Major characteristics
\r\n\t
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With more than 30 scientific and technical publications as author and editor under his belt, Umar actively participates in global automotive standardization efforts where he is a Secretary for a Society Automotive Engineers (SAE) Committee.",institutionString:"Sensible 4 Oy",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"1",institution:null}],coeditorOne:{id:"204176",title:"Associate Prof.",name:"Ahmad 'Athif Mohd",middleName:null,surname:"Faudzi",slug:"ahmad-'athif-mohd-faudzi",fullName:"Ahmad 'Athif Mohd Faudzi",profilePictureURL:"https://mts.intechopen.com/storage/users/204176/images/system/204176.png",biography:"Assoc. Prof. Ir. Dr. Ahmad `Athif Bin Mohd Faudzi received the B. Eng. in Computer Engineering, the M. Eng. in Mechatronics and Automatic Control from Universiti Teknologi Malaysia, Malaysia and the Dr. Eng. in System Integration from Okayama University, Japan in 2004, 2006, and 2010 respectively. He was a Visiting Research Fellow at the Tokyo Institute of Technology from 2015 to 2017. From March 2019 to date, he is the Director of the Centre for Artificial Intelligence and Robotics (CAIRO), Universiti Teknologi Malaysia, Malaysia. He is mainly engaged in the research fields of actuators (pneumatic, soft mechanism, hydraulic, and motorized actuators) concentrate his work in field robotics, bioinspired robotics and biomedical applications. He is a Professional Engineer (PEng), a Charted Engineer (CEng), a member of the IEEE Robotics and Automation Society (RAS) and a member of two Akademi Sains Malaysia Special Interest Group (ASM SIG) of Biodiversity and Robotics. He is also the recipient of Top Research Scientist Malaysia (TRSM) 2020 in the area of Robotics. 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The dissemination of cloud computing causes a lot of important information to flow on networks. And such information is stored in data centers and servers. Meanwhile, cyber terrorism and other crimes that aim at such important information are also on the increase and their techniques have been advanced. To respond to these threats, advanced security measures are implemented in Layer 2 (data link layer) and higher layers of the Open System Interconnection (OSI) reference model. However, safety measures of Layer 1 (physical layer) that forms a transmission path have not been established although Layer 1 is an open area. In such a network broadly two issues exist.
For the security of Layer 2 and higher layers cryptography pursuing mathematical complexity is used for decryption calculation. And the basis of safety greatly depends on the performance of computer used by a eavesdropper for decryption. (The safety deteriorates with the increase in performance of computer.)
Security hole shifts to Layer 1 and Layer 1 becomes relatively vulnerable when the safety of Layer 2 and higher layers is strengthened.
For this reason, physical security measures are required in Layer 1 to improve safety. Especially in communication lines requiring high safety, measures for constant monitoring through a dedicated optical fiber path of special line route are presented. But such measures require very high running costs and therefore can be realized only for special purposes. Researches on quantum cryptography for the safety of transmission paths have been made all over the world by above-mentioned background [1]. The quantum cryptography currently studied mainly in Japan and Europe is normally the Quantum Key Distribution (QKD) system using photon transmission. The mainstream of this system is generally called BB84 that was proposed by C.H.Bennett and G.Brassard in 1984 [2]. On the other hand, Y-00 is a new quantum cipher system published by H.P.Yuen(Professor of Northwestern University in US) in 2000 [3]. BB84 uses photon transmission for the QKD system. But Y-00 is the stream cipher system that uses quantum noise existing in continuous light of a laser diode (LD) to directly encrypt data. Y-00, H.P.Yuen and O.Hirota(Professor of Tamagawa University in Japan) made theoretical verification for safety in reports exceeding the Shannon Limit for cryptography in their respective papers for the final version [4]. However, implementation conditions are limited when practical use and dissemination are considered with the current optical communication technology. As one of the Y-00 features, it has been proved that Y-00 is stronger than the current cipher though the ultimate safety (unconditional safety) cannot be achieved by the current technology [5]. Data cannot be completely deciphered by a ciphertext only attack in the currently installed equipment [6]. Also safety can be ensured by the amount of time up to decryption on the fast correlation attack. Y-00 is a physical cipher system and the safety does not depend on calculation amount like general mathematical cryptography. It information hidden by physical phenomena (quantum effect) must be extracted. No shortcut exists because physical working time for extracting this information becomes the basis of safety. Furthermore, the amount of time can be ensured. Astronomical time of this amount of time can be realized also for the currently installed equipment.
The QKD system that controls photon and transmits data with key information put on a single photon can theoretically show the safety effect provided that One-Time-Pad can be achieved as described in section 1.1. (The absolute condition required by One Time Pad is key distribution that achieves unconditional safety.) To achieve this unconditional safety by single-photon transmission, ideal devices and transmission path are necessary. And various conditions for implementation are really added. These conditions become a loop hole. Therefore that disables absolutely secure key distribution and deteriorates safety level to allow eavesdropping [7,8]. For this reason, the practical use of the QKD system is difficult while maintaining safety in the current optical communication system. Adaptability to large-capacity optical communication networks handling a great deal of information and construction of a new special transmission system at the time of introduction of a security system require much costs.Therefore, applications that are available be limited. Realizing a system by reducing these limiting conditions as much as possible is also an important task. Research and development for Y-00 have been placing the highest priority on the application to existing optical communication systems and possibility that made based on current optical communication technologies. As a result, the WDM transmission system can be shared and no further special infrastructure needs to be constructed. Because Y-00 effectively uses the existing optical modulation system, it can follow up technology trends of normal optical transceiver modules. And it also enables high-speeding, integration, and power saving of the equipment.
