used to perform context-adaptive authentication in-the-wild and continuous monitoring of soldier's psychophysical condition in a dedicated edge computing architecture.

We propose a method for transferring an arbitrary style to only a specific object in an image. Style transfer is the process of combining the content of an image and the style of another image into a new image. Our results show that the proposed method can realize style transfer to specific object.

Transmission techniques based on channel coding with feedback are proposed in this paper to enhance the security of wireless communications systems at the physical layer. Reliable and secure transmission over an additive noise Gaussian wiretap channel is investigated using Bose-Chaudhuri-Hocquenghem (BCH) and Low-Density Parity-Check (LDPC) channel codes. A hybrid automatic repeat-request (HARQ) protocol is used to allow for the retransmission of coded packets requested by the intended receiver (Bob). It is assumed that an eavesdropper (Eve) has access to all forward and feedback transmitted packets. To limit the information leakage to Eve, retransmitted packets are subdivided into smaller granular subpackets. Retransmissions are stopped as soon as the decoding process at the legitimate (Bob) receiver converges. For the hard decision decoded BCH codes, a framework to compute the frame error probability with granular HARQ is proposed. For LDPC codes, the HARQ retransmission requests are based on received symbols likelihood computations: the legitimate recipient request for the retransmission of the set of bits that are more likely to help for successful LDPC decoding. The performances of the proposed techniques are assessed for nul and negative security gap (SG) values, that is when the eavesdropper's channel benefits from equal or better channel conditions than the legitimate channel.

The following is a research conducted on the Dark Web to study and identify the ins and outs of the dark web, what the dark web is all about, the various methods available to access the dark web and many others. The researchers have also included the steps and precautions taken before the dark web was opened. Apart from that, the findings and the website links / URL are also included along with a description of the sites. The primary usage of the dark web and some of the researcher's experience has been further documented in this research paper.

The Controller Area Network (CAN) is a broadcast communications network invented by Robert Bosch GmbH in 1986. CAN is the standard communication network found in automobiles, industry equipment, and many space applications. To be used in these environments, CAN is designed for efficiency and reliability, rather than security. This research paper closely examines the security risks within the CAN protocol and proposes a feasible solution. In this research, we investigate the problems with implementing certain security features in the CAN protocol, such as message authentication and protections against replay and denial-of-service (DoS) attacks. We identify the restrictions of the CAN bus, and we demonstrate how our proposed implementation meets these restrictions. Many previously proposed solutions lack security, feasibility, and/or efficiency; however, a solution must not drastically hinder the real-time operation speed of the network. The solution proposed in this research is tested with a simulative CAN environment. This paper proposes an alteration to the standard CAN bus nodes and the CAN protocol to better protect automobiles and other CAN-related systems from attacks.

In this paper, we present the design of Intelligent Security Lock prototype which acts as a smart electronic/digital door locking system. The design of lock device and software system including app is discussed. The paper presents idea to control the lock using mobile app via Bluetooth. The lock satisfies comprehensive security requirements using state of the art technologies. It provides strong authentication using face recognition on app. It stores records of all lock/unlock operations with date and time. It also provides intrusion detection notification and real time camera surveillance on app. Hence, the lock is a unique combination of various aforementioned security features providing absolute solution to problem of security.

We present an approach to tracking the behaviour of an attacker on a decoy system, where the decoy communicates with the real system only through low energy bluetooth. The result is a low-cost solution that does not interrupt the live system, while limiting potential damage. The attacker has no way to detect that they are being monitored, while their actions are being logged for further investigation. The system has been physically implemented using Raspberry PI and Arduino boards to replicate practical performance.

The need for security in today's world has become a mandatory issue to look after. With the increase in a number of thefts, it has become a necessity to implement a smart security system. Due to the high cost of the existing smart security systems which use conventional Bluetooth and other wireless technologies and their relatively high energy consumption, implementing a security system with low energy consumption at a low cost has become the need of the hour. The objective of the paper is to build a cost effective and low energy consumption security system using the Bluetooth Low Energy (BLE) technology. This system will help the user to monitor and manage the security of the house even when the user is outside the house with the help of webpage. This paper presents the design and implementation of a security system using PSoC 4 BLE which can automatically lock and unlock the door when the user in the vicinity and leaving the vicinity of the door respectively by establishing a wireless connection between the physical lock and the smartphone. The system also captures an image of a person arriving at the house and transmits it wirelessly to a webpage. The system also notifies the user of any intrusion by sending a message and the image of the intruder to the webpage. The user can also access the door remotely on the go from the website.

Mobile Ad-hoc Network (MANET) is a prominent technology in the wireless networking field in which the movables nodes operates in distributed manner and collaborates with each other in order to provide the multi-hop communication between the source and destination nodes. Generally, the main assumption considered in the MANET is that each node is trusted node. However, in the real scenario, there are some unreliable nodes which perform black hole attack in which the misbehaving nodes attract all the traffic towards itself by giving false information of having the minimum path towards the destination with a very high destination sequence number and drops all the data packets. In the paper, we have presented different categories for black hole attack mitigation techniques and also presented the summary of various techniques along with its drawbacks that need to be considered while designing an efficient protocol.

Mobile ad hoc networks (MANET) is a type of networks that consists of autonomous nodes connecting directly without a top-down network architecture or central controller. Absence of base stations in MANET force the nodes to rely on their adjacent nodes in transmitting messages. The dynamic nature of MANET makes the relationship between nodes untrusted due to mobility of nodes. A malicious node may start denial of service attack at network layer to discard the packets instead of forwarding them to destination which is known as black hole attack. In this paper a secure and trust based approach based on ad hoc on demand distance vector (STAODV) has been proposed to improve the security of AODV routing protocol. The approach isolates the malicious nodes that try to attack the network depending on their previous information. A trust level is attached to each participating node to detect the level of trust of that node. Each incoming packet will be examined to prevent the black hole attack.

Jellyfish attack is type of DoS attack which is difficult to detect and prevent. Jellyfish attack is categorized as JF Reorder Attack, JF Periodic Dropping Attack and JF Delay Variance Attack. JF attack delay data packets for some amount of time before forwarding and after reception which results high end-to-end delay in the network. JF Attack disrupts whole functionality of transmission and reduces the performance of network. In this paper difference of receive time and sending time greater than threshold value then delay occur due to congestion or availability of JF nodes that confirm by checking load of network. This way detect and prevent jellyfish attack.