As described above, research of Y-00 was started by H.P.Yuen and other people at the Northwestern University in the United States. Also research and development on implementation are being made at NuCrypt Limited Liability Company (member company of Northwestern University) [9-11]. In this research, phase modulation on coherent light is used as base and encryption is performed by using phase fluctuation (quantum fluctuation) of light. The phase modulation angle of the light becomes multiple value densely. And logic “1” and logic “0” (binary) are distinguished in the 180 degree opposite phase combination. Only one combination is selected from multiple binary combinations (called bases) for each bit from the key information in synchronization with the receiver. The multi-value phase information on the same circumference is closely arranged like overlapping by quantum fluctuation. Eavesdroppers who have no key information must accurately detect phase information. Normal receivers can predict a set of selected base values by using the common key information and therefore can distinguish information. Several-thousands of phase angle values to be used for modulation are set and Non-Linear Feedback Shift Register (NLFSR) and Advanced Encryption Standard (AES) are used for sorting the base to enhance the safety. They use phase modulation for the Y-00 base to apply it to optical space transmission and achieve highly secure communication between aircraft and the ground. In Japan, O.Hirota of Tamagawa University (in Japan) who had made research together with H.P.Yuen started research of Y-00 on the basis of the widely spread intensity modulation of light [12]. Implementation is made by Hitachi Information & Communication Engineering, Ltd. and its application to existing optical fiber networks is considered [13-18].
Figure1 shows the idea of theoretical safety of Y-00. Theoretical research on ultimate safety of Y-00 is in progress. But if implementation and practicality are considered by present technologies, safety is restricted. However, this restriction can ensure nearly ultimate safety though it is limited by providing essential conditions (astronomical amount of time) for decryption by eavesdroppers through a quantum physical phenomenon. The quantum physical phenomenon means quantum noise (quantum fluctuation) which is an absolute phenomenon that cannot be removed theoretically. Because this phenomenon is completely random, it does not correlate with measured data and the phenomenon cannot be copied. If this phenomenon can diffuse the effect over the signal area, completely decipher is impossible. But differentiation in receiving conditions between normal receiver and eavesdropper is difficult. This will generate trade-off between receiving sensitivity of normal receivers and safety. Therefore ultimate safety cannot be pursued with technical conditions aimed at practical use. Eavesdroppers still cannot avoid physical phenomena of these conditions and acquire correct data. Therefore, direct decryption (cipher text only attack) is impossible. Furthermore, eavesdroppers will attempt to seek for data correlation to get the initial key from acquired sample data like fast correlation attack that makes exhaustive search. In the exhaustive search, phenomena cannot be copied correctly due to effects of physical phenomena. It is disabling parallel processing [19]. Therefore, eavesdropper must be stacked in serial to find correlation of data. In addition, the sample data volume required for decryption is an order of 1E20~1E30 bytes or more by implementing the safety enhancing measures described later. That memory capacity to store the sample data are 1E20~1E30 bytes or more and the sample data acquisition time is several tens of millions to several hundred millions of years (at 10Gbps transmission) even if effects of physical phenomena cannot be diffused over the signal area as described above. This is limited and that is considered to be indecipherable safety. Because it does not depend on computer’s performance unlike the present cryptography that pursues mathematical complexity.
Image of the safety of Y-00
This section mainly describes an example of optical intensity modulation that is generally used in optical communication. A semiconductor laser diode used in general optical communication uses high-output continuous light (coherent light). The generation probability of each photon that forms this coherent light in the phase and optical power directions is unstable during measurement due to quantum phenomenon, and the value of the probability is not uniquely determined. The distribution of this undefined value is handled as a part of shot noise that is generated during the photoelectric conversion in optical communication, which is an element that degrades the receiving sensitivity. However, effects of other classical noise (including thermal noise of receiving amplifier) generated in the receiver become dominant to the receiving sensitivity of optical communication using the normal optical intensity modulation system. Normal receivers of the devised optical modulation system in Y-00 can maintain little quantum noise effect as in the case of conventional optical communication system. Also Y-00 produces an effect of significantly degrading the receiving sensitivity (to an unreceivable level) for eavesdroppers. In other words, is established safety by great difference of Signal-to-Noise-ratio (S/N) between at normal receiver and eavesdropper. In this case, safety will be improved by as close as possible to 0.5 the error rate of eavesdroppers. Measured value of quantum noise that affects optical communication varies at completely random against the phase value and power value of light as described in section 2.2. Therefore, the phase modulation system and intensity modulation system used in the existing optical communication can be applied to the Y-00 encryption system that uses this quantum noise. The following describes basic idea to establish safety.
Multi-value modulation
The normal optical communication performs a multiple value transfer to increase transmission capacity. However in Y-00, only a single bit out of multiplexed values is used for transmitting information and other values are dummy information for eavesdroppers. It is important for multi-values to establish safety that the quantum noise distribution sufficiently overlaps between adjacent levels (both in optical intensity and phase). The number of values becomes several thousands or more depending on conditions.
Encryption and decryption
In the encryption by a transmitter, a combination of binary data (1-bit “1” or “0” level value) is selected for each bit of transmit data from multiple signal values created under conditions (1) using the initial key by the multi-value selection information. This selected binary combination is called base in the same way as phase modulation. The amplitude of this base (between two values) determines the receiving sensitivity of normal receivers in the case of intensity modulation. Therefore, 1/2 (180 degrees for phase modulation) of the maximum signal amplitude is the best value for normal receivers to obtain the optimum receiving sensitivity (Figure2). Decryption process of receiver is essential to distinguish the base that varies in each bit by the best threshold value at signal reception. The amplitude of “1” and “0” levels during reception is estimated based on the multi-value selection information generated by the initial key shared with the transmitter and the threshold value is momentarily moved to the best point to distinguish “1” level and “0” level of the signal. Synchronization of multi-level selection information is critical at this time between the transmitter and receiver. This information is changed at random in each bit between transmitter and receiver (Figure2) [17,18,20-22].
Tapping
People other than those who are engaged in optical communication believe in many cases that optical fiber does not be able to tapping unlike electric wires. The principle of optical fiber transmission is well known. Light travels in an optical fiber while repeating reflection using the refraction of light generated by junction of the core and clad in the optical fiber.
Signal basis and quantum noise
This reflectance varies by bending the optical fiber. If the optical fiber is bent at a sharp angle in particular, the refractive index of the core and clad extremely changes. Therefore optical signal not be able to total reflection. Part of the optical signal will leak out for that. Signal monitoring equipment that uses this principle has been commercialized and used as a measuring instrument. Tapping data from optical fibers has become relatively easy at present due to the technical advance (including high-speed, high-sensitivity detector and low-noise optical amplifier) in optical communication as shown in this example. Measures for improving safety to independently protect transmission paths have become imperative for background mentioned above (Figure3) [22,23].
Eavesdropping from optical fiber
The Y-00 encryption transmission equipment shares the initial key (Seed Key) between transmitter and normal receiver and performs synchronization processing on each side.
And it configures a pair of transceivers between transmitter and receiver. Figure4 shows the basic configuration of the transmitter of the transceiver. A running key that actually makes encryption is generated from the Seed Key shared by the transmitter and receiver. And the base information (a pair of combination) is selected by the running key from multiple values. Furthermore, the signal level to be used actually is determined from this base information. Input data is converted to a multi-value level by the code modulator and is then output from the subsequent electrical/optical (E/O) converter as a Y-00 encryption optical signal. Figure5 shows the basic configuration of the receiver of the transceiver. The Y-00 encryption optical signal sent from the transmitter is converted to an electrical signal (voltage value) by the O/E converter. And base information is created by the Seed Key in the same procedure as the transmitter. A threshold value that allows the best reception signal to be distinguished is selected from this base information. And a value of 0 or 1 is distinguished by the decoder concurrently with the decoding processing to restore the previous data. This synchronized work between transmitter and receiver performs all processing in each bit of the data transmission rate.
Structure of transmitter of Y-00
Structure of receiver of Y-00
The probability of eavesdropper’s signal level detection error increases with the increase in noise distribution range as described about the safety of Y-00 in the previous section. This effect makes it difficult to extract the correlation of signal level samples acquired by a eavesdropper. Therefore more samples are required. This determines irreducible absolute amount of time necessary to obtain the number of samples required for decryption. This time is for the safety of the people it is possible to secure almost forever (finite strictly) if it is an astronomical value (hundreds of millions of years). Quantum noise contained in coherent light is Poisson distribution dependent on the average optical power as is well known. But this quantum noise is effective between adjacent multi-value levels but it cannot affect entire signal area. For this reason, Y-00 enhances safety using various methods [5,17,18]. This quantum noise effect diffusion method is called Randomization. The following introduces several typical methods.
Overlap Selection Keying (OSK)
OSK is a method that allocates logic information (1 or 0) to “High” or “Low” level of light at random to make it difficult for eavesdroppers to decipher signal information “1” or “0” even if they can detect the reception level [16]. Logic of the signal is randomly allocated to a "1" and "0" for each 1bit in order to achieve the OSK. This operation makes it difficult to distinguish whether the signal level detected by tapping is positive logic “1” or negative logic “0”. This method is the same as general stream cipher, but is different in purpose and effect. In the basic Y-00, adjacent signal levels are replaced with bit information “1” and “0” alternately. But eavesdroppers can predict the code by focusing on “1” or “0” every other level. Therefore, the safety level is equivalent to the case when the number of values (number of bases) is reduced to 1/2. To solve this problem, changing bit information on a bit basis can maintain degree of difficulty of decryption [12,15,17,24].
Keyed Deliberate Signal Randomization (KDSR)
Uniforming the conditional probability of multi-value signal detection in Y-00 is important in terms of cryptographic theory. KDSR is used to perform the uniforming [14]. It is a correction technology that does not directly enhance safety but spuriously evenly expands the quantum noise distribution that is effective for eavesdroppers in detecting the multi-value signal level. This method produces effects equivalent to the case where S/N deterioration effect (overlap of quantum noise between adjacent multi-value signal levels) of eavesdroppers is diffused to a wide area as described in the previous section. Figure6 illustrates this mechanism.
Y-00 of optical intensity modulation is causing a level detection error by the quantum noise distribution overlaps of the adjacent signal level as described in the previous section. It is preferable to uniform the entire multi-value signal level. But it degrades the receiving sensitivity of normal receivers making communication difficult. KDSR slightly fluctuates the selected signal level by shifting a part of multi-value level selections conditions at random to solve this problem. Figure 6 (a) shows this state. The k’s true value M is diffused to a range of M±2 by diffusion using KDSR in this example. Furthermore, the noise effect can be
Mechanism of the spread by the random shifter.
diffused to a range of M±5 with the effect of quantum noise distribution (b). The quantum noise distribution function P(k|l) to the individual signal level k diffused by effects of KDSR is evenly arranged, where the l signal level measurement error probability is P(l|i) as the effect of quantum noise at this time. At this time, the effect (a) of KDSR is P(k|l). In addition, the quantum noise effect on the l that are distributed with the effect of (a) is P(l|i). Therefore, the conditional probability P(k|i) of error of true signal level k is shown by the following expression.
With respect to effects on the receiving sensitivity of normal receivers at that time, the signal level degradation PKDS is shown by the following expression. Conditions are described below. Also ±n is quantum noise diffusion effect by KDSR, 2M is number of multi-values and P2M is full signal amplitude.
For example, if 2M=4096 and n=±3, the level of effects on normal receivers deteriorates to about 1/683 of the signal’s full amplitude power. This effect is slight for normal receivers. The following describes KDSR in terms of quantum noise distribution. Figure7 illustrates the range of effects of signal level “i” on the adjacent level when KDSR is not applied. The quantum noise effect is exerted to the reference level ±2 in this example. For this reason, the base selection information error probability is biased and therefore eavesdroppers can estimate a part of the base selection information more easily. KDSR is applied to the base selection information that determines base selection as shown in Figure6 to diffuse noise effects on multi-value levels as shown in Figure8 to solve this problem. Thus the bias in the probability distribution of base selection information error is reduced. And making it very difficult to estimate the base selection information [17,25].
The spread of the noise (KDSR nothing)
The spread of the noise (KDR)
Irregular mapping
Bit error positions become uneven due to effects of the quantum noise distribution in the basic model. Therefore, fast correlation attack may be enabled if the key length is short in the basic array (alternate arrangement of “1” and “0”) of bit information of adjacent multi-value levels determined by the base information [25]. However, bit error positions must be uniform to disable such fast correlation attack. Irregular mapping has been developed in order to provide immunity against fast correlation attack even when the short key length [26]. This method disables eavesdroppers to decrypt Y-00 cipher except for complete Brute Force Attack. Figure9 shows the concept of irregular mapping. Synchronization is established between transmitter and receiver. Then bit information is arranged irregularly in the mapping of the multi-value level corresponding to the base. Bit error positions are evenly diffused because the arrangement of the bit information of adjacent multi-value levels is irregular even if the quantum noise distribution effect range is physically the same. This effect disables the fast correlation attack that uses non-uniformity of bit error rate for decryption when the multi-value signal is returned to bit information [17].
Irregular mapping
Figure10 shows the configuration of the encryption and modulation circuit that is actually mounted in the Y-00 transmitter. Clock is extracted from input plaintext data for self-synchronization by the Clock Data Recovery (CDR) function. The information for synchronization processing and control is added to the original signal in the Y-00 transmission. Therefore, clock frequency is converted in the FIFO circuit and change the data rate. And frame processing is performed by the framer then information required for synchronization is added. OSK processing is added to this signal to generate a main signal to be the original signal as described in section 3.1. On the other hand, multi-value level selection signal is generated as follows. Running Key is generated from the Seed Key as a first. Then a base selection signal to be the original signal is generated using the randomly mapped base configuration information. This selection signal generates a multi-level selection signal level after processing by KDSR. The multi-value level selection signal that is the same as the main signal is weighted by each driver circuit and added to determine the multi-value level and generate an encoding signal for encryption of Y-00. The operating principle of this final-stage processing is the same as that of the Digital to Analog (D/A) converter. By driving the optical external modulator using the Y-00 signal generated, the Y-00 encryption signal becomes an optical signal with valid quantum noise effect. [17,18].
The configuration of the coding of the Y-00 transmitter
Figure11 shows the configuration of the decoder circuit in the Y-00 receiver. The Seed Key information and irregular mapping information are also provided in the receiver as common information. The basic circuit configuration of the decoder is the same as the encryption circuit of the transmitter. However, the receiver does not perform the decoding of KDSR. Therefore, from the decoder outputs a decoding signal (threshold value selection information) of Y-00. The threshold value controller distinguishes the signal on a bit by bit to generate a threshold value level with the best level and timing. Optimum adjustment is made for the threshold level and timing by the Automatic Gain Control (AGC) amplifier and the threshold value controller. Furthermore, the decoder establishes bit synchronization and key synchronization for encryption of Y-00 [17,18].
The configuration of the decoding circuit of the Y-00 receiver
To verified the adaptability to existing optical communication networks as Y-00 encryption equipment. Prototype equipment was produced and evaluated based on the content in section 3. The prototype targeted standard specifications of OC-48 (Optical Carrier: SONET standard) optical communication as IEEE standard considering practical use. Table1 shows evaluation results [17]. The transmission rate of original plaintext data is 2.48832 Gbps conforming to OC-48 and the average optical output power is 0 dBm. This is achieved transmission distance of 50 km without relay.
A receiving sensitivity of -15.3 dBm was obtained at a bit error rate (BER) of 1E-12 with a transmission rate of 2.48832 Gbps and an average optical output power of 0 dBm.
Item | unit | result |
data rate | Gbps | 2.48832 |
transmission distance | km (w/o amp.) | 50 |
output optical power | dBm (ave.) | 0 |
number of basis (number of levels) | - (-) | 2048 (4096) |
Major characteristics
Low-delay real-time transmission of encrypted uncompressed full-specification High-Definition-Television (HDTV) moving picture data was performed using the prototype Y-00 transmission equipment. Figure12 shows the BER in the back-to-back transmission. The minimum receiving sensitivity is -15.3 dBm when BER=1E-12. The average input power of the Y-00 transmission equipment (receiver) is approx -10 dBm and the margin of 5.3 dB. It enabling 40 km transmission when considering the optical fiber loss (approx. 0.25 dB/km). Figure13 shows the transmission system in the experiment. The transmitter converts the OC-48 optical signal from 1.5 Gbps moving picture data of signal source by the High Definition Serial Digital Interface to Synchronous Digital Hierarchy (HD-SDI/SDH) converter. And then encrypts the signal by the Y-00 cipher transmission equipment (transmitter). The encrypted optical signal is transmitted through a 40 km single mode fiber (SMF). The receiver decodes encryption signal. And then restores the original moving picture data by the HD-SDI/SDH converter. The latency of the transmission system shown in Figure13 is approx 500 μs. It is achieving secure real-time high-definition moving picture transmission that hardly shows visible delay in monitor images before and after transmission. This result has verified that the Y-00 cipher transmission equipment is applicable to medical sector and financial system networks which require real-time response [27,28].
Receiver sensitivity of the regular receiver
Real-time HDTV transmission experiment
We made a transmission experiment using an existing commercial line optical fiber to obtain further prospect of practical use. Figure14 shows the system of the transmission experiment that was actually made. The distance of each transmission span is 48 km and the average span attenuation is 14.5 dB. We made a transmission experiment of total distance 192 km with relay at three location using optical fiber amplifiers (EDFA). Figure15 shows the result of receiving sensitivity measured at the reception end. Figure16 shows waveforms of encrypted and decoded signals. We verified a receiving sensitivity of -18.4 dBm and -19.4 dBm respectively at a BER of 1E-12 in 192 km bidirectional transmission. Also we verified adaptability to optical amplifier repeater transmission. In addition, we have confirmed that the encryption of Y-00 can be applied in Fiber Channel (FC) and Gigabit Ether (GbE). The measured latency value of the transmission system was 1.29 ms in total including the delay of fiber length. Furthermore, we made WDM transmission experiment multiplexing optical output signals from two opposed Y-00 units and verified error-free transmission at each wavelength [17,18,21].
km relay Y-00 encrypted transmission through commercial fibers
Received optical power sensitivity (192 km)
Y-00 transmission wave pattern
This section describes a trial toward large-volume transmission that is the trend of optical communication. Y-00 encryption transmission equipment for 10 Gbps transmission based on optical intensity modulation has been developed in japan [30,31]. The design concept of this equipment is the same as the above-mentioned 2.4 Gbps transmission equipment except that dedicated high-speed devices have been developed to realize the equipment. This section describes the result of 360 km transmission experiment using optical fibers (for experiment laid in Tamagawa University) installed in the field. Figure17 shows the configuration of the transmission system. The 360 km transmission path contains nine EDFA for relay at intervals of 40 km using standard single mode fibers (SMF). Dispersion values are adjusted by the dispersion compensating fiber (DCF) and the tunable dispersion compensator (TDC) to set the residual dispersion to +1170 ps/nm. The optical interface conforms to OC-192. The optical output power is -1.7 dBm in the back-to-back transmission and the full-amplitude extinction ratio is 2.5 dB. Furthermore, the encryption contains various types of randomization for enhance safety. The transmission path is also provided with an optical preamplifier and an optical bandpass filter in the receiver to ensure the S/N for normal receivers.
km Y-00 transmission system
Figure18 shows transmission waveforms (eye diagram). They are encrypted waveforms with no eye-opening at each transmission distance. Figure 19 shows characteristic of normal receiver (back-to-back, 40 km, 60 km and 80 km of non repeater transmittion and optical amplifier repeater transmission of 360 km) and the BER of eavesdropper. The minimum receiving sensitivity is -12.2 dBm (BER=1E-12) as shown in Figure 19. And the BER of 360-km transmission is 5.0 × 1E-7. Furthermore, we obtained results that satisfy receiving sensitivity -4 dBm at a BER of 5.0 × 1E-5 which is the target specification considering code error correction under all conditions. We evaluated adjacent signal detection of multi-value signal in the back-to-back transmission to evaluate tapping capability. And obtained a satisfactory result of eavesdropper’s BER larger than 0.4. This evaluation has proved that the Y-00 transmission equipment is sufficiently applicable to 10 Gbps transmission. Thus we could obtain prospects for high-speed transmission [29,30,31].
Based on the Yuen 2000 protocol (Y-00) theory as the research result of H.P.Yuen and O.Hirota, we have developed the Y-00 encryption transmission equipment using quantum noise effects and have verified the practicality of the equipment. We verified the safety and adaptability to existing systems based on trial production results of the equipment and obtained prospects for practical use. The results show the high completeness of the equipment. Hitachi Information & Communication Engineering has been engaged in the development of prototype equipment and is further improving the reliability of the Y-00 encryption transmission equipment for the productization (Figure20). Trial production results show that the Y-00 system can achieve long-haul, large-capacity, high-speed real-
Gbps Y-00 transmission wave form
Bit error rate (10 Gbps)
time transmission with low latency. Thus application of the Y-00 system to various fields can be expected. The Y-00 system is also applicable to uncompressed high-definition image transmission in particular, which extends the range of use. Since conventional optical communication technologies that are being developed at present can be used technically, development trends (such as large capacity, downsizing, and power-saving) can be maintained in common. Furthermore, existing optical communication infrastructures are available and allowing co-existence and combined use with current systems and reducing initial costs. Thus we can expect the use of the Y-00 system in wide applications.
Y-00 encryption transmission equipment for the productization
I would like to thank Prof. Osamu Hirota who provided carefully considered feedback and valuable comments. Special thanks also go to Prof. Kiichi Yamashita, Mr.Makoto Honda, Mr. Shigeto Akutus and Mr.Yoshifumi Doi whose opinions and information have helped me very much throughout the production of this study.
The world population is expected to grow by more than one-third, that is, 2.3 billion people, between the years 2009 and 2050. This growth is slower than the one seen in the past four decades, where the population grew by more than 90% (3.3 billion people). Nearly all the predicted growth is to take place in the developing world, predominantly in Africa. The fastest growth (+114%) is forecasted for sub-Saharan Africa and the slowest growth (+13%) for East and Southeast Asia [1].
Food security exists when all people in a society have adequate food for an active, healthy life at all times [2]. As a broad term, ‘food security’ is defined by: (1) the availability of safe and nutritious food and (2) a guaranteed capability to procure and acquire food of good quality in a socially acceptable way. Food insecurity on the other hand occurs when basic healthy food is not easily accessible, and poor households struggle to secure enough food for their nutritional needs [3]. Food insecurity has been identified as a global crisis [4].
Food insecurity is a major challenge in African countries where the rate at which the population grows far exceeds both the quantity and quality of food required to sustain the population (Figure 1). It is reported that 204 million of the 814 million undernourished people in the world live in sub-Saharan Africa [3]. The root causes of hunger are poverty and poor food distribution. The majority of poor households in sub-Saharan Africa are struggling to access high national and healthy food. Food insecurity and hunger in sub-Saharan Africa are caused by agricultural policy uncertain such as land reform and expropriation land without compensation. Increased food requirements from a growing world population will only escalate existing food security problems. The United Nations estimates that by 2050, 86% of the world’s population living in extreme poverty will be concentrated in sub-Saharan Africa [1]. And in order to ensure food security in the future, current food production levels will need to be increased by at least 70% [1].
Population projections. Source: [1].
Projected climate change and unexpected extreme weather events will worsen the fragile agricultural systems, negatively affecting the natural resource base, particularly in places prone to soil degradation, water scarcity and desertification [5]. The sub-Saharan Africa is well known for relying heavy on rainfed agriculture, however, due to threats posed by extreme climatic events, high climate variability and change, the majority of the climate sensitive sectors are struggling to cope and adapt to challenges posed this natural vagaries. The general effect of climate change on agriculture will differ between different geographic regions, and it will still be difficult for farmers to plan and manage production while preventing crop losses or outbreaks of pests and diseases.
Most of the poor population in Africa depends on agriculture, particularly small-scale farming, as the primary source of their livelihoods. Ensuring food security and poverty reduction in many African countries depends largely on the on the growth and development of the agricultural sector [6]. Agriculture in Africa is dominated by small-scale famers who rely on family labour; with 33 million farms that are less than 2 ha, small-scale farms represent 80% of all farms [7]. The role of small-scale farmers in ensuring food, nutrition security and sustainable rural development in Africa is becoming more crucial as the world faces increasing climate change challenges. Africa needs ecologically sound and climate-resilient farming systems to provide nutritionally balanced food and ensure food security for the most vulnerable.
Getting rural households to actively participate in small-scale agricultural activities for subsistence farming can play a vital role in minimizing the vulnerability to hunger in rural food-insecure households [8]. Studies done in different countries indicate that the gross domestic product (GDP) growth originating from agricultural activities is at least twice as effective in advancing the poorest half of a country’s population than GDP growth generated from any other sector [9]. This benefit from the agricultural sector is to be anticipated considering that 75% of the poor in African countries live in the rural areas and derive their livelihood from agriculture as well as other agriculture-related activities. In another study, [10] also reported that people who depend on agriculture for their livelihood in African countries are typically much poorer than those working in other sectors; these people, however, represent a relatively large portion, often the majority, of the total number of the poor people in these countries.
The term smallholder or small-scale farmers refers to producers who farm in smallholdings [11]. This term includes farmers growing in home-food gardens or homestead gardens, irrigated farmers and people farming in rain-fed fields outside of the homestead [11]. Characteristics differentiating small-scale/smallholder from commercial farmers include scale and size of farm system, proportion of crops sold, household expenditure, and use of family labour, mechanization, capital intensity, financial ability and level of linkages with larger economic systems [11, 12].
According to Antonaci et al. [13], 80% of the food produced in sub-Saharan Africa is produced by smallholder farmers and these farmers are also the largest employers for the local labour force in these countries. This is partly because poverty is still a major challenge in sub-Saharan Africa and also because the agricultural sector also contributes a large share of the GDP and employment. Agriculture employs between 60 and 90% of the total labour force in sub-Saharan Africa [14].
Climate change has had and will continue to have a significant impact on the livelihoods and food security of the rural poor in developing African countries. The 4th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) forecasts that climate change is expected to have a significant effect on water availability and agricultural production in many African countries. Projections by [15] suggest that when the effects of climate change are not considered, the total production of major agricultural products (cereals, fruits and vegetables oilseeds, pulses, roots and tubers, and meat) is projected to double or even triple between 2010 and 2050 (Table 1). However, with the inevitable adverse effect of climate change, production will be adversely affected, and different crops will be affected differently (Table 1). Climate change is projected to have a slightly positive effect on oilseed production and minimum effect on production of pulses, while showing and small negative effects on production of fruit and vegetables and meat [15], (Table 1). The projected negative effects of climate change are higher for cereals (reductions of 2.9% in 2030 and 5.1% in 2050) and roots and tubers (reductions of 1% in 2030 and 1.7% in 2050) compared to when the effect of climate change is not considered (Table 1).
No climate change | Effects of climate change | |||||
---|---|---|---|---|---|---|
2010 | 2030 | 2050 | 2010 | 2030 | 2050 | |
Cereals | 114.2 | 178.4 | 237.1 | 108% | −2.9% | −5.1% |
Fruits and vegetables | 101.4 | 187.4 | 293.7 | 190% | −0.3% | −0.1% |
Oilseeds | 52.9 | 90 | 113.9 | 115% | 0.3% | 1.0% |
Pulses | 11.6 | 18.2 | 27.5 | 137% | 0.0% | 0.0% |
Roots and tubers | 224 | 346.6 | 483.2 | 116% | −1.0% | −1.7% |
Meat | 10.8 | 20.4 | 34.4 | 219% | −0.1% | −0.1% |
Projected effect of climate change on agricultural production (million metric tons) in Africa.
Adapted from: AGRA [15].
Additionally, Makate et al. [12] found that smallholder farmers are faced with a variety of challenges, which include drought, pests and crop diseases, scarce arable land with water, lack of market availability, old age, low level of education, limited availability of quality infrastructure, lack of good cell phone network connections and limited access to quality inputs. ‘A poorly functioning rural economy with undeveloped infrastructure, weak market linkages and poor agricultural support services isolates rural households from the mainstream economy and from important agricultural value-chains’, reported [11].
The economies and food security of many African countries are dependent on sectors that are influenced by changing climate conditions, including agriculture, forestry, fisheries and tourism [3]. The effect of climate change is expected to vary in the different regions, for example, an increase in desertification and decrease in forest cover is expected in the arid north, with rainfall shortages predicted in the Sahara and Sahel, accompanied by soil degradation and an increasing frequency of dust storms. In West Africa, frequent and longer dry periods are projected, whereas rising sea levels will be observed in coastal areas [3].
African countries are more vulnerable to the impacts of climate change because the bulk of the population relies on rain-fed agriculture for food and their livelihoods [16]. In 2007, [17] estimated that the total agricultural yield produced in some African countries could be reduced by as much as 50% in 2020. These authors further projected that the net crop revenues could fall by 90% by the year 2100. These predictions indicate a serious threat to food security, and, by proxy, the achievement of the sustainable developmental goals set by the UN.
The deleterious effects of climate change, climate variability and food insecurity will continue to negatively impact the livelihoods of people in at-risk regions. With the increased frequency of droughts and dry spells, increasingly inconsistent rain, and heavier torrential downpours, the risk of soil erosion and vegetation damage through run-off is likely to increase. Additionally, higher than average temperatures will result in increased evapotranspiration and soil moisture evaporation rates. However, forecasts also indicate that not all changes in climate and climate variability will be negative. For instance, in some parts of the Ethiopian highlands and Mozambique, climate change effects may extend the agricultural growing season owing to increased temperatures and rainfall [14].
The inevitable change in climate necessitates regional and country initiatives to adapt. This is especially critical in African countries where vulnerability is high due to the low capacity to mitigate sudden climatic changes. Adaptation strategies are important to help farmers attain food, income as well as livelihood security despite the unpredictable climatic conditions, and extreme weather events such as droughts and floods [18, 19].
Small-scale agriculture presents an opportunity to improve the livelihoods of the rural poor and ensure food security; however, many of the rural farmers, who had previously managed to successfully cultivate crops for subsistence use and to supplement their income, now experience poor yields or have ceased production. This can be attributed to increased urbanization, poor productivity and competition from commercial agriculture, which is producing food more effectively and at lower prices [20]. It is, therefore, imperative that small-scale farmers adopt new technologies to increase production and, consequently, ensure food security. Improved productivity of these small farmers is the key to providing practical, sustainable solutions able to address the growing problem of food security on a global scale.
Historically, a vibrant agricultural sector has, in most cases, been the foundation for positive economic growth or transformation in many developed countries. Agricultural growth was the precursor to several industrial revolutions in Europe and the United States and more recently to the industrial revolutions in China, Republic of Korea, Taiwan, Vietnam Thailand and other rapidly growing economies in Asia. At the heart of these transformations, investment in agriculture resulted in surpluses of agricultural produce; this helped to keep food prices low and played a hand in stimulating overall economic growth. This agriculture-based economic development helped to create new employment opportunities that were pivotal in absorbing the rural labour surplus. The potential of agriculture to improve a country’s overall economy can never be overemphasized, [21] estimated that 1% increase in crop yields would reduce the total number of people living in poverty by 0.48% in Asia and by 0.72% in Africa.
Farming in most African countries is characterized by many small- and marginal-scale farmers with small farm holdings. These farmers produce only a limited number of crops, which occupy a relatively large portion of the production area. These ‘modern’ agricultural systems have degraded the natural biological interactions responsible for generating ecosystem services that are essential to agriculture, including soil fertility (nutrient cycling and retention), water-holding capacity, pest/disease control and pollination [22]. In ‘modern’ monocultural agricultural systems, crops rely on external nutrient inputs such as fertilizers and pesticides to replace interactions that occurred naturally. This reliance on external inputs has several consequences, including climate change, polluted air and water and the degradation of fertile soils [23]. Growing the same crops continually each year results in the emergence of several biotic and abiotic constraints and progressive reduction in yield. Therefore, crop diversification is one of the cost-effective and simple methods that can be implemented to ensure sustainable and increased agricultural production.
Increasing climate variability, fluctuating temperature and rainfall patterns, is an indicator that agricultural processes will not remain the same as crop and ecosystem responses are also expected to change. These changes comprise variations in nutrient cycling, changes in evapotranspiration, soil moisture content, as well as changes in pest incidences and plant diseases, all these entirely impact food production and food security [24, 25].
A resilient agricultural system is important in mitigating the effects of climate change. Resilience is defined as the ability or tendency of a system to maintain its organizational structure and efficiency after perturbation [26]. Therefore, a resilient agricultural system will keep producing high crop yields even after severe climate changes such as droughts or significant rainfall reductions. Crop biodiversity can therefore provide the connection between climatic stress and resilience of the system because a diversity of organisms is important for ecosystems to perform optimally and provide essential services [27].
According to Vandermeer et al. [28], crop diversification improves the functioning of an ecosystem because different species perform differing roles and consequently occupy different niches within the system. Diversification also increases ecosystem function as some components of the system may seem redundant at some point in time but become important when change in some environmental conditions is experienced. Therefore, the importance of crop diversification is that when climatic or environmental change is experienced, the redundancies within the system permit for continual functioning of the ecosystem and production of high yields [28].
Crop diversification is one of the ways small-scale farmers can use to develop a resilient agricultural system. Crop diversification forms part of the risk aversion strategy, the majority of small-scale farmers have moved away from monocropping system due to high climatic variability and change. It ensures effective use of land, water and other resources for increased yield and productivity, playing a pivotal role in poverty reduction in rural communities. Diversification in farms can also include livestock production, including aquaculture, as well as the production of commercial crops such as cotton, sugar cane, oilseeds, fruits and vegetables. Crop diversification also reduces the risk of crop failure and uncertainty due to unforeseen climate events that could adversely impact agricultural production, including the sudden onset of frost or drought and the emergence of pests [29]. This is achieved by planting crops with varying drought resistance abilities and/or selecting crops for harvest based on their seasonal suitability.
Inclusion of cash crops is particularly important for small-scale farmers in making their farms viable [30]. Diversification helps protect small-scale farmers against drops in profit that ensue if the price for a crop is lower than average in a given year [31]. This improves the purchasing power of the household, thus allowing these households to purchase other food products not produced on the farm. Consequently, farm-level crop diversification should include a wider range of crops; this way, it can contribute positively to improved health, household nutrition and food security, as well as ensuring climate resilience [32]. Thus, diversification can be used to improve and stabilize income flow, thereby providing increases in gainful employment while further reducing farm income variability.
The inclusion of horticultural crops, especially fruits and vegetables, can be used to address food and nutritional security [33]. Households practising crop diversification are more likely to have a varied diet than those who do not [32]. These authors also reported that households practising higher crop diversification are less food-insecure compared to those with relatively lower or no crop diversification.
Agricultural extension can be defined as the application of scientific research and scientific principles/knowledge to agricultural practices through the education of farmers [34]. The role played by extension officers is invaluable in equipping farmers with the necessary skills to improve productivity. Agricultural extension is also critical in translating new knowledge into innovative practices [35].
The declining effectiveness of public extension services is one of the factors impeding the productivity of small-scale famers in most African countries. Increasing the productivity of small-scale farmers requires significant investment and ongoing support in agricultural extension services. Agricultural extension services can provide farmers with the vital tools and critical knowledge needed to adopt and implement new, more sustainable farming methods. Small-scale farmers face a number of risks, which require a more interactive extension system. The adoption of new technologies will serve to increase product yields, improve local food security and livelihoods, as well as build resilience against severe climate changes.
The traditional extension system, which uses a top-down approach in transferring technology, is rapidly becoming outdated in the market-oriented and more competitive climate of today’s agricultural scene. In order to ensure continued and increased contribution of small-scale farmers to food security in Africa, there needs to be renewed emphasis on, as well as new approaches to, agricultural extension. The role of extension officers should not be limited to providing and transferring knowledge for increased productivity, but should also focus on new roles, including linking small-scale farmers to high value and export markets, ensuring sustainable production and mitigating the effect of climate change.
To ensure increased and sustainable crop productivity, sub-Saharan Africa should focus on improved crop varieties that are adapted to diverse environments [36]. The cultivation of improved crop varieties is a strategy that can be used to enhance quality, productivity, health and nutritional value of crops. Improved varieties can also help in building crop resilience to diseases, crop pests and environmental stresses such as the emergence of new pests, water stress (including salinity changes) and heat stress. Using improved crop varieties developed to resist adverse climatic conditions will help to ensure sustained and even increased crop production despite the impacts of climate change. Additionally, varieties with improved nutritional content can reduce nutritional insecurity, thereby reducing susceptibility to diseases and improving overall health.
The use of improved crop varieties has shown to have a positive impact on the performance of smallholder farmers. A study by [36] showed that planting improved groundnut varieties in Uganda resulted in increased income by US$130–254/ha while decreasing poverty by 7–9%. These authors also reported that as the area allocated to improved maize varieties increased in Tanzania, household food security also increased while poverty declined [36]. Similarly, [37] found that the introduction of a new improved rice variety decreased poverty significantly. In a study conducted in Madagascar, [38] reported that communities that readily adopted and planted new crop varieties enjoyed higher crop yields, lower food prices, as well as higher wages for unskilled workers, greater food security and lower poverty.
It is therefore prudent to conclude that to ensure food security in Africa, especially at the household level, we need to rethink the way we produce and distribute food. The empowerment and support of small-scale farmers must be a priority. This includes improved and more inclusive agricultural extension services as well as the use of technology (such as applications) in communicating agricultural advice or climate information. The adoption of new agricultural practices is more important now than it was in the past. When small-scale farmers adopt and plant improved crop varieties they increase their agricultural income and escape poverty, thereby increasing local food security.
Several European countries already have policies and incentives that encourage diversification in farms.
We extend our utmost appreciation to Dr. Taryn Ralph for numerous discussions on this topic and initial editing of this manuscript. The authors acknowledge the Water Research Commission.
The authors declare no conflict of interest.
